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HEALTH CARE IS AN INFORMATION MANAGEMENT BUSINESS
Clinical Associate Professor T Hannan
FRACPFACHIFACMI
March 2015
THEMES
bull COSTS OF CARE-are national fundamentals different
bull HEALTH CARE IS AN INFORMATION MANAGEMENT BUSINESS-ndash (this is what clinicians do)
bull INFORMATION OVERLOAD-technology driven
bull CARE OUTCOMES-current measures
ndash $VariationCommunicationQualityAccess Readmission rates
bull PATIENTS AS CARE MANAGERS-challenges
bull DO ANY TOOLS HELP US
HEALTH CARE IS UNAFFORDABLE [NEJM 2012]-WORLDWIDEHealth Expenditures as a Percentage of Gross Domestic Product (GDP) in Selected OECD Countries 1960ndash2009
Fineberg HV N Engl J Med 20123661020-1027
AUSTRALIA
26 March 2015
Health care is a service business
bull What clinicians deliverhellip
ndash advice
ndash medication
ndash devices
ndash surgery
ndash physical therapy
26 March 2015
Health care is an information business
26 March 2015
Health care is an information business
bull What clinicians actually dohellip
ndash find information (prior records)
ndash gather information (history physical lab)
ndash record information (notes reports etc)
ndash process information (risksbenefits rarr decisions)
ndash transmit information (advice orders letters)
bull The quality efficiency and effectiveness of care depend on our ability to manage information
rarr Electronic Health Records
ldquoThere is no healthcare without management and there is no management without informationrdquo
Gonzalo Vecina NetoHead Brazilian National Health
Regulatory Agency
26 March 2015
DATAINFORMATIONKNOWLEDGETSUNAMI
26 March 2015 8
A WORLDWIDE HUMAN LIMITED INFORMATION MANAGEMENT AND KNOWLEDGE ACCESS CAPACITY PROBLEM INDEPENDENT OF THE HEALTH CARE MODELLING
ldquoWe must remove ourselves from the lsquounscientific non data driven personal recommendationsrsquo for carerdquo
Dr M Smith CHCF 2009
26 March 2015 10
THREATS TO QUALITY OF CARE
1 OVERUSE-receiving treatment of no value
2 UNDERUSE ndashfailing to receive needed treatment
3 MISUSE-errors and defects in treatmentL Leape Five Years After To Err Is Human What Have We Learned JAMA 20052932384-2390
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010 Dollars Blue) 1821ndash2010
Dollars Blue) 1821ndash2010
Two Hundred Years of Hospital Costs and Mortality mdash MGH and Four Eras of Value in MedicineGregg S Meyer MD Akinluwa A Demehin MPH Xiu Liu MS and Duncan Neuhauser PhD N Engl J Med 2012 3662147-21497-2149
The law of diminishing returns
National Trends in 30-Day Readmission Rates 2002ndash2009
Ashish K N Engl J Med 20123661606-152 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Dr Adeera Levin Director Kidney Function Clinic St Pauls Hospital University of British Columbia Rm 6010-A 1081 Burrard St Vancouver BC V6Z 1Y6 fax 604 806-8120 alevinprovidencehealthbcca
Poorly or Unsupported Clinical Decision MakingRESOURCE UTILISATION-CANADA
OVERUSE-5 CKD patients 25 Duplicate testing
Duplicate Lab Tests by Group BC 2005
0
005
01
015
02
025
03
035
04
045
CVD DM-CVD CKD-CVD-DM CKD-CVD DM CKD DM-CKD
Num
ber
of
Lab T
est
s (M
illi
ons)
2003
2004
2005
Duplicate Lab Tests in 2005 = 114M
COST = $455M
duplicate test defined as same test within 30 days
~$455 M (~$450test)
26 March 2015 14
OVERUSE INAPPROPRIATE USE OF RADIOLOGY
PHARMACY RESOURCES
CANADA 1999-2009
bull Prescriptions-community pharmacies-
bull 272 million (1999) to 483 million (2009)
bull Appropriate vs Inappropriate use
bull CT scanners -198 to 465
bull MRI scanners- 19 to 266 from federal investments
bull Number of Scans
bull 58 increase CT scans
bull 100 increase MRIs (Compared to 2003)
bull Source wwwhealthcouncilcanadaca
Heather Dawson Director Analysis and Reporting Health Council of Canada Healthcare
Policy Vol6 No4 2011
26 March 2015 15
UNITED KINGDOM
RESOURCE UTILISATION- DEM AFTER HOURS
Resource Utilisation - 199899
87 Unnecessary out-of-hours tests
80 Diagnostic uncertainty
79 Medico-legal protection
66 Avoid leaving work for colleagues
71 Prevent criticism from staff (especially Consultants)
76 Lessen anxiety and reduce stress levels
71 Agreed attempts should be made to reduce unnecessary testing
McConnell AA Bowie P Health Bull (Edinb) 2002 Jan60(1)40-3
Unnecessary out-of-hours biochemistry investigations--a subjective view of necessity
26 March 2015 16
PRACTISING UNDER THE FEAR OF
LITIGATION
Without individualized data physicians assume
that they are performing at tolerable rates2000 Project HOPEmdashPeople-to-People Health Foundation Inc Health Affairs MarchApril 2000Medicare Pharmacy Coverage Ensuring Safety Before Funding by Lee N Newcomer
Is More Testing Better
The ldquodiagnosis of uncertaintyrdquo-effects on clinical
decision-making behaviour costs and outcomes(Takes CDM further away from the Dx)
1 N Engl J Med 1975 Jul 31293(5)229-34 Therapeutic decision making a cost-benefit analysis Pauker SG
Kassirer JP
2 Johns RJ Blum BI The use of clinical information systems to control cost as well as to improve care Trans Am ClinClimatol Assoc 197990140-52
COMMUNICATION
Prof L Weed 1989bull They are highly motivated and if they are not nothing works in
the long run anywaybull They do not charge They even pay to helpbull There is one for every member of the population
26 March 2015
1994-2007
COMMUNICATION IN HEALTH CARE
GPs -CONSULTANT COMMUNICATION
3 HOSPITALISED PATIENTS
25 DISCHARGE SUMMARIES NEVER ARRIVED
75 DELAY IN DISCHARGE SUMMARY 253 DAYS
(208 DAYS TO TYPE SUMMARIES IN HOSPITAL)
60 STANDARD LETTERS ARE NOT READ90 REFERRAL LETTERS CONTAIN NO INFORMATION
RELEVANT TO THE PROBLEMS RELATED TO
REFERRAL- MOST ILLEGIBLE
PJ Branger JSDuisterhout Communication in Health Care JAMIA 199469-77
26 March 2015
1994-2007 COMMUNICATION-HOSPITALS TO PRIMARY CARE- KriplaniJAMA 2007
bull Direct communication Hosp-PCP 3-20
bull Availability of Discharge Summary
bull 1st post discharge visit-12-34
bull 4 weeks-51-77
bull Affect on QOC of FU visits-25
bull PCP dissatisfaction HIGH
Communication lacking important information
Diagnostic test results missing 33-63
Treatment or hospital course 7-22
Discharge medications 20-40
Test results pending at discharge 65
Patient or family counselling 90-92
Follow-up plans 2-43
26 March 2015 20
ADVERSE EVENTS -IDENTIFICATION AND PREVENTION
2006 Institute of Medicine -nearly 15 million
preventable adverse drug events each year
Hasan S G T Duncan et al Automatic detection of omissions in medication lists J Am Med
Inform Assoc 18(4) 449-58
ldquoMost hospitals rely on spontaneous voluntary
reporting to identify adverse events but this method
overlooks more than 90 of adverse events detected by
other methods Retrospective chart review
improves the rate of adverse event detection but is
expensive and does not facilitate preventionrdquo
Potential identifiability and preventability of adverse events using information systems D Bates etal J Am Med Informatics Assoc 19941404-411
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
THEMES
bull COSTS OF CARE-are national fundamentals different
bull HEALTH CARE IS AN INFORMATION MANAGEMENT BUSINESS-ndash (this is what clinicians do)
bull INFORMATION OVERLOAD-technology driven
bull CARE OUTCOMES-current measures
ndash $VariationCommunicationQualityAccess Readmission rates
bull PATIENTS AS CARE MANAGERS-challenges
bull DO ANY TOOLS HELP US
HEALTH CARE IS UNAFFORDABLE [NEJM 2012]-WORLDWIDEHealth Expenditures as a Percentage of Gross Domestic Product (GDP) in Selected OECD Countries 1960ndash2009
Fineberg HV N Engl J Med 20123661020-1027
AUSTRALIA
26 March 2015
Health care is a service business
bull What clinicians deliverhellip
ndash advice
ndash medication
ndash devices
ndash surgery
ndash physical therapy
26 March 2015
Health care is an information business
26 March 2015
Health care is an information business
bull What clinicians actually dohellip
ndash find information (prior records)
ndash gather information (history physical lab)
ndash record information (notes reports etc)
ndash process information (risksbenefits rarr decisions)
ndash transmit information (advice orders letters)
bull The quality efficiency and effectiveness of care depend on our ability to manage information
rarr Electronic Health Records
ldquoThere is no healthcare without management and there is no management without informationrdquo
Gonzalo Vecina NetoHead Brazilian National Health
Regulatory Agency
26 March 2015
DATAINFORMATIONKNOWLEDGETSUNAMI
26 March 2015 8
A WORLDWIDE HUMAN LIMITED INFORMATION MANAGEMENT AND KNOWLEDGE ACCESS CAPACITY PROBLEM INDEPENDENT OF THE HEALTH CARE MODELLING
ldquoWe must remove ourselves from the lsquounscientific non data driven personal recommendationsrsquo for carerdquo
Dr M Smith CHCF 2009
26 March 2015 10
THREATS TO QUALITY OF CARE
1 OVERUSE-receiving treatment of no value
2 UNDERUSE ndashfailing to receive needed treatment
3 MISUSE-errors and defects in treatmentL Leape Five Years After To Err Is Human What Have We Learned JAMA 20052932384-2390
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010 Dollars Blue) 1821ndash2010
Dollars Blue) 1821ndash2010
Two Hundred Years of Hospital Costs and Mortality mdash MGH and Four Eras of Value in MedicineGregg S Meyer MD Akinluwa A Demehin MPH Xiu Liu MS and Duncan Neuhauser PhD N Engl J Med 2012 3662147-21497-2149
The law of diminishing returns
National Trends in 30-Day Readmission Rates 2002ndash2009
Ashish K N Engl J Med 20123661606-152 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Dr Adeera Levin Director Kidney Function Clinic St Pauls Hospital University of British Columbia Rm 6010-A 1081 Burrard St Vancouver BC V6Z 1Y6 fax 604 806-8120 alevinprovidencehealthbcca
Poorly or Unsupported Clinical Decision MakingRESOURCE UTILISATION-CANADA
OVERUSE-5 CKD patients 25 Duplicate testing
Duplicate Lab Tests by Group BC 2005
0
005
01
015
02
025
03
035
04
045
CVD DM-CVD CKD-CVD-DM CKD-CVD DM CKD DM-CKD
Num
ber
of
Lab T
est
s (M
illi
ons)
2003
2004
2005
Duplicate Lab Tests in 2005 = 114M
COST = $455M
duplicate test defined as same test within 30 days
~$455 M (~$450test)
26 March 2015 14
OVERUSE INAPPROPRIATE USE OF RADIOLOGY
PHARMACY RESOURCES
CANADA 1999-2009
bull Prescriptions-community pharmacies-
bull 272 million (1999) to 483 million (2009)
bull Appropriate vs Inappropriate use
bull CT scanners -198 to 465
bull MRI scanners- 19 to 266 from federal investments
bull Number of Scans
bull 58 increase CT scans
bull 100 increase MRIs (Compared to 2003)
bull Source wwwhealthcouncilcanadaca
Heather Dawson Director Analysis and Reporting Health Council of Canada Healthcare
Policy Vol6 No4 2011
26 March 2015 15
UNITED KINGDOM
RESOURCE UTILISATION- DEM AFTER HOURS
Resource Utilisation - 199899
87 Unnecessary out-of-hours tests
80 Diagnostic uncertainty
79 Medico-legal protection
66 Avoid leaving work for colleagues
71 Prevent criticism from staff (especially Consultants)
76 Lessen anxiety and reduce stress levels
71 Agreed attempts should be made to reduce unnecessary testing
McConnell AA Bowie P Health Bull (Edinb) 2002 Jan60(1)40-3
Unnecessary out-of-hours biochemistry investigations--a subjective view of necessity
26 March 2015 16
PRACTISING UNDER THE FEAR OF
LITIGATION
Without individualized data physicians assume
that they are performing at tolerable rates2000 Project HOPEmdashPeople-to-People Health Foundation Inc Health Affairs MarchApril 2000Medicare Pharmacy Coverage Ensuring Safety Before Funding by Lee N Newcomer
Is More Testing Better
The ldquodiagnosis of uncertaintyrdquo-effects on clinical
decision-making behaviour costs and outcomes(Takes CDM further away from the Dx)
1 N Engl J Med 1975 Jul 31293(5)229-34 Therapeutic decision making a cost-benefit analysis Pauker SG
Kassirer JP
2 Johns RJ Blum BI The use of clinical information systems to control cost as well as to improve care Trans Am ClinClimatol Assoc 197990140-52
COMMUNICATION
Prof L Weed 1989bull They are highly motivated and if they are not nothing works in
the long run anywaybull They do not charge They even pay to helpbull There is one for every member of the population
26 March 2015
1994-2007
COMMUNICATION IN HEALTH CARE
GPs -CONSULTANT COMMUNICATION
3 HOSPITALISED PATIENTS
25 DISCHARGE SUMMARIES NEVER ARRIVED
75 DELAY IN DISCHARGE SUMMARY 253 DAYS
(208 DAYS TO TYPE SUMMARIES IN HOSPITAL)
60 STANDARD LETTERS ARE NOT READ90 REFERRAL LETTERS CONTAIN NO INFORMATION
