EMR and Public EMR and Public HealthHealth
Ninad Mishra MD, MSNinad Mishra MD, MS
07/09/200907/09/2009
Anatomy of the Presentation (1)
EHR: functions, definitions, potentialEHR: functions, definitions, potential Current state: adoption, stakeholdersCurrent state: adoption, stakeholders Future state: drivers, barriersFuture state: drivers, barriers Public health and EHR interoperabilityPublic health and EHR interoperability
An immunization example Preventive assessment & quality
Our work:Our work: Obesity and co-morbidity detection from
medical discharge summaries Disease prevention and automatic
classification of medical records
EMR Vs EHR
EMR (Electronic Medical Record): Electronic EMR (Electronic Medical Record): Electronic record with full interoperability within an record with full interoperability within an
enterprise (hospital, clinic, practice)enterprise (hospital, clinic, practice)
EHR (Electronic Health Record): Generic EHR (Electronic Health Record): Generic term applied to electronic patient care term applied to electronic patient care
systemssystems
Original Source: an article entitled EHR vs. CPR vs. EMR in the May 2003 issue of - Healthcare Informatics
EHR Functions
Health info & Health info & datadata
Result Result managementmanagement
Order Order managementmanagement
Decision Decision supportsupport
Electronic Electronic communicationcommunication
Patient supportPatient support Administrative Administrative
reportingreporting Population Population
health & health & reportingreporting
IOM Report: Key Capabilities of EHR system, July 2003
Only 4% of physicians use an Only 4% of physicians use an extensive, fully functional extensive, fully functional system for electronic health system for electronic health records, and 13% use some records, and 13% use some form of basic electronic recordsform of basic electronic records
Those who use electronic Those who use electronic records are generally satisfied records are generally satisfied with the systems and believe with the systems and believe that they improve the quality that they improve the quality of care that patients receiveof care that patients receive
Source: Jha & DesRoches N ENGL J MED 359;1
Status of EHR Adoption
Status of EHR Adoption
SettingSetting 20062006
(%)(%)20072007
(%)(%)20082008
(%)(%)20092009
(%)(%)PO (basic)PO (basic) 1111 1313 1717
PO ( full)PO ( full) 33 44 44
Hospitals Hospitals (basic)(basic)
NANA NANA 88
Hospitals Hospitals (full)(full)
NANA NANA 22
Source: CDC National Ambulatory Medical Survey (NAMC) of ~2700 physicians RR 62% AHA~