RELEVANT TO THE PROBLEMS RELATED TO
REFERRAL- MOST ILLEGIBLE
PJ Branger JSDuisterhout Communication in Health Care JAMIA 199469-77
26 March 2015
1994-2007 COMMUNICATION-HOSPITALS TO PRIMARY CARE- KriplaniJAMA 2007
bull Direct communication Hosp-PCP 3-20
bull Availability of Discharge Summary
bull 1st post discharge visit-12-34
bull 4 weeks-51-77
bull Affect on QOC of FU visits-25
bull PCP dissatisfaction HIGH
Communication lacking important information
Diagnostic test results missing 33-63
Treatment or hospital course 7-22
Discharge medications 20-40
Test results pending at discharge 65
Patient or family counselling 90-92
Follow-up plans 2-43
26 March 2015 20
ADVERSE EVENTS -IDENTIFICATION AND PREVENTION
2006 Institute of Medicine -nearly 15 million
preventable adverse drug events each year
Hasan S G T Duncan et al Automatic detection of omissions in medication lists J Am Med
Inform Assoc 18(4) 449-58
ldquoMost hospitals rely on spontaneous voluntary
reporting to identify adverse events but this method
overlooks more than 90 of adverse events detected by
other methods Retrospective chart review
improves the rate of adverse event detection but is
expensive and does not facilitate preventionrdquo
Potential identifiability and preventability of adverse events using information systems D Bates etal J Am Med Informatics Assoc 19941404-411
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
HEALTH CARE IS UNAFFORDABLE [NEJM 2012]-WORLDWIDEHealth Expenditures as a Percentage of Gross Domestic Product (GDP) in Selected OECD Countries 1960ndash2009
Fineberg HV N Engl J Med 20123661020-1027
AUSTRALIA
26 March 2015
Health care is a service business
bull What clinicians deliverhellip
ndash advice
ndash medication
ndash devices
ndash surgery
ndash physical therapy
26 March 2015
Health care is an information business
26 March 2015
Health care is an information business
bull What clinicians actually dohellip
ndash find information (prior records)
ndash gather information (history physical lab)
ndash record information (notes reports etc)
ndash process information (risksbenefits rarr decisions)
ndash transmit information (advice orders letters)
bull The quality efficiency and effectiveness of care depend on our ability to manage information
rarr Electronic Health Records
ldquoThere is no healthcare without management and there is no management without informationrdquo
Gonzalo Vecina NetoHead Brazilian National Health
Regulatory Agency
26 March 2015
DATAINFORMATIONKNOWLEDGETSUNAMI
26 March 2015 8
A WORLDWIDE HUMAN LIMITED INFORMATION MANAGEMENT AND KNOWLEDGE ACCESS CAPACITY PROBLEM INDEPENDENT OF THE HEALTH CARE MODELLING
ldquoWe must remove ourselves from the lsquounscientific non data driven personal recommendationsrsquo for carerdquo
Dr M Smith CHCF 2009
26 March 2015 10
THREATS TO QUALITY OF CARE
1 OVERUSE-receiving treatment of no value
2 UNDERUSE ndashfailing to receive needed treatment
3 MISUSE-errors and defects in treatmentL Leape Five Years After To Err Is Human What Have We Learned JAMA 20052932384-2390
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010 Dollars Blue) 1821ndash2010
Dollars Blue) 1821ndash2010
Two Hundred Years of Hospital Costs and Mortality mdash MGH and Four Eras of Value in MedicineGregg S Meyer MD Akinluwa A Demehin MPH Xiu Liu MS and Duncan Neuhauser PhD N Engl J Med 2012 3662147-21497-2149
The law of diminishing returns
National Trends in 30-Day Readmission Rates 2002ndash2009
Ashish K N Engl J Med 20123661606-152 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Dr Adeera Levin Director Kidney Function Clinic St Pauls Hospital University of British Columbia Rm 6010-A 1081 Burrard St Vancouver BC V6Z 1Y6 fax 604 806-8120 alevinprovidencehealthbcca
Poorly or Unsupported Clinical Decision MakingRESOURCE UTILISATION-CANADA
OVERUSE-5 CKD patients 25 Duplicate testing
Duplicate Lab Tests by Group BC 2005
0
005
01
015
02
025
03
035
04
045
CVD DM-CVD CKD-CVD-DM CKD-CVD DM CKD DM-CKD
Num
ber
of
Lab T
est
s (M
illi
ons)
2003
2004
2005
Duplicate Lab Tests in 2005 = 114M
COST = $455M
duplicate test defined as same test within 30 days
~$455 M (~$450test)
26 March 2015 14
OVERUSE INAPPROPRIATE USE OF RADIOLOGY
PHARMACY RESOURCES
CANADA 1999-2009
bull Prescriptions-community pharmacies-
bull 272 million (1999) to 483 million (2009)
bull Appropriate vs Inappropriate use
bull CT scanners -198 to 465
bull MRI scanners- 19 to 266 from federal investments
bull Number of Scans
bull 58 increase CT scans
bull 100 increase MRIs (Compared to 2003)
bull Source wwwhealthcouncilcanadaca
Heather Dawson Director Analysis and Reporting Health Council of Canada Healthcare
Policy Vol6 No4 2011
26 March 2015 15
UNITED KINGDOM
RESOURCE UTILISATION- DEM AFTER HOURS
Resource Utilisation - 199899
87 Unnecessary out-of-hours tests
80 Diagnostic uncertainty
79 Medico-legal protection
66 Avoid leaving work for colleagues
71 Prevent criticism from staff (especially Consultants)
76 Lessen anxiety and reduce stress levels
71 Agreed attempts should be made to reduce unnecessary testing
McConnell AA Bowie P Health Bull (Edinb) 2002 Jan60(1)40-3
Unnecessary out-of-hours biochemistry investigations--a subjective view of necessity
26 March 2015 16
PRACTISING UNDER THE FEAR OF
LITIGATION
Without individualized data physicians assume
that they are performing at tolerable rates2000 Project HOPEmdashPeople-to-People Health Foundation Inc Health Affairs MarchApril 2000Medicare Pharmacy Coverage Ensuring Safety Before Funding by Lee N Newcomer
Is More Testing Better
The ldquodiagnosis of uncertaintyrdquo-effects on clinical
decision-making behaviour costs and outcomes(Takes CDM further away from the Dx)
1 N Engl J Med 1975 Jul 31293(5)229-34 Therapeutic decision making a cost-benefit analysis Pauker SG
Kassirer JP
2 Johns RJ Blum BI The use of clinical information systems to control cost as well as to improve care Trans Am ClinClimatol Assoc 197990140-52
COMMUNICATION
Prof L Weed 1989bull They are highly motivated and if they are not nothing works in
the long run anywaybull They do not charge They even pay to helpbull There is one for every member of the population
26 March 2015
1994-2007
COMMUNICATION IN HEALTH CARE
GPs -CONSULTANT COMMUNICATION
3 HOSPITALISED PATIENTS
25 DISCHARGE SUMMARIES NEVER ARRIVED
75 DELAY IN DISCHARGE SUMMARY 253 DAYS
(208 DAYS TO TYPE SUMMARIES IN HOSPITAL)
60 STANDARD LETTERS ARE NOT READ90 REFERRAL LETTERS CONTAIN NO INFORMATION
RELEVANT TO THE PROBLEMS RELATED TO
REFERRAL- MOST ILLEGIBLE
PJ Branger JSDuisterhout Communication in Health Care JAMIA 199469-77
26 March 2015
1994-2007 COMMUNICATION-HOSPITALS TO PRIMARY CARE- KriplaniJAMA 2007
bull Direct communication Hosp-PCP 3-20
bull Availability of Discharge Summary
bull 1st post discharge visit-12-34
bull 4 weeks-51-77
bull Affect on QOC of FU visits-25
bull PCP dissatisfaction HIGH
Communication lacking important information
Diagnostic test results missing 33-63
Treatment or hospital course 7-22
Discharge medications 20-40
Test results pending at discharge 65
Patient or family counselling 90-92
Follow-up plans 2-43
26 March 2015 20
ADVERSE EVENTS -IDENTIFICATION AND PREVENTION
2006 Institute of Medicine -nearly 15 million
preventable adverse drug events each year
Hasan S G T Duncan et al Automatic detection of omissions in medication lists J Am Med
Inform Assoc 18(4) 449-58
ldquoMost hospitals rely on spontaneous voluntary
reporting to identify adverse events but this method
overlooks more than 90 of adverse events detected by
other methods Retrospective chart review
improves the rate of adverse event detection but is
expensive and does not facilitate preventionrdquo
Potential identifiability and preventability of adverse events using information systems D Bates etal J Am Med Informatics Assoc 19941404-411
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015
Health care is a service business
bull What clinicians deliverhellip
ndash advice
ndash medication
ndash devices
ndash surgery
ndash physical therapy
26 March 2015
Health care is an information business
26 March 2015
Health care is an information business
bull What clinicians actually dohellip
ndash find information (prior records)
ndash gather information (history physical lab)
ndash record information (notes reports etc)
ndash process information (risksbenefits rarr decisions)
ndash transmit information (advice orders letters)
bull The quality efficiency and effectiveness of care depend on our ability to manage information
rarr Electronic Health Records
ldquoThere is no healthcare without management and there is no management without informationrdquo
Gonzalo Vecina NetoHead Brazilian National Health
Regulatory Agency
26 March 2015
DATAINFORMATIONKNOWLEDGETSUNAMI
26 March 2015 8
A WORLDWIDE HUMAN LIMITED INFORMATION MANAGEMENT AND KNOWLEDGE ACCESS CAPACITY PROBLEM INDEPENDENT OF THE HEALTH CARE MODELLING
ldquoWe must remove ourselves from the lsquounscientific non data driven personal recommendationsrsquo for carerdquo
Dr M Smith CHCF 2009
26 March 2015 10
THREATS TO QUALITY OF CARE
1 OVERUSE-receiving treatment of no value
2 UNDERUSE ndashfailing to receive needed treatment
3 MISUSE-errors and defects in treatmentL Leape Five Years After To Err Is Human What Have We Learned JAMA 20052932384-2390
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010 Dollars Blue) 1821ndash2010
Dollars Blue) 1821ndash2010
Two Hundred Years of Hospital Costs and Mortality mdash MGH and Four Eras of Value in MedicineGregg S Meyer MD Akinluwa A Demehin MPH Xiu Liu MS and Duncan Neuhauser PhD N Engl J Med 2012 3662147-21497-2149
The law of diminishing returns
National Trends in 30-Day Readmission Rates 2002ndash2009
Ashish K N Engl J Med 20123661606-152 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Dr Adeera Levin Director Kidney Function Clinic St Pauls Hospital University of British Columbia Rm 6010-A 1081 Burrard St Vancouver BC V6Z 1Y6 fax 604 806-8120 alevinprovidencehealthbcca
Poorly or Unsupported Clinical Decision MakingRESOURCE UTILISATION-CANADA
OVERUSE-5 CKD patients 25 Duplicate testing
Duplicate Lab Tests by Group BC 2005
0
005
01
015
02
025
03
035
04
045
CVD DM-CVD CKD-CVD-DM CKD-CVD DM CKD DM-CKD
Num
ber
of
Lab T
est
s (M
illi
ons)
2003
2004
2005
Duplicate Lab Tests in 2005 = 114M
COST = $455M
duplicate test defined as same test within 30 days
~$455 M (~$450test)
26 March 2015 14
OVERUSE INAPPROPRIATE USE OF RADIOLOGY
PHARMACY RESOURCES
CANADA 1999-2009
bull Prescriptions-community pharmacies-
bull 272 million (1999) to 483 million (2009)
bull Appropriate vs Inappropriate use
bull CT scanners -198 to 465
bull MRI scanners- 19 to 266 from federal investments
bull Number of Scans
bull 58 increase CT scans
bull 100 increase MRIs (Compared to 2003)
bull Source wwwhealthcouncilcanadaca
Heather Dawson Director Analysis and Reporting Health Council of Canada Healthcare
Policy Vol6 No4 2011
26 March 2015 15
UNITED KINGDOM
RESOURCE UTILISATION- DEM AFTER HOURS
Resource Utilisation - 199899
87 Unnecessary out-of-hours tests
80 Diagnostic uncertainty
79 Medico-legal protection
66 Avoid leaving work for colleagues
71 Prevent criticism from staff (especially Consultants)
76 Lessen anxiety and reduce stress levels
71 Agreed attempts should be made to reduce unnecessary testing
McConnell AA Bowie P Health Bull (Edinb) 2002 Jan60(1)40-3
Unnecessary out-of-hours biochemistry investigations--a subjective view of necessity
26 March 2015 16
PRACTISING UNDER THE FEAR OF
LITIGATION
Without individualized data physicians assume
that they are performing at tolerable rates2000 Project HOPEmdashPeople-to-People Health Foundation Inc Health Affairs MarchApril 2000Medicare Pharmacy Coverage Ensuring Safety Before Funding by Lee N Newcomer
Is More Testing Better
The ldquodiagnosis of uncertaintyrdquo-effects on clinical
decision-making behaviour costs and outcomes(Takes CDM further away from the Dx)
1 N Engl J Med 1975 Jul 31293(5)229-34 Therapeutic decision making a cost-benefit analysis Pauker SG
Kassirer JP
2 Johns RJ Blum BI The use of clinical information systems to control cost as well as to improve care Trans Am ClinClimatol Assoc 197990140-52
COMMUNICATION
Prof L Weed 1989bull They are highly motivated and if they are not nothing works in
the long run anywaybull They do not charge They even pay to helpbull There is one for every member of the population
26 March 2015
1994-2007
COMMUNICATION IN HEALTH CARE
GPs -CONSULTANT COMMUNICATION
3 HOSPITALISED PATIENTS
25 DISCHARGE SUMMARIES NEVER ARRIVED
75 DELAY IN DISCHARGE SUMMARY 253 DAYS
(208 DAYS TO TYPE SUMMARIES IN HOSPITAL)
60 STANDARD LETTERS ARE NOT READ90 REFERRAL LETTERS CONTAIN NO INFORMATION
RELEVANT TO THE PROBLEMS RELATED TO
REFERRAL- MOST ILLEGIBLE
PJ Branger JSDuisterhout Communication in Health Care JAMIA 199469-77
26 March 2015
1994-2007 COMMUNICATION-HOSPITALS TO PRIMARY CARE- KriplaniJAMA 2007
bull Direct communication Hosp-PCP 3-20
bull Availability of Discharge Summary
bull 1st post discharge visit-12-34
bull 4 weeks-51-77
bull Affect on QOC of FU visits-25
bull PCP dissatisfaction HIGH
Communication lacking important information
Diagnostic test results missing 33-63
Treatment or hospital course 7-22
Discharge medications 20-40
Test results pending at discharge 65
Patient or family counselling 90-92
Follow-up plans 2-43
26 March 2015 20
ADVERSE EVENTS -IDENTIFICATION AND PREVENTION
2006 Institute of Medicine -nearly 15 million
preventable adverse drug events each year
Hasan S G T Duncan et al Automatic detection of omissions in medication lists J Am Med
Inform Assoc 18(4) 449-58
ldquoMost hospitals rely on spontaneous voluntary
reporting to identify adverse events but this method
overlooks more than 90 of adverse events detected by
other methods Retrospective chart review
improves the rate of adverse event detection but is
expensive and does not facilitate preventionrdquo
Potential identifiability and preventability of adverse events using information systems D Bates etal J Am Med Informatics Assoc 19941404-411
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015
Health care is an information business
26 March 2015
Health care is an information business
bull What clinicians actually dohellip
ndash find information (prior records)
ndash gather information (history physical lab)
ndash record information (notes reports etc)
ndash process information (risksbenefits rarr decisions)
ndash transmit information (advice orders letters)
bull The quality efficiency and effectiveness of care depend on our ability to manage information
rarr Electronic Health Records
ldquoThere is no healthcare without management and there is no management without informationrdquo
Gonzalo Vecina NetoHead Brazilian National Health
Regulatory Agency
26 March 2015
DATAINFORMATIONKNOWLEDGETSUNAMI
26 March 2015 8
A WORLDWIDE HUMAN LIMITED INFORMATION MANAGEMENT AND KNOWLEDGE ACCESS CAPACITY PROBLEM INDEPENDENT OF THE HEALTH CARE MODELLING
ldquoWe must remove ourselves from the lsquounscientific non data driven personal recommendationsrsquo for carerdquo
Dr M Smith CHCF 2009
26 March 2015 10
THREATS TO QUALITY OF CARE
1 OVERUSE-receiving treatment of no value
2 UNDERUSE ndashfailing to receive needed treatment
3 MISUSE-errors and defects in treatmentL Leape Five Years After To Err Is Human What Have We Learned JAMA 20052932384-2390
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010 Dollars Blue) 1821ndash2010
Dollars Blue) 1821ndash2010
Two Hundred Years of Hospital Costs and Mortality mdash MGH and Four Eras of Value in MedicineGregg S Meyer MD Akinluwa A Demehin MPH Xiu Liu MS and Duncan Neuhauser PhD N Engl J Med 2012 3662147-21497-2149
The law of diminishing returns
National Trends in 30-Day Readmission Rates 2002ndash2009
Ashish K N Engl J Med 20123661606-152 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Dr Adeera Levin Director Kidney Function Clinic St Pauls Hospital University of British Columbia Rm 6010-A 1081 Burrard St Vancouver BC V6Z 1Y6 fax 604 806-8120 alevinprovidencehealthbcca
Poorly or Unsupported Clinical Decision MakingRESOURCE UTILISATION-CANADA
OVERUSE-5 CKD patients 25 Duplicate testing
Duplicate Lab Tests by Group BC 2005
0
005
01
015
02
025
03
035
04
045
CVD DM-CVD CKD-CVD-DM CKD-CVD DM CKD DM-CKD
Num
ber
of
Lab T
est
s (M
illi
ons)
2003
2004
2005
Duplicate Lab Tests in 2005 = 114M
COST = $455M
duplicate test defined as same test within 30 days
~$455 M (~$450test)
26 March 2015 14
OVERUSE INAPPROPRIATE USE OF RADIOLOGY
PHARMACY RESOURCES
CANADA 1999-2009
bull Prescriptions-community pharmacies-
bull 272 million (1999) to 483 million (2009)
bull Appropriate vs Inappropriate use
bull CT scanners -198 to 465
bull MRI scanners- 19 to 266 from federal investments
bull Number of Scans
bull 58 increase CT scans
bull 100 increase MRIs (Compared to 2003)
bull Source wwwhealthcouncilcanadaca
Heather Dawson Director Analysis and Reporting Health Council of Canada Healthcare
Policy Vol6 No4 2011
26 March 2015 15
UNITED KINGDOM
RESOURCE UTILISATION- DEM AFTER HOURS
Resource Utilisation - 199899
87 Unnecessary out-of-hours tests
80 Diagnostic uncertainty
79 Medico-legal protection
66 Avoid leaving work for colleagues
71 Prevent criticism from staff (especially Consultants)
76 Lessen anxiety and reduce stress levels
71 Agreed attempts should be made to reduce unnecessary testing
McConnell AA Bowie P Health Bull (Edinb) 2002 Jan60(1)40-3
Unnecessary out-of-hours biochemistry investigations--a subjective view of necessity
26 March 2015 16
PRACTISING UNDER THE FEAR OF
LITIGATION
Without individualized data physicians assume
that they are performing at tolerable rates2000 Project HOPEmdashPeople-to-People Health Foundation Inc Health Affairs MarchApril 2000Medicare Pharmacy Coverage Ensuring Safety Before Funding by Lee N Newcomer
Is More Testing Better
The ldquodiagnosis of uncertaintyrdquo-effects on clinical
decision-making behaviour costs and outcomes(Takes CDM further away from the Dx)
1 N Engl J Med 1975 Jul 31293(5)229-34 Therapeutic decision making a cost-benefit analysis Pauker SG
Kassirer JP
2 Johns RJ Blum BI The use of clinical information systems to control cost as well as to improve care Trans Am ClinClimatol Assoc 197990140-52
COMMUNICATION
Prof L Weed 1989bull They are highly motivated and if they are not nothing works in
the long run anywaybull They do not charge They even pay to helpbull There is one for every member of the population
26 March 2015
1994-2007
COMMUNICATION IN HEALTH CARE
GPs -CONSULTANT COMMUNICATION
3 HOSPITALISED PATIENTS
25 DISCHARGE SUMMARIES NEVER ARRIVED
75 DELAY IN DISCHARGE SUMMARY 253 DAYS
(208 DAYS TO TYPE SUMMARIES IN HOSPITAL)
60 STANDARD LETTERS ARE NOT READ90 REFERRAL LETTERS CONTAIN NO INFORMATION
RELEVANT TO THE PROBLEMS RELATED TO
REFERRAL- MOST ILLEGIBLE
PJ Branger JSDuisterhout Communication in Health Care JAMIA 199469-77
26 March 2015
1994-2007 COMMUNICATION-HOSPITALS TO PRIMARY CARE- KriplaniJAMA 2007
bull Direct communication Hosp-PCP 3-20
bull Availability of Discharge Summary
bull 1st post discharge visit-12-34
bull 4 weeks-51-77
bull Affect on QOC of FU visits-25
bull PCP dissatisfaction HIGH
Communication lacking important information
Diagnostic test results missing 33-63
Treatment or hospital course 7-22
Discharge medications 20-40
Test results pending at discharge 65
Patient or family counselling 90-92
Follow-up plans 2-43
26 March 2015 20
ADVERSE EVENTS -IDENTIFICATION AND PREVENTION
2006 Institute of Medicine -nearly 15 million
preventable adverse drug events each year
Hasan S G T Duncan et al Automatic detection of omissions in medication lists J Am Med
Inform Assoc 18(4) 449-58
ldquoMost hospitals rely on spontaneous voluntary
reporting to identify adverse events but this method
overlooks more than 90 of adverse events detected by
other methods Retrospective chart review
improves the rate of adverse event detection but is
expensive and does not facilitate preventionrdquo
Potential identifiability and preventability of adverse events using information systems D Bates etal J Am Med Informatics Assoc 19941404-411
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015
Health care is an information business
bull What clinicians actually dohellip
ndash find information (prior records)
ndash gather information (history physical lab)
ndash record information (notes reports etc)
ndash process information (risksbenefits rarr decisions)
ndash transmit information (advice orders letters)
bull The quality efficiency and effectiveness of care depend on our ability to manage information
rarr Electronic Health Records
ldquoThere is no healthcare without management and there is no management without informationrdquo
Gonzalo Vecina NetoHead Brazilian National Health
Regulatory Agency
26 March 2015
DATAINFORMATIONKNOWLEDGETSUNAMI
26 March 2015 8
A WORLDWIDE HUMAN LIMITED INFORMATION MANAGEMENT AND KNOWLEDGE ACCESS CAPACITY PROBLEM INDEPENDENT OF THE HEALTH CARE MODELLING
ldquoWe must remove ourselves from the lsquounscientific non data driven personal recommendationsrsquo for carerdquo
Dr M Smith CHCF 2009
26 March 2015 10
THREATS TO QUALITY OF CARE
1 OVERUSE-receiving treatment of no value
2 UNDERUSE ndashfailing to receive needed treatment
3 MISUSE-errors and defects in treatmentL Leape Five Years After To Err Is Human What Have We Learned JAMA 20052932384-2390
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010 Dollars Blue) 1821ndash2010
Dollars Blue) 1821ndash2010
Two Hundred Years of Hospital Costs and Mortality mdash MGH and Four Eras of Value in MedicineGregg S Meyer MD Akinluwa A Demehin MPH Xiu Liu MS and Duncan Neuhauser PhD N Engl J Med 2012 3662147-21497-2149
The law of diminishing returns
National Trends in 30-Day Readmission Rates 2002ndash2009
Ashish K N Engl J Med 20123661606-152 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Dr Adeera Levin Director Kidney Function Clinic St Pauls Hospital University of British Columbia Rm 6010-A 1081 Burrard St Vancouver BC V6Z 1Y6 fax 604 806-8120 alevinprovidencehealthbcca
Poorly or Unsupported Clinical Decision MakingRESOURCE UTILISATION-CANADA
OVERUSE-5 CKD patients 25 Duplicate testing
Duplicate Lab Tests by Group BC 2005
0
005
01
015
02
025
03
035
04
045
CVD DM-CVD CKD-CVD-DM CKD-CVD DM CKD DM-CKD
Num
ber
of
Lab T
est
s (M
illi
ons)
2003
2004
2005
Duplicate Lab Tests in 2005 = 114M
COST = $455M
duplicate test defined as same test within 30 days
~$455 M (~$450test)
26 March 2015 14
OVERUSE INAPPROPRIATE USE OF RADIOLOGY
PHARMACY RESOURCES
CANADA 1999-2009
bull Prescriptions-community pharmacies-
bull 272 million (1999) to 483 million (2009)
bull Appropriate vs Inappropriate use
bull CT scanners -198 to 465
bull MRI scanners- 19 to 266 from federal investments
bull Number of Scans
bull 58 increase CT scans
bull 100 increase MRIs (Compared to 2003)
bull Source wwwhealthcouncilcanadaca
Heather Dawson Director Analysis and Reporting Health Council of Canada Healthcare
Policy Vol6 No4 2011
26 March 2015 15
UNITED KINGDOM
RESOURCE UTILISATION- DEM AFTER HOURS
Resource Utilisation - 199899
87 Unnecessary out-of-hours tests
80 Diagnostic uncertainty
79 Medico-legal protection
66 Avoid leaving work for colleagues
71 Prevent criticism from staff (especially Consultants)
76 Lessen anxiety and reduce stress levels
71 Agreed attempts should be made to reduce unnecessary testing
McConnell AA Bowie P Health Bull (Edinb) 2002 Jan60(1)40-3
Unnecessary out-of-hours biochemistry investigations--a subjective view of necessity
26 March 2015 16
PRACTISING UNDER THE FEAR OF
LITIGATION
Without individualized data physicians assume
that they are performing at tolerable rates2000 Project HOPEmdashPeople-to-People Health Foundation Inc Health Affairs MarchApril 2000Medicare Pharmacy Coverage Ensuring Safety Before Funding by Lee N Newcomer
Is More Testing Better
The ldquodiagnosis of uncertaintyrdquo-effects on clinical
decision-making behaviour costs and outcomes(Takes CDM further away from the Dx)
1 N Engl J Med 1975 Jul 31293(5)229-34 Therapeutic decision making a cost-benefit analysis Pauker SG
Kassirer JP
2 Johns RJ Blum BI The use of clinical information systems to control cost as well as to improve care Trans Am ClinClimatol Assoc 197990140-52
COMMUNICATION
Prof L Weed 1989bull They are highly motivated and if they are not nothing works in
the long run anywaybull They do not charge They even pay to helpbull There is one for every member of the population
26 March 2015
1994-2007
COMMUNICATION IN HEALTH CARE
GPs -CONSULTANT COMMUNICATION
3 HOSPITALISED PATIENTS
25 DISCHARGE SUMMARIES NEVER ARRIVED
75 DELAY IN DISCHARGE SUMMARY 253 DAYS
(208 DAYS TO TYPE SUMMARIES IN HOSPITAL)
60 STANDARD LETTERS ARE NOT READ90 REFERRAL LETTERS CONTAIN NO INFORMATION
RELEVANT TO THE PROBLEMS RELATED TO
REFERRAL- MOST ILLEGIBLE
PJ Branger JSDuisterhout Communication in Health Care JAMIA 199469-77
26 March 2015
1994-2007 COMMUNICATION-HOSPITALS TO PRIMARY CARE- KriplaniJAMA 2007
bull Direct communication Hosp-PCP 3-20
bull Availability of Discharge Summary
bull 1st post discharge visit-12-34
bull 4 weeks-51-77
bull Affect on QOC of FU visits-25
bull PCP dissatisfaction HIGH
Communication lacking important information
Diagnostic test results missing 33-63
Treatment or hospital course 7-22
Discharge medications 20-40
Test results pending at discharge 65
Patient or family counselling 90-92
Follow-up plans 2-43
26 March 2015 20
ADVERSE EVENTS -IDENTIFICATION AND PREVENTION
2006 Institute of Medicine -nearly 15 million
preventable adverse drug events each year
Hasan S G T Duncan et al Automatic detection of omissions in medication lists J Am Med
Inform Assoc 18(4) 449-58
ldquoMost hospitals rely on spontaneous voluntary
reporting to identify adverse events but this method
overlooks more than 90 of adverse events detected by
other methods Retrospective chart review
improves the rate of adverse event detection but is
expensive and does not facilitate preventionrdquo
Potential identifiability and preventability of adverse events using information systems D Bates etal J Am Med Informatics Assoc 19941404-411
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015
DATAINFORMATIONKNOWLEDGETSUNAMI
26 March 2015 8
A WORLDWIDE HUMAN LIMITED INFORMATION MANAGEMENT AND KNOWLEDGE ACCESS CAPACITY PROBLEM INDEPENDENT OF THE HEALTH CARE MODELLING
ldquoWe must remove ourselves from the lsquounscientific non data driven personal recommendationsrsquo for carerdquo
Dr M Smith CHCF 2009
26 March 2015 10
THREATS TO QUALITY OF CARE
1 OVERUSE-receiving treatment of no value
2 UNDERUSE ndashfailing to receive needed treatment
3 MISUSE-errors and defects in treatmentL Leape Five Years After To Err Is Human What Have We Learned JAMA 20052932384-2390
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010 Dollars Blue) 1821ndash2010
Dollars Blue) 1821ndash2010
Two Hundred Years of Hospital Costs and Mortality mdash MGH and Four Eras of Value in MedicineGregg S Meyer MD Akinluwa A Demehin MPH Xiu Liu MS and Duncan Neuhauser PhD N Engl J Med 2012 3662147-21497-2149
The law of diminishing returns
National Trends in 30-Day Readmission Rates 2002ndash2009
Ashish K N Engl J Med 20123661606-152 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Dr Adeera Levin Director Kidney Function Clinic St Pauls Hospital University of British Columbia Rm 6010-A 1081 Burrard St Vancouver BC V6Z 1Y6 fax 604 806-8120 alevinprovidencehealthbcca
Poorly or Unsupported Clinical Decision MakingRESOURCE UTILISATION-CANADA
OVERUSE-5 CKD patients 25 Duplicate testing
Duplicate Lab Tests by Group BC 2005
0
005
01
015
02
025
03
035
04
045
CVD DM-CVD CKD-CVD-DM CKD-CVD DM CKD DM-CKD
Num
ber
of
Lab T
est
s (M
illi
ons)
2003
2004
2005
Duplicate Lab Tests in 2005 = 114M
COST = $455M
duplicate test defined as same test within 30 days
~$455 M (~$450test)
26 March 2015 14
OVERUSE INAPPROPRIATE USE OF RADIOLOGY
PHARMACY RESOURCES
CANADA 1999-2009
bull Prescriptions-community pharmacies-
bull 272 million (1999) to 483 million (2009)
bull Appropriate vs Inappropriate use
bull CT scanners -198 to 465
bull MRI scanners- 19 to 266 from federal investments
bull Number of Scans
bull 58 increase CT scans
bull 100 increase MRIs (Compared to 2003)
bull Source wwwhealthcouncilcanadaca
Heather Dawson Director Analysis and Reporting Health Council of Canada Healthcare
Policy Vol6 No4 2011
26 March 2015 15
UNITED KINGDOM
RESOURCE UTILISATION- DEM AFTER HOURS
Resource Utilisation - 199899
87 Unnecessary out-of-hours tests
80 Diagnostic uncertainty
79 Medico-legal protection
66 Avoid leaving work for colleagues
71 Prevent criticism from staff (especially Consultants)
76 Lessen anxiety and reduce stress levels
71 Agreed attempts should be made to reduce unnecessary testing
McConnell AA Bowie P Health Bull (Edinb) 2002 Jan60(1)40-3
Unnecessary out-of-hours biochemistry investigations--a subjective view of necessity
26 March 2015 16
PRACTISING UNDER THE FEAR OF
LITIGATION
Without individualized data physicians assume
that they are performing at tolerable rates2000 Project HOPEmdashPeople-to-People Health Foundation Inc Health Affairs MarchApril 2000Medicare Pharmacy Coverage Ensuring Safety Before Funding by Lee N Newcomer
Is More Testing Better
The ldquodiagnosis of uncertaintyrdquo-effects on clinical
decision-making behaviour costs and outcomes(Takes CDM further away from the Dx)
1 N Engl J Med 1975 Jul 31293(5)229-34 Therapeutic decision making a cost-benefit analysis Pauker SG
Kassirer JP
2 Johns RJ Blum BI The use of clinical information systems to control cost as well as to improve care Trans Am ClinClimatol Assoc 197990140-52
COMMUNICATION
Prof L Weed 1989bull They are highly motivated and if they are not nothing works in
the long run anywaybull They do not charge They even pay to helpbull There is one for every member of the population
26 March 2015
1994-2007
COMMUNICATION IN HEALTH CARE
GPs -CONSULTANT COMMUNICATION
3 HOSPITALISED PATIENTS
25 DISCHARGE SUMMARIES NEVER ARRIVED
75 DELAY IN DISCHARGE SUMMARY 253 DAYS
(208 DAYS TO TYPE SUMMARIES IN HOSPITAL)
60 STANDARD LETTERS ARE NOT READ90 REFERRAL LETTERS CONTAIN NO INFORMATION
RELEVANT TO THE PROBLEMS RELATED TO
REFERRAL- MOST ILLEGIBLE
PJ Branger JSDuisterhout Communication in Health Care JAMIA 199469-77
26 March 2015
1994-2007 COMMUNICATION-HOSPITALS TO PRIMARY CARE- KriplaniJAMA 2007
bull Direct communication Hosp-PCP 3-20
bull Availability of Discharge Summary
bull 1st post discharge visit-12-34
bull 4 weeks-51-77
bull Affect on QOC of FU visits-25
bull PCP dissatisfaction HIGH
Communication lacking important information
Diagnostic test results missing 33-63
Treatment or hospital course 7-22
Discharge medications 20-40
Test results pending at discharge 65
Patient or family counselling 90-92
Follow-up plans 2-43
26 March 2015 20
ADVERSE EVENTS -IDENTIFICATION AND PREVENTION
2006 Institute of Medicine -nearly 15 million
preventable adverse drug events each year
Hasan S G T Duncan et al Automatic detection of omissions in medication lists J Am Med
Inform Assoc 18(4) 449-58
ldquoMost hospitals rely on spontaneous voluntary
reporting to identify adverse events but this method
overlooks more than 90 of adverse events detected by
other methods Retrospective chart review
improves the rate of adverse event detection but is
expensive and does not facilitate preventionrdquo
Potential identifiability and preventability of adverse events using information systems D Bates etal J Am Med Informatics Assoc 19941404-411
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015 8
A WORLDWIDE HUMAN LIMITED INFORMATION MANAGEMENT AND KNOWLEDGE ACCESS CAPACITY PROBLEM INDEPENDENT OF THE HEALTH CARE MODELLING
ldquoWe must remove ourselves from the lsquounscientific non data driven personal recommendationsrsquo for carerdquo
Dr M Smith CHCF 2009
26 March 2015 10
THREATS TO QUALITY OF CARE
1 OVERUSE-receiving treatment of no value
2 UNDERUSE ndashfailing to receive needed treatment
3 MISUSE-errors and defects in treatmentL Leape Five Years After To Err Is Human What Have We Learned JAMA 20052932384-2390
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010 Dollars Blue) 1821ndash2010
Dollars Blue) 1821ndash2010
Two Hundred Years of Hospital Costs and Mortality mdash MGH and Four Eras of Value in MedicineGregg S Meyer MD Akinluwa A Demehin MPH Xiu Liu MS and Duncan Neuhauser PhD N Engl J Med 2012 3662147-21497-2149
The law of diminishing returns
National Trends in 30-Day Readmission Rates 2002ndash2009
Ashish K N Engl J Med 20123661606-152 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Dr Adeera Levin Director Kidney Function Clinic St Pauls Hospital University of British Columbia Rm 6010-A 1081 Burrard St Vancouver BC V6Z 1Y6 fax 604 806-8120 alevinprovidencehealthbcca
Poorly or Unsupported Clinical Decision MakingRESOURCE UTILISATION-CANADA
OVERUSE-5 CKD patients 25 Duplicate testing
Duplicate Lab Tests by Group BC 2005
0
005
01
015
02
025
03
035
04
045
CVD DM-CVD CKD-CVD-DM CKD-CVD DM CKD DM-CKD
Num
ber
of
Lab T
est
s (M
illi
ons)
2003
2004
2005
Duplicate Lab Tests in 2005 = 114M
COST = $455M
duplicate test defined as same test within 30 days
~$455 M (~$450test)
26 March 2015 14
OVERUSE INAPPROPRIATE USE OF RADIOLOGY
PHARMACY RESOURCES
CANADA 1999-2009
bull Prescriptions-community pharmacies-
bull 272 million (1999) to 483 million (2009)
bull Appropriate vs Inappropriate use
bull CT scanners -198 to 465
bull MRI scanners- 19 to 266 from federal investments
bull Number of Scans
bull 58 increase CT scans
bull 100 increase MRIs (Compared to 2003)
bull Source wwwhealthcouncilcanadaca
Heather Dawson Director Analysis and Reporting Health Council of Canada Healthcare
Policy Vol6 No4 2011
26 March 2015 15
UNITED KINGDOM
RESOURCE UTILISATION- DEM AFTER HOURS
Resource Utilisation - 199899
87 Unnecessary out-of-hours tests
80 Diagnostic uncertainty
79 Medico-legal protection
66 Avoid leaving work for colleagues
71 Prevent criticism from staff (especially Consultants)
76 Lessen anxiety and reduce stress levels
71 Agreed attempts should be made to reduce unnecessary testing
McConnell AA Bowie P Health Bull (Edinb) 2002 Jan60(1)40-3
Unnecessary out-of-hours biochemistry investigations--a subjective view of necessity
26 March 2015 16
PRACTISING UNDER THE FEAR OF
LITIGATION
Without individualized data physicians assume
that they are performing at tolerable rates2000 Project HOPEmdashPeople-to-People Health Foundation Inc Health Affairs MarchApril 2000Medicare Pharmacy Coverage Ensuring Safety Before Funding by Lee N Newcomer
Is More Testing Better
The ldquodiagnosis of uncertaintyrdquo-effects on clinical
decision-making behaviour costs and outcomes(Takes CDM further away from the Dx)
1 N Engl J Med 1975 Jul 31293(5)229-34 Therapeutic decision making a cost-benefit analysis Pauker SG
Kassirer JP
2 Johns RJ Blum BI The use of clinical information systems to control cost as well as to improve care Trans Am ClinClimatol Assoc 197990140-52
COMMUNICATION
Prof L Weed 1989bull They are highly motivated and if they are not nothing works in
the long run anywaybull They do not charge They even pay to helpbull There is one for every member of the population
26 March 2015
1994-2007
COMMUNICATION IN HEALTH CARE
GPs -CONSULTANT COMMUNICATION
3 HOSPITALISED PATIENTS
25 DISCHARGE SUMMARIES NEVER ARRIVED
75 DELAY IN DISCHARGE SUMMARY 253 DAYS
(208 DAYS TO TYPE SUMMARIES IN HOSPITAL)
60 STANDARD LETTERS ARE NOT READ90 REFERRAL LETTERS CONTAIN NO INFORMATION
RELEVANT TO THE PROBLEMS RELATED TO
REFERRAL- MOST ILLEGIBLE
PJ Branger JSDuisterhout Communication in Health Care JAMIA 199469-77
26 March 2015
1994-2007 COMMUNICATION-HOSPITALS TO PRIMARY CARE- KriplaniJAMA 2007
bull Direct communication Hosp-PCP 3-20
bull Availability of Discharge Summary
bull 1st post discharge visit-12-34
bull 4 weeks-51-77
bull Affect on QOC of FU visits-25
bull PCP dissatisfaction HIGH
Communication lacking important information
Diagnostic test results missing 33-63
Treatment or hospital course 7-22
Discharge medications 20-40
Test results pending at discharge 65
Patient or family counselling 90-92
Follow-up plans 2-43
26 March 2015 20
ADVERSE EVENTS -IDENTIFICATION AND PREVENTION
2006 Institute of Medicine -nearly 15 million
preventable adverse drug events each year
Hasan S G T Duncan et al Automatic detection of omissions in medication lists J Am Med
Inform Assoc 18(4) 449-58
ldquoMost hospitals rely on spontaneous voluntary
reporting to identify adverse events but this method
overlooks more than 90 of adverse events detected by
other methods Retrospective chart review
improves the rate of adverse event detection but is
expensive and does not facilitate preventionrdquo
Potential identifiability and preventability of adverse events using information systems D Bates etal J Am Med Informatics Assoc 19941404-411
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
A WORLDWIDE HUMAN LIMITED INFORMATION MANAGEMENT AND KNOWLEDGE ACCESS CAPACITY PROBLEM INDEPENDENT OF THE HEALTH CARE MODELLING
ldquoWe must remove ourselves from the lsquounscientific non data driven personal recommendationsrsquo for carerdquo
Dr M Smith CHCF 2009
26 March 2015 10
THREATS TO QUALITY OF CARE
1 OVERUSE-receiving treatment of no value
2 UNDERUSE ndashfailing to receive needed treatment
3 MISUSE-errors and defects in treatmentL Leape Five Years After To Err Is Human What Have We Learned JAMA 20052932384-2390
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010 Dollars Blue) 1821ndash2010
Dollars Blue) 1821ndash2010
Two Hundred Years of Hospital Costs and Mortality mdash MGH and Four Eras of Value in MedicineGregg S Meyer MD Akinluwa A Demehin MPH Xiu Liu MS and Duncan Neuhauser PhD N Engl J Med 2012 3662147-21497-2149
The law of diminishing returns
National Trends in 30-Day Readmission Rates 2002ndash2009
Ashish K N Engl J Med 20123661606-152 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Dr Adeera Levin Director Kidney Function Clinic St Pauls Hospital University of British Columbia Rm 6010-A 1081 Burrard St Vancouver BC V6Z 1Y6 fax 604 806-8120 alevinprovidencehealthbcca
Poorly or Unsupported Clinical Decision MakingRESOURCE UTILISATION-CANADA
OVERUSE-5 CKD patients 25 Duplicate testing
Duplicate Lab Tests by Group BC 2005
0
005
01
015
02
025
03
035
04
045
CVD DM-CVD CKD-CVD-DM CKD-CVD DM CKD DM-CKD
Num
ber
of
Lab T
est
s (M
illi
ons)
2003
2004
2005
Duplicate Lab Tests in 2005 = 114M
COST = $455M
duplicate test defined as same test within 30 days
~$455 M (~$450test)
26 March 2015 14
OVERUSE INAPPROPRIATE USE OF RADIOLOGY
PHARMACY RESOURCES
CANADA 1999-2009
bull Prescriptions-community pharmacies-
bull 272 million (1999) to 483 million (2009)
bull Appropriate vs Inappropriate use
bull CT scanners -198 to 465
bull MRI scanners- 19 to 266 from federal investments
bull Number of Scans
bull 58 increase CT scans
bull 100 increase MRIs (Compared to 2003)
bull Source wwwhealthcouncilcanadaca
Heather Dawson Director Analysis and Reporting Health Council of Canada Healthcare
Policy Vol6 No4 2011
26 March 2015 15
UNITED KINGDOM
RESOURCE UTILISATION- DEM AFTER HOURS
Resource Utilisation - 199899
87 Unnecessary out-of-hours tests
80 Diagnostic uncertainty
79 Medico-legal protection
66 Avoid leaving work for colleagues
71 Prevent criticism from staff (especially Consultants)
76 Lessen anxiety and reduce stress levels
71 Agreed attempts should be made to reduce unnecessary testing
McConnell AA Bowie P Health Bull (Edinb) 2002 Jan60(1)40-3
Unnecessary out-of-hours biochemistry investigations--a subjective view of necessity
26 March 2015 16
PRACTISING UNDER THE FEAR OF
LITIGATION
Without individualized data physicians assume
that they are performing at tolerable rates2000 Project HOPEmdashPeople-to-People Health Foundation Inc Health Affairs MarchApril 2000Medicare Pharmacy Coverage Ensuring Safety Before Funding by Lee N Newcomer
Is More Testing Better
The ldquodiagnosis of uncertaintyrdquo-effects on clinical
decision-making behaviour costs and outcomes(Takes CDM further away from the Dx)
1 N Engl J Med 1975 Jul 31293(5)229-34 Therapeutic decision making a cost-benefit analysis Pauker SG
Kassirer JP
2 Johns RJ Blum BI The use of clinical information systems to control cost as well as to improve care Trans Am ClinClimatol Assoc 197990140-52
COMMUNICATION
Prof L Weed 1989bull They are highly motivated and if they are not nothing works in
the long run anywaybull They do not charge They even pay to helpbull There is one for every member of the population
26 March 2015
1994-2007
COMMUNICATION IN HEALTH CARE
GPs -CONSULTANT COMMUNICATION
3 HOSPITALISED PATIENTS
25 DISCHARGE SUMMARIES NEVER ARRIVED
75 DELAY IN DISCHARGE SUMMARY 253 DAYS
(208 DAYS TO TYPE SUMMARIES IN HOSPITAL)
60 STANDARD LETTERS ARE NOT READ90 REFERRAL LETTERS CONTAIN NO INFORMATION
RELEVANT TO THE PROBLEMS RELATED TO
REFERRAL- MOST ILLEGIBLE
PJ Branger JSDuisterhout Communication in Health Care JAMIA 199469-77
26 March 2015
1994-2007 COMMUNICATION-HOSPITALS TO PRIMARY CARE- KriplaniJAMA 2007
bull Direct communication Hosp-PCP 3-20
bull Availability of Discharge Summary
bull 1st post discharge visit-12-34
bull 4 weeks-51-77
bull Affect on QOC of FU visits-25
bull PCP dissatisfaction HIGH
Communication lacking important information
Diagnostic test results missing 33-63
Treatment or hospital course 7-22
Discharge medications 20-40
Test results pending at discharge 65
Patient or family counselling 90-92
Follow-up plans 2-43
26 March 2015 20
ADVERSE EVENTS -IDENTIFICATION AND PREVENTION
2006 Institute of Medicine -nearly 15 million
preventable adverse drug events each year
Hasan S G T Duncan et al Automatic detection of omissions in medication lists J Am Med
Inform Assoc 18(4) 449-58
ldquoMost hospitals rely on spontaneous voluntary
reporting to identify adverse events but this method
overlooks more than 90 of adverse events detected by
other methods Retrospective chart review
improves the rate of adverse event detection but is
expensive and does not facilitate preventionrdquo
Potential identifiability and preventability of adverse events using information systems D Bates etal J Am Med Informatics Assoc 19941404-411
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015 10
THREATS TO QUALITY OF CARE
1 OVERUSE-receiving treatment of no value
2 UNDERUSE ndashfailing to receive needed treatment
3 MISUSE-errors and defects in treatmentL Leape Five Years After To Err Is Human What Have We Learned JAMA 20052932384-2390
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010 Dollars Blue) 1821ndash2010
Dollars Blue) 1821ndash2010
Two Hundred Years of Hospital Costs and Mortality mdash MGH and Four Eras of Value in MedicineGregg S Meyer MD Akinluwa A Demehin MPH Xiu Liu MS and Duncan Neuhauser PhD N Engl J Med 2012 3662147-21497-2149
The law of diminishing returns
National Trends in 30-Day Readmission Rates 2002ndash2009
Ashish K N Engl J Med 20123661606-152 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Dr Adeera Levin Director Kidney Function Clinic St Pauls Hospital University of British Columbia Rm 6010-A 1081 Burrard St Vancouver BC V6Z 1Y6 fax 604 806-8120 alevinprovidencehealthbcca
Poorly or Unsupported Clinical Decision MakingRESOURCE UTILISATION-CANADA
OVERUSE-5 CKD patients 25 Duplicate testing
Duplicate Lab Tests by Group BC 2005
0
005
01
015
02
025
03
035
04
045
CVD DM-CVD CKD-CVD-DM CKD-CVD DM CKD DM-CKD
Num
ber
of
Lab T
est
s (M
illi
ons)
2003
2004
2005
Duplicate Lab Tests in 2005 = 114M
COST = $455M
duplicate test defined as same test within 30 days
~$455 M (~$450test)
26 March 2015 14
OVERUSE INAPPROPRIATE USE OF RADIOLOGY
PHARMACY RESOURCES
CANADA 1999-2009
bull Prescriptions-community pharmacies-
bull 272 million (1999) to 483 million (2009)
bull Appropriate vs Inappropriate use
bull CT scanners -198 to 465
bull MRI scanners- 19 to 266 from federal investments
bull Number of Scans
bull 58 increase CT scans
bull 100 increase MRIs (Compared to 2003)
bull Source wwwhealthcouncilcanadaca
Heather Dawson Director Analysis and Reporting Health Council of Canada Healthcare
Policy Vol6 No4 2011
26 March 2015 15
UNITED KINGDOM
RESOURCE UTILISATION- DEM AFTER HOURS
Resource Utilisation - 199899
87 Unnecessary out-of-hours tests
80 Diagnostic uncertainty
79 Medico-legal protection
66 Avoid leaving work for colleagues
71 Prevent criticism from staff (especially Consultants)
76 Lessen anxiety and reduce stress levels
71 Agreed attempts should be made to reduce unnecessary testing
McConnell AA Bowie P Health Bull (Edinb) 2002 Jan60(1)40-3
Unnecessary out-of-hours biochemistry investigations--a subjective view of necessity
26 March 2015 16
PRACTISING UNDER THE FEAR OF
LITIGATION
Without individualized data physicians assume
that they are performing at tolerable rates2000 Project HOPEmdashPeople-to-People Health Foundation Inc Health Affairs MarchApril 2000Medicare Pharmacy Coverage Ensuring Safety Before Funding by Lee N Newcomer
Is More Testing Better
The ldquodiagnosis of uncertaintyrdquo-effects on clinical
decision-making behaviour costs and outcomes(Takes CDM further away from the Dx)
1 N Engl J Med 1975 Jul 31293(5)229-34 Therapeutic decision making a cost-benefit analysis Pauker SG
Kassirer JP
2 Johns RJ Blum BI The use of clinical information systems to control cost as well as to improve care Trans Am ClinClimatol Assoc 197990140-52
COMMUNICATION
Prof L Weed 1989bull They are highly motivated and if they are not nothing works in
the long run anywaybull They do not charge They even pay to helpbull There is one for every member of the population
26 March 2015
1994-2007
COMMUNICATION IN HEALTH CARE
GPs -CONSULTANT COMMUNICATION
3 HOSPITALISED PATIENTS
25 DISCHARGE SUMMARIES NEVER ARRIVED
75 DELAY IN DISCHARGE SUMMARY 253 DAYS
(208 DAYS TO TYPE SUMMARIES IN HOSPITAL)
60 STANDARD LETTERS ARE NOT READ90 REFERRAL LETTERS CONTAIN NO INFORMATION
RELEVANT TO THE PROBLEMS RELATED TO
REFERRAL- MOST ILLEGIBLE
PJ Branger JSDuisterhout Communication in Health Care JAMIA 199469-77
26 March 2015
1994-2007 COMMUNICATION-HOSPITALS TO PRIMARY CARE- KriplaniJAMA 2007
bull Direct communication Hosp-PCP 3-20
bull Availability of Discharge Summary
bull 1st post discharge visit-12-34
bull 4 weeks-51-77
bull Affect on QOC of FU visits-25
bull PCP dissatisfaction HIGH
Communication lacking important information
Diagnostic test results missing 33-63
Treatment or hospital course 7-22
Discharge medications 20-40
Test results pending at discharge 65
Patient or family counselling 90-92
Follow-up plans 2-43
26 March 2015 20
ADVERSE EVENTS -IDENTIFICATION AND PREVENTION
2006 Institute of Medicine -nearly 15 million
preventable adverse drug events each year
Hasan S G T Duncan et al Automatic detection of omissions in medication lists J Am Med
Inform Assoc 18(4) 449-58
ldquoMost hospitals rely on spontaneous voluntary
reporting to identify adverse events but this method
overlooks more than 90 of adverse events detected by
other methods Retrospective chart review
improves the rate of adverse event detection but is
expensive and does not facilitate preventionrdquo
Potential identifiability and preventability of adverse events using information systems D Bates etal J Am Med Informatics Assoc 19941404-411
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010
MGHs Inpatient Mortality Rate (Brown) and Adjusted Cost per Patient Who Was Discharged Alive (in 2010 Dollars Blue) 1821ndash2010
Dollars Blue) 1821ndash2010
Two Hundred Years of Hospital Costs and Mortality mdash MGH and Four Eras of Value in MedicineGregg S Meyer MD Akinluwa A Demehin MPH Xiu Liu MS and Duncan Neuhauser PhD N Engl J Med 2012 3662147-21497-2149
The law of diminishing returns
National Trends in 30-Day Readmission Rates 2002ndash2009
Ashish K N Engl J Med 20123661606-152 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Dr Adeera Levin Director Kidney Function Clinic St Pauls Hospital University of British Columbia Rm 6010-A 1081 Burrard St Vancouver BC V6Z 1Y6 fax 604 806-8120 alevinprovidencehealthbcca
Poorly or Unsupported Clinical Decision MakingRESOURCE UTILISATION-CANADA
OVERUSE-5 CKD patients 25 Duplicate testing
Duplicate Lab Tests by Group BC 2005
0
005
01
015
02
025
03
035
04
045
CVD DM-CVD CKD-CVD-DM CKD-CVD DM CKD DM-CKD
Num
ber
of
Lab T
est
s (M
illi
ons)
2003
2004
2005
Duplicate Lab Tests in 2005 = 114M
COST = $455M
duplicate test defined as same test within 30 days
~$455 M (~$450test)
26 March 2015 14
OVERUSE INAPPROPRIATE USE OF RADIOLOGY
PHARMACY RESOURCES
CANADA 1999-2009
bull Prescriptions-community pharmacies-
bull 272 million (1999) to 483 million (2009)
bull Appropriate vs Inappropriate use
bull CT scanners -198 to 465
bull MRI scanners- 19 to 266 from federal investments
bull Number of Scans
bull 58 increase CT scans
bull 100 increase MRIs (Compared to 2003)
bull Source wwwhealthcouncilcanadaca
Heather Dawson Director Analysis and Reporting Health Council of Canada Healthcare
Policy Vol6 No4 2011
26 March 2015 15
UNITED KINGDOM
RESOURCE UTILISATION- DEM AFTER HOURS
Resource Utilisation - 199899
87 Unnecessary out-of-hours tests
80 Diagnostic uncertainty
79 Medico-legal protection
66 Avoid leaving work for colleagues
71 Prevent criticism from staff (especially Consultants)
76 Lessen anxiety and reduce stress levels
71 Agreed attempts should be made to reduce unnecessary testing
McConnell AA Bowie P Health Bull (Edinb) 2002 Jan60(1)40-3
Unnecessary out-of-hours biochemistry investigations--a subjective view of necessity
26 March 2015 16
PRACTISING UNDER THE FEAR OF
LITIGATION
Without individualized data physicians assume
that they are performing at tolerable rates2000 Project HOPEmdashPeople-to-People Health Foundation Inc Health Affairs MarchApril 2000Medicare Pharmacy Coverage Ensuring Safety Before Funding by Lee N Newcomer
Is More Testing Better
The ldquodiagnosis of uncertaintyrdquo-effects on clinical
decision-making behaviour costs and outcomes(Takes CDM further away from the Dx)
1 N Engl J Med 1975 Jul 31293(5)229-34 Therapeutic decision making a cost-benefit analysis Pauker SG
Kassirer JP
2 Johns RJ Blum BI The use of clinical information systems to control cost as well as to improve care Trans Am ClinClimatol Assoc 197990140-52
COMMUNICATION
Prof L Weed 1989bull They are highly motivated and if they are not nothing works in
the long run anywaybull They do not charge They even pay to helpbull There is one for every member of the population
26 March 2015
1994-2007
COMMUNICATION IN HEALTH CARE
GPs -CONSULTANT COMMUNICATION
3 HOSPITALISED PATIENTS
25 DISCHARGE SUMMARIES NEVER ARRIVED
75 DELAY IN DISCHARGE SUMMARY 253 DAYS
(208 DAYS TO TYPE SUMMARIES IN HOSPITAL)
60 STANDARD LETTERS ARE NOT READ90 REFERRAL LETTERS CONTAIN NO INFORMATION
RELEVANT TO THE PROBLEMS RELATED TO
REFERRAL- MOST ILLEGIBLE
PJ Branger JSDuisterhout Communication in Health Care JAMIA 199469-77
26 March 2015
1994-2007 COMMUNICATION-HOSPITALS TO PRIMARY CARE- KriplaniJAMA 2007
bull Direct communication Hosp-PCP 3-20
bull Availability of Discharge Summary
bull 1st post discharge visit-12-34
bull 4 weeks-51-77
bull Affect on QOC of FU visits-25
bull PCP dissatisfaction HIGH
Communication lacking important information
Diagnostic test results missing 33-63
Treatment or hospital course 7-22
Discharge medications 20-40
Test results pending at discharge 65
Patient or family counselling 90-92
Follow-up plans 2-43
26 March 2015 20
ADVERSE EVENTS -IDENTIFICATION AND PREVENTION
2006 Institute of Medicine -nearly 15 million
preventable adverse drug events each year
Hasan S G T Duncan et al Automatic detection of omissions in medication lists J Am Med
Inform Assoc 18(4) 449-58
ldquoMost hospitals rely on spontaneous voluntary
reporting to identify adverse events but this method
overlooks more than 90 of adverse events detected by
other methods Retrospective chart review
improves the rate of adverse event detection but is
expensive and does not facilitate preventionrdquo
Potential identifiability and preventability of adverse events using information systems D Bates etal J Am Med Informatics Assoc 19941404-411
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
National Trends in 30-Day Readmission Rates 2002ndash2009
Ashish K N Engl J Med 20123661606-152 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Dr Adeera Levin Director Kidney Function Clinic St Pauls Hospital University of British Columbia Rm 6010-A 1081 Burrard St Vancouver BC V6Z 1Y6 fax 604 806-8120 alevinprovidencehealthbcca
Poorly or Unsupported Clinical Decision MakingRESOURCE UTILISATION-CANADA
OVERUSE-5 CKD patients 25 Duplicate testing
Duplicate Lab Tests by Group BC 2005
0
005
01
015
02
025
03
035
04
045
CVD DM-CVD CKD-CVD-DM CKD-CVD DM CKD DM-CKD
Num
ber
of
Lab T
est
s (M
illi
ons)
2003
2004
2005
Duplicate Lab Tests in 2005 = 114M
COST = $455M
duplicate test defined as same test within 30 days
~$455 M (~$450test)
26 March 2015 14
OVERUSE INAPPROPRIATE USE OF RADIOLOGY
PHARMACY RESOURCES
CANADA 1999-2009
bull Prescriptions-community pharmacies-
bull 272 million (1999) to 483 million (2009)
bull Appropriate vs Inappropriate use
bull CT scanners -198 to 465
bull MRI scanners- 19 to 266 from federal investments
bull Number of Scans
bull 58 increase CT scans
bull 100 increase MRIs (Compared to 2003)
bull Source wwwhealthcouncilcanadaca
Heather Dawson Director Analysis and Reporting Health Council of Canada Healthcare
Policy Vol6 No4 2011
26 March 2015 15
UNITED KINGDOM
RESOURCE UTILISATION- DEM AFTER HOURS
Resource Utilisation - 199899
87 Unnecessary out-of-hours tests
80 Diagnostic uncertainty
79 Medico-legal protection
66 Avoid leaving work for colleagues
71 Prevent criticism from staff (especially Consultants)
76 Lessen anxiety and reduce stress levels
71 Agreed attempts should be made to reduce unnecessary testing
McConnell AA Bowie P Health Bull (Edinb) 2002 Jan60(1)40-3
Unnecessary out-of-hours biochemistry investigations--a subjective view of necessity
26 March 2015 16
PRACTISING UNDER THE FEAR OF
LITIGATION
Without individualized data physicians assume
that they are performing at tolerable rates2000 Project HOPEmdashPeople-to-People Health Foundation Inc Health Affairs MarchApril 2000Medicare Pharmacy Coverage Ensuring Safety Before Funding by Lee N Newcomer
Is More Testing Better
The ldquodiagnosis of uncertaintyrdquo-effects on clinical
decision-making behaviour costs and outcomes(Takes CDM further away from the Dx)
1 N Engl J Med 1975 Jul 31293(5)229-34 Therapeutic decision making a cost-benefit analysis Pauker SG
Kassirer JP
2 Johns RJ Blum BI The use of clinical information systems to control cost as well as to improve care Trans Am ClinClimatol Assoc 197990140-52
COMMUNICATION
Prof L Weed 1989bull They are highly motivated and if they are not nothing works in
the long run anywaybull They do not charge They even pay to helpbull There is one for every member of the population
26 March 2015
1994-2007
COMMUNICATION IN HEALTH CARE
GPs -CONSULTANT COMMUNICATION
3 HOSPITALISED PATIENTS
25 DISCHARGE SUMMARIES NEVER ARRIVED
75 DELAY IN DISCHARGE SUMMARY 253 DAYS
(208 DAYS TO TYPE SUMMARIES IN HOSPITAL)
60 STANDARD LETTERS ARE NOT READ90 REFERRAL LETTERS CONTAIN NO INFORMATION
RELEVANT TO THE PROBLEMS RELATED TO
REFERRAL- MOST ILLEGIBLE
PJ Branger JSDuisterhout Communication in Health Care JAMIA 199469-77
26 March 2015
1994-2007 COMMUNICATION-HOSPITALS TO PRIMARY CARE- KriplaniJAMA 2007
bull Direct communication Hosp-PCP 3-20
bull Availability of Discharge Summary
bull 1st post discharge visit-12-34
bull 4 weeks-51-77
bull Affect on QOC of FU visits-25
bull PCP dissatisfaction HIGH
Communication lacking important information
Diagnostic test results missing 33-63
Treatment or hospital course 7-22
Discharge medications 20-40
Test results pending at discharge 65
Patient or family counselling 90-92
Follow-up plans 2-43
26 March 2015 20
ADVERSE EVENTS -IDENTIFICATION AND PREVENTION
2006 Institute of Medicine -nearly 15 million
preventable adverse drug events each year
Hasan S G T Duncan et al Automatic detection of omissions in medication lists J Am Med
Inform Assoc 18(4) 449-58
ldquoMost hospitals rely on spontaneous voluntary
reporting to identify adverse events but this method
overlooks more than 90 of adverse events detected by
other methods Retrospective chart review
improves the rate of adverse event detection but is
expensive and does not facilitate preventionrdquo
Potential identifiability and preventability of adverse events using information systems D Bates etal J Am Med Informatics Assoc 19941404-411
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
Dr Adeera Levin Director Kidney Function Clinic St Pauls Hospital University of British Columbia Rm 6010-A 1081 Burrard St Vancouver BC V6Z 1Y6 fax 604 806-8120 alevinprovidencehealthbcca
Poorly or Unsupported Clinical Decision MakingRESOURCE UTILISATION-CANADA
OVERUSE-5 CKD patients 25 Duplicate testing
Duplicate Lab Tests by Group BC 2005
0
005
01
015
02
025
03
035
04
045
CVD DM-CVD CKD-CVD-DM CKD-CVD DM CKD DM-CKD
Num
ber
of
Lab T
est
s (M
illi
ons)
2003
2004
2005
Duplicate Lab Tests in 2005 = 114M
COST = $455M
duplicate test defined as same test within 30 days
~$455 M (~$450test)
26 March 2015 14
OVERUSE INAPPROPRIATE USE OF RADIOLOGY
PHARMACY RESOURCES
CANADA 1999-2009
bull Prescriptions-community pharmacies-
bull 272 million (1999) to 483 million (2009)
bull Appropriate vs Inappropriate use
bull CT scanners -198 to 465
bull MRI scanners- 19 to 266 from federal investments
bull Number of Scans
bull 58 increase CT scans
bull 100 increase MRIs (Compared to 2003)
bull Source wwwhealthcouncilcanadaca
Heather Dawson Director Analysis and Reporting Health Council of Canada Healthcare
Policy Vol6 No4 2011
26 March 2015 15
UNITED KINGDOM
RESOURCE UTILISATION- DEM AFTER HOURS
Resource Utilisation - 199899
87 Unnecessary out-of-hours tests
80 Diagnostic uncertainty
79 Medico-legal protection
66 Avoid leaving work for colleagues
71 Prevent criticism from staff (especially Consultants)
76 Lessen anxiety and reduce stress levels
71 Agreed attempts should be made to reduce unnecessary testing
McConnell AA Bowie P Health Bull (Edinb) 2002 Jan60(1)40-3
Unnecessary out-of-hours biochemistry investigations--a subjective view of necessity
26 March 2015 16
PRACTISING UNDER THE FEAR OF
LITIGATION
Without individualized data physicians assume
that they are performing at tolerable rates2000 Project HOPEmdashPeople-to-People Health Foundation Inc Health Affairs MarchApril 2000Medicare Pharmacy Coverage Ensuring Safety Before Funding by Lee N Newcomer
Is More Testing Better
The ldquodiagnosis of uncertaintyrdquo-effects on clinical
decision-making behaviour costs and outcomes(Takes CDM further away from the Dx)
1 N Engl J Med 1975 Jul 31293(5)229-34 Therapeutic decision making a cost-benefit analysis Pauker SG
Kassirer JP
2 Johns RJ Blum BI The use of clinical information systems to control cost as well as to improve care Trans Am ClinClimatol Assoc 197990140-52
COMMUNICATION
Prof L Weed 1989bull They are highly motivated and if they are not nothing works in
the long run anywaybull They do not charge They even pay to helpbull There is one for every member of the population
26 March 2015
1994-2007
COMMUNICATION IN HEALTH CARE
GPs -CONSULTANT COMMUNICATION
3 HOSPITALISED PATIENTS
25 DISCHARGE SUMMARIES NEVER ARRIVED
75 DELAY IN DISCHARGE SUMMARY 253 DAYS
(208 DAYS TO TYPE SUMMARIES IN HOSPITAL)
60 STANDARD LETTERS ARE NOT READ90 REFERRAL LETTERS CONTAIN NO INFORMATION
RELEVANT TO THE PROBLEMS RELATED TO
REFERRAL- MOST ILLEGIBLE
PJ Branger JSDuisterhout Communication in Health Care JAMIA 199469-77
26 March 2015
1994-2007 COMMUNICATION-HOSPITALS TO PRIMARY CARE- KriplaniJAMA 2007
bull Direct communication Hosp-PCP 3-20
bull Availability of Discharge Summary
bull 1st post discharge visit-12-34
bull 4 weeks-51-77
bull Affect on QOC of FU visits-25
bull PCP dissatisfaction HIGH
Communication lacking important information
Diagnostic test results missing 33-63
Treatment or hospital course 7-22
Discharge medications 20-40
Test results pending at discharge 65
Patient or family counselling 90-92
Follow-up plans 2-43
26 March 2015 20
ADVERSE EVENTS -IDENTIFICATION AND PREVENTION
2006 Institute of Medicine -nearly 15 million
preventable adverse drug events each year
Hasan S G T Duncan et al Automatic detection of omissions in medication lists J Am Med
Inform Assoc 18(4) 449-58
ldquoMost hospitals rely on spontaneous voluntary
reporting to identify adverse events but this method
overlooks more than 90 of adverse events detected by
other methods Retrospective chart review
improves the rate of adverse event detection but is
expensive and does not facilitate preventionrdquo
Potential identifiability and preventability of adverse events using information systems D Bates etal J Am Med Informatics Assoc 19941404-411
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015 14
OVERUSE INAPPROPRIATE USE OF RADIOLOGY
PHARMACY RESOURCES
CANADA 1999-2009
bull Prescriptions-community pharmacies-
bull 272 million (1999) to 483 million (2009)
bull Appropriate vs Inappropriate use
bull CT scanners -198 to 465
bull MRI scanners- 19 to 266 from federal investments
bull Number of Scans
bull 58 increase CT scans
bull 100 increase MRIs (Compared to 2003)
bull Source wwwhealthcouncilcanadaca
Heather Dawson Director Analysis and Reporting Health Council of Canada Healthcare
Policy Vol6 No4 2011
26 March 2015 15
UNITED KINGDOM
RESOURCE UTILISATION- DEM AFTER HOURS
Resource Utilisation - 199899
87 Unnecessary out-of-hours tests
80 Diagnostic uncertainty
79 Medico-legal protection
66 Avoid leaving work for colleagues
71 Prevent criticism from staff (especially Consultants)
76 Lessen anxiety and reduce stress levels
71 Agreed attempts should be made to reduce unnecessary testing
McConnell AA Bowie P Health Bull (Edinb) 2002 Jan60(1)40-3
Unnecessary out-of-hours biochemistry investigations--a subjective view of necessity
26 March 2015 16
PRACTISING UNDER THE FEAR OF
LITIGATION
Without individualized data physicians assume
that they are performing at tolerable rates2000 Project HOPEmdashPeople-to-People Health Foundation Inc Health Affairs MarchApril 2000Medicare Pharmacy Coverage Ensuring Safety Before Funding by Lee N Newcomer
Is More Testing Better
The ldquodiagnosis of uncertaintyrdquo-effects on clinical
decision-making behaviour costs and outcomes(Takes CDM further away from the Dx)
1 N Engl J Med 1975 Jul 31293(5)229-34 Therapeutic decision making a cost-benefit analysis Pauker SG
Kassirer JP
2 Johns RJ Blum BI The use of clinical information systems to control cost as well as to improve care Trans Am ClinClimatol Assoc 197990140-52
COMMUNICATION
Prof L Weed 1989bull They are highly motivated and if they are not nothing works in
the long run anywaybull They do not charge They even pay to helpbull There is one for every member of the population
26 March 2015
1994-2007
COMMUNICATION IN HEALTH CARE
GPs -CONSULTANT COMMUNICATION
3 HOSPITALISED PATIENTS
25 DISCHARGE SUMMARIES NEVER ARRIVED
75 DELAY IN DISCHARGE SUMMARY 253 DAYS
(208 DAYS TO TYPE SUMMARIES IN HOSPITAL)
60 STANDARD LETTERS ARE NOT READ90 REFERRAL LETTERS CONTAIN NO INFORMATION
RELEVANT TO THE PROBLEMS RELATED TO
REFERRAL- MOST ILLEGIBLE
PJ Branger JSDuisterhout Communication in Health Care JAMIA 199469-77
26 March 2015
1994-2007 COMMUNICATION-HOSPITALS TO PRIMARY CARE- KriplaniJAMA 2007
bull Direct communication Hosp-PCP 3-20
bull Availability of Discharge Summary
bull 1st post discharge visit-12-34
bull 4 weeks-51-77
bull Affect on QOC of FU visits-25
bull PCP dissatisfaction HIGH
Communication lacking important information
Diagnostic test results missing 33-63
Treatment or hospital course 7-22
Discharge medications 20-40
Test results pending at discharge 65
Patient or family counselling 90-92
Follow-up plans 2-43
26 March 2015 20
ADVERSE EVENTS -IDENTIFICATION AND PREVENTION
2006 Institute of Medicine -nearly 15 million
preventable adverse drug events each year
Hasan S G T Duncan et al Automatic detection of omissions in medication lists J Am Med
Inform Assoc 18(4) 449-58
ldquoMost hospitals rely on spontaneous voluntary
reporting to identify adverse events but this method
overlooks more than 90 of adverse events detected by
other methods Retrospective chart review
improves the rate of adverse event detection but is
expensive and does not facilitate preventionrdquo
Potential identifiability and preventability of adverse events using information systems D Bates etal J Am Med Informatics Assoc 19941404-411
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015 15
UNITED KINGDOM
RESOURCE UTILISATION- DEM AFTER HOURS
Resource Utilisation - 199899
87 Unnecessary out-of-hours tests
80 Diagnostic uncertainty
79 Medico-legal protection
66 Avoid leaving work for colleagues
71 Prevent criticism from staff (especially Consultants)
76 Lessen anxiety and reduce stress levels
71 Agreed attempts should be made to reduce unnecessary testing
McConnell AA Bowie P Health Bull (Edinb) 2002 Jan60(1)40-3
Unnecessary out-of-hours biochemistry investigations--a subjective view of necessity
26 March 2015 16
PRACTISING UNDER THE FEAR OF
LITIGATION
Without individualized data physicians assume
that they are performing at tolerable rates2000 Project HOPEmdashPeople-to-People Health Foundation Inc Health Affairs MarchApril 2000Medicare Pharmacy Coverage Ensuring Safety Before Funding by Lee N Newcomer
Is More Testing Better
The ldquodiagnosis of uncertaintyrdquo-effects on clinical
decision-making behaviour costs and outcomes(Takes CDM further away from the Dx)
1 N Engl J Med 1975 Jul 31293(5)229-34 Therapeutic decision making a cost-benefit analysis Pauker SG
Kassirer JP
2 Johns RJ Blum BI The use of clinical information systems to control cost as well as to improve care Trans Am ClinClimatol Assoc 197990140-52
COMMUNICATION
Prof L Weed 1989bull They are highly motivated and if they are not nothing works in
the long run anywaybull They do not charge They even pay to helpbull There is one for every member of the population
26 March 2015
1994-2007
COMMUNICATION IN HEALTH CARE
GPs -CONSULTANT COMMUNICATION
3 HOSPITALISED PATIENTS
25 DISCHARGE SUMMARIES NEVER ARRIVED
75 DELAY IN DISCHARGE SUMMARY 253 DAYS
(208 DAYS TO TYPE SUMMARIES IN HOSPITAL)
60 STANDARD LETTERS ARE NOT READ90 REFERRAL LETTERS CONTAIN NO INFORMATION
RELEVANT TO THE PROBLEMS RELATED TO
REFERRAL- MOST ILLEGIBLE
PJ Branger JSDuisterhout Communication in Health Care JAMIA 199469-77
26 March 2015
1994-2007 COMMUNICATION-HOSPITALS TO PRIMARY CARE- KriplaniJAMA 2007
bull Direct communication Hosp-PCP 3-20
bull Availability of Discharge Summary
bull 1st post discharge visit-12-34
bull 4 weeks-51-77
bull Affect on QOC of FU visits-25
bull PCP dissatisfaction HIGH
Communication lacking important information
Diagnostic test results missing 33-63
Treatment or hospital course 7-22
Discharge medications 20-40
Test results pending at discharge 65
Patient or family counselling 90-92
Follow-up plans 2-43
26 March 2015 20
ADVERSE EVENTS -IDENTIFICATION AND PREVENTION
2006 Institute of Medicine -nearly 15 million
preventable adverse drug events each year
Hasan S G T Duncan et al Automatic detection of omissions in medication lists J Am Med
Inform Assoc 18(4) 449-58
ldquoMost hospitals rely on spontaneous voluntary
reporting to identify adverse events but this method
overlooks more than 90 of adverse events detected by
other methods Retrospective chart review
improves the rate of adverse event detection but is
expensive and does not facilitate preventionrdquo
Potential identifiability and preventability of adverse events using information systems D Bates etal J Am Med Informatics Assoc 19941404-411
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015 16
PRACTISING UNDER THE FEAR OF
LITIGATION
Without individualized data physicians assume
that they are performing at tolerable rates2000 Project HOPEmdashPeople-to-People Health Foundation Inc Health Affairs MarchApril 2000Medicare Pharmacy Coverage Ensuring Safety Before Funding by Lee N Newcomer
Is More Testing Better
The ldquodiagnosis of uncertaintyrdquo-effects on clinical
decision-making behaviour costs and outcomes(Takes CDM further away from the Dx)
1 N Engl J Med 1975 Jul 31293(5)229-34 Therapeutic decision making a cost-benefit analysis Pauker SG
Kassirer JP
2 Johns RJ Blum BI The use of clinical information systems to control cost as well as to improve care Trans Am ClinClimatol Assoc 197990140-52
COMMUNICATION
Prof L Weed 1989bull They are highly motivated and if they are not nothing works in
the long run anywaybull They do not charge They even pay to helpbull There is one for every member of the population
26 March 2015
1994-2007
COMMUNICATION IN HEALTH CARE
GPs -CONSULTANT COMMUNICATION
3 HOSPITALISED PATIENTS
25 DISCHARGE SUMMARIES NEVER ARRIVED
75 DELAY IN DISCHARGE SUMMARY 253 DAYS
(208 DAYS TO TYPE SUMMARIES IN HOSPITAL)
60 STANDARD LETTERS ARE NOT READ90 REFERRAL LETTERS CONTAIN NO INFORMATION
RELEVANT TO THE PROBLEMS RELATED TO
REFERRAL- MOST ILLEGIBLE
PJ Branger JSDuisterhout Communication in Health Care JAMIA 199469-77
26 March 2015
1994-2007 COMMUNICATION-HOSPITALS TO PRIMARY CARE- KriplaniJAMA 2007
bull Direct communication Hosp-PCP 3-20
bull Availability of Discharge Summary
bull 1st post discharge visit-12-34
bull 4 weeks-51-77
bull Affect on QOC of FU visits-25
bull PCP dissatisfaction HIGH
Communication lacking important information
Diagnostic test results missing 33-63
Treatment or hospital course 7-22
Discharge medications 20-40
Test results pending at discharge 65
Patient or family counselling 90-92
Follow-up plans 2-43
26 March 2015 20
ADVERSE EVENTS -IDENTIFICATION AND PREVENTION
2006 Institute of Medicine -nearly 15 million
preventable adverse drug events each year
Hasan S G T Duncan et al Automatic detection of omissions in medication lists J Am Med
Inform Assoc 18(4) 449-58
ldquoMost hospitals rely on spontaneous voluntary
reporting to identify adverse events but this method
overlooks more than 90 of adverse events detected by
other methods Retrospective chart review
improves the rate of adverse event detection but is
expensive and does not facilitate preventionrdquo
Potential identifiability and preventability of adverse events using information systems D Bates etal J Am Med Informatics Assoc 19941404-411
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
COMMUNICATION
Prof L Weed 1989bull They are highly motivated and if they are not nothing works in
the long run anywaybull They do not charge They even pay to helpbull There is one for every member of the population
26 March 2015
1994-2007
COMMUNICATION IN HEALTH CARE
GPs -CONSULTANT COMMUNICATION
3 HOSPITALISED PATIENTS
25 DISCHARGE SUMMARIES NEVER ARRIVED
75 DELAY IN DISCHARGE SUMMARY 253 DAYS
(208 DAYS TO TYPE SUMMARIES IN HOSPITAL)
60 STANDARD LETTERS ARE NOT READ90 REFERRAL LETTERS CONTAIN NO INFORMATION
RELEVANT TO THE PROBLEMS RELATED TO
REFERRAL- MOST ILLEGIBLE
PJ Branger JSDuisterhout Communication in Health Care JAMIA 199469-77
26 March 2015
1994-2007 COMMUNICATION-HOSPITALS TO PRIMARY CARE- KriplaniJAMA 2007
bull Direct communication Hosp-PCP 3-20
bull Availability of Discharge Summary
bull 1st post discharge visit-12-34
bull 4 weeks-51-77
bull Affect on QOC of FU visits-25
bull PCP dissatisfaction HIGH
Communication lacking important information
Diagnostic test results missing 33-63
Treatment or hospital course 7-22
Discharge medications 20-40
Test results pending at discharge 65
Patient or family counselling 90-92
Follow-up plans 2-43
26 March 2015 20
ADVERSE EVENTS -IDENTIFICATION AND PREVENTION
2006 Institute of Medicine -nearly 15 million
preventable adverse drug events each year
Hasan S G T Duncan et al Automatic detection of omissions in medication lists J Am Med
Inform Assoc 18(4) 449-58
ldquoMost hospitals rely on spontaneous voluntary
reporting to identify adverse events but this method
overlooks more than 90 of adverse events detected by
other methods Retrospective chart review
improves the rate of adverse event detection but is
expensive and does not facilitate preventionrdquo
Potential identifiability and preventability of adverse events using information systems D Bates etal J Am Med Informatics Assoc 19941404-411
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015
1994-2007
COMMUNICATION IN HEALTH CARE
GPs -CONSULTANT COMMUNICATION
3 HOSPITALISED PATIENTS
25 DISCHARGE SUMMARIES NEVER ARRIVED
75 DELAY IN DISCHARGE SUMMARY 253 DAYS
(208 DAYS TO TYPE SUMMARIES IN HOSPITAL)
60 STANDARD LETTERS ARE NOT READ90 REFERRAL LETTERS CONTAIN NO INFORMATION
RELEVANT TO THE PROBLEMS RELATED TO
REFERRAL- MOST ILLEGIBLE
PJ Branger JSDuisterhout Communication in Health Care JAMIA 199469-77
26 March 2015
1994-2007 COMMUNICATION-HOSPITALS TO PRIMARY CARE- KriplaniJAMA 2007
bull Direct communication Hosp-PCP 3-20
bull Availability of Discharge Summary
bull 1st post discharge visit-12-34
bull 4 weeks-51-77
bull Affect on QOC of FU visits-25
bull PCP dissatisfaction HIGH
Communication lacking important information
Diagnostic test results missing 33-63
Treatment or hospital course 7-22
Discharge medications 20-40
Test results pending at discharge 65
Patient or family counselling 90-92
Follow-up plans 2-43
26 March 2015 20
ADVERSE EVENTS -IDENTIFICATION AND PREVENTION
2006 Institute of Medicine -nearly 15 million
preventable adverse drug events each year
Hasan S G T Duncan et al Automatic detection of omissions in medication lists J Am Med
Inform Assoc 18(4) 449-58
ldquoMost hospitals rely on spontaneous voluntary
reporting to identify adverse events but this method
overlooks more than 90 of adverse events detected by
other methods Retrospective chart review
improves the rate of adverse event detection but is
expensive and does not facilitate preventionrdquo
Potential identifiability and preventability of adverse events using information systems D Bates etal J Am Med Informatics Assoc 19941404-411
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015
1994-2007 COMMUNICATION-HOSPITALS TO PRIMARY CARE- KriplaniJAMA 2007
bull Direct communication Hosp-PCP 3-20
bull Availability of Discharge Summary
bull 1st post discharge visit-12-34
bull 4 weeks-51-77
bull Affect on QOC of FU visits-25
bull PCP dissatisfaction HIGH
Communication lacking important information
Diagnostic test results missing 33-63
Treatment or hospital course 7-22
Discharge medications 20-40
Test results pending at discharge 65
Patient or family counselling 90-92
Follow-up plans 2-43
26 March 2015 20
ADVERSE EVENTS -IDENTIFICATION AND PREVENTION
2006 Institute of Medicine -nearly 15 million
preventable adverse drug events each year
Hasan S G T Duncan et al Automatic detection of omissions in medication lists J Am Med
Inform Assoc 18(4) 449-58
ldquoMost hospitals rely on spontaneous voluntary
reporting to identify adverse events but this method
overlooks more than 90 of adverse events detected by
other methods Retrospective chart review
improves the rate of adverse event detection but is
expensive and does not facilitate preventionrdquo
Potential identifiability and preventability of adverse events using information systems D Bates etal J Am Med Informatics Assoc 19941404-411
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015 20
ADVERSE EVENTS -IDENTIFICATION AND PREVENTION
2006 Institute of Medicine -nearly 15 million
preventable adverse drug events each year
Hasan S G T Duncan et al Automatic detection of omissions in medication lists J Am Med
Inform Assoc 18(4) 449-58
ldquoMost hospitals rely on spontaneous voluntary
reporting to identify adverse events but this method
overlooks more than 90 of adverse events detected by
other methods Retrospective chart review
improves the rate of adverse event detection but is
expensive and does not facilitate preventionrdquo
Potential identifiability and preventability of adverse events using information systems D Bates etal J Am Med Informatics Assoc 19941404-411
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015
Medication-related malpractice claims
bull ADE - 63 of claims Preventable 73
bull IP vs OP = 50 46 -life threatening or fatal
ADE and malpractice claims
severe costly and preventable
Rothschild JM Federico FA Gandhi TK Kaushal R Williams DH Bates DW Analysis of medication-related malpractice claims causes preventability and costs Arch Intern Med 2002 Nov 25162(21)2414-20
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
National Trends in 30-Day Readmission Rates 2002ndash2009
Joynt KE Jha AK N Engl J Med 2012 DOI 101056NEJMp1201598
National Trends in 30-Day Readmission Rates 2002ndash2009
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
Mortality at 30 Days among All Hospitals According to Pay-for-Performance Status 2002ndash2009among All Hospitals According to Pay-for-Performance Status 2002ndash2009
Jha AK et al N Engl J Med 2012 DOI 101056NEJMsa1112351
No evidence that the largest hospital-based pay-for-performance program
led to a decrease in 30-day mortality
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015
CURRENT HEALTH DATA MEASURMENT TOOLS
Case-MixDRGsActivity-Based Funding
bull Lack of a robust measurement program
bull Take years to collect
bull No nationally agreed-on methods for systematically
identifying tracking and reporting adverse events
bull A shortage of good patient-safety metrics
bull Poor quality measures are plentiful
bull Current patient-safety indicators which use billing data
have poor sensitivity and specificity- their utility varies
with hospitalsrsquo billing practices[Case-Mix DRGs ABF]
bull INFLATIONARY to health care costs
Ashish K Jha David C Classen MDGetting Moving on Patient Safety mdash Harnessing Electronic Data for
Safer CareNEJM 36519 NEJMorg 1756 November 10 2011
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY2000-To Err Is Human Building a Safer Health System INSTITUTE OF MEDICINE
2005 -Leape LL and DM Berwick Five years after To Err Is Human what have we learned JAMA
2011- Health Information Technology Institute Of Medicine Health IT and Patient Safety Building Safer
Systems for Better Care The National Academies
Press Washington DC
2011-Jha AK and DC Classen Getting moving on patient safety--harnessing electronic data for safer
care N Engl J Med
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
Time to tackle unwarranted variations in practice
THE VARIATION PHENOMENON ldquoThe variation phenomenon in modern medicine -the observation of differences in the way apparently similar patients are treated from one health care setting to anotherrdquo
D Blumenthal Editorial NEJM 33119941017-8
Much of the variation in use of healthcare is accounted for by the willingness and ability of doctors to offer treatment rather than differences in illness or patient preference
Variation that cannot be explained on the basis of illness patient preferences or the dictates of evidence-based medicine
Identifying and reducing such variation should be a priority for providers
(John Wennberg 2011-Dartmouth Institute)
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
EffectivePreference-sensitiveSupply-sensitive Care
bull Dartmouth Atlas Project researchers have distinguished between three types of services
bull (1) ldquoEffective Carerdquo interventions that are viewed as medically necessary on the basis of clinical outcomes evidence and for which the benefits so outweigh the risks that virtually all patients with medical need should receive the them Eg NOF
bull (2) ldquoPreference-sensitive Carerdquo treatments such as discretionary surgery for which there are two or more valid treatment alternatives and the choice of treatment involves trade-offs that should be based on patientsrsquo preferences
bull (3) ldquoSupply-sensitive Carerdquo services such as physician visits referrals to
bull specialists hospitalizations and stays in intensive care units involved in the medical (non-surgical) management of disease In Medicare the large majority of these services are for patients with chronic illness
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015
Regional differences in Medicare spending are largely
explained by the more inpatient-based and specialist oriented
pattern of practice observed in high-spending regions Neither
quality of care nor access to care appear to be better for
Medicare enrolees in higher-spending regionsThe Implications of Regional Variations in Medicare Spending Part 1The Content Quality and Accessibility
of Care Elliott S Fisher MD MPH Ann Intern Med 2003138273-287
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
Does more $ per capita improve care
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
Greater spending and higher supply-sensitive care-beneficial
bull Greater spending with higher use of supply-sensitive care ie more doctors etcbull High spending vs Low Spending-69 more days in hospital pp than low spendingbull 154 MORE physician visitsbull Patients see MORE physicians in the last 612 of life
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
Reasons for practice variation
Subjective judgment uncertaintySubjective evaluation is notoriously poor across groups or over time
and enthusiasm for unproven methods
Lack of valid and poor access to clinical
knowledge -(poor evidence)
Complexity How many factors can the human mind simultaneously balance to
optimize an outcome
Human error- -- humans are inherently fallible
information processors- -- Clem MacDonald PhD
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015
Technology is NOT the problem RMRS 2012(est 1976)
Regenstrief Institute April 2012 18 hospitalsbull gt32 million physician orders entered by CPOE bull Data base of 6 million patientsbull 900 million on-line coded resultsbull 20 million reports-diagnostic studies
procedure results operative notes and discharge summaries
bull 65 million radiology imagesbull CLINICAL DECISION SUPPORT- BLINK TIMES
(CCDSS-through iterative Dbase analysis)
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015 35
CCDSS IMPROVING RESOURCE UTILISATION
OUTCOMES
-127-119
-125
-153 -152
-105
-16
-14
-12
-10
-8
-6
-4
-2
0
TOTAL
BED
TEST
DRUG
OTHER
LOS
Physician inpatient order writing on microcomputer workstations-effects on resource
utilisation WM Tierney and others JAMA 1993269379-383
$3 million per year savings ~$64bUS(1995) ( 2013-$tr)
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015
CCDSS(EHR) 1996
COSTSQUALITYOUTCOMESRESEARCH
ldquoThe plural of anecdote is not datardquo160000 patient over 4 years
Overall antibiotic use decreased 228
Mortality rates decreased from 365 to 265
Antibiotic-associated ADE decreased 30
Antibiotic resistance remained STABLE
Appropriately timed preoperative abiotics 40 to 991
Antibiotic costs per treated patient decreased $12266 to $5190
Acquisition costs for antibiotics fell 248 to 129
($987547) to ($612500)
Our Case-Mix index which measures patient acuity levels
INCREASED during this period meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics (WENNBERG 2012)Pestotnik S L Classen D C Evans R S Burke J P Implementing antibiotic practice guidelines through
computer-assisted decision support clinical and financial outcomesAnn Intern Med 1996 May 15
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
Benefits in e-Prescribing 2012
Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates Reductions in clinical errors were limited in the absence of substantial decision support but a statistically significant decline in serious errors was observed
System-related errors require close attention as they are frequent but are potentially remediable by system redesign and user training
Effects of Two Commercial Electronic Prescribing Systems on Prescribing Error Rates in Hospital In-Patients A Before and After StudyJohanna I Westbrook Margaret Reckmann Ling Li William B Runciman Rosemary Burke Connie Lo Melissa T Baysari Jeffrey Braithwaite Richard O Day
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
AIDS in Kenya-2000
25 million persons infected (15 of adults)
4th behind South Africa India and Nigeria
1 million AIDS orphans (of 31 million citizens)
Life expectancy has dropped 18 years in the past 5 years from 65 rarr 47 years
bull In 2000-pre EMR
ndash gt50 of the beds in Moi Hospital were filled with young people dying of AIDS
ndash no ARVs few antibiotics for opportunistic infections
ndash despair depression resignation
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
Clinical Information Management-the report that changed HIVAIDS in Africa
Use of OpenMRS (MMRS precursor) allowed us to manage care in a timely manner
Collecting this clinical information allowed effective measurement of the AIDS epidemic and therefore the ability to manage it in the future
HIV and TB = 0Not measured
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
SCALABILITY 2000-2012
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015
SCALABILITY 2000-2012 May 2012
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
DESIGN GOALS FOR COMPLEX E-HEALTH SYSTEMS
bull COLLABORATION bull SCALABILITY bull FLEXIBILITY bull RAPID FROM DESIGN bull USE OF STANDARDS bull SUPPORT HIGH QUALITY RESEARCH bull WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY bull LOW COST preferably freeopen source
bull CLINICALLY USEFUL feedback to providers and caregivers is critical If the system is NOT CLINICALLY USEFUL it will not be used
bull Mamlin BW Biondich PG Wolfe BA Fraser H Jazayeri D Allen C et al Cooking up an open source EMR for developing countries OpenMRS - a recipe for successful collaboration AMIA Annu Symp Proc 2006529-33 Epub 20070124N
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
ldquoThe single greatest impediment to error prevention in the medical industry is that we punish people for making mistakesrdquoDr Lucian Leape -Harvard School of Public Health-2009
Also clinicians are slow to change-the ldquoculture of medicinerdquoFive Years After To Err Is Human L Leape What Have We Learned JAMA 20052932384-
2390
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
26 March 2015 44
THE ldquoSYSTEMrsquo TO BE ldquoHEALEDrdquo
ldquoThe biggest information repository in most organisations sits within the heads of those who work there and the largest communication network is the web of conversations that binds them Together people tools and conversations ndashthat is the ldquosystemrdquordquo ENRICO COIERA [UNSWAIHI] (Int J Med Inform 69(2-3)2003205-222)
Oh no Where to from here
Oh no Where to from here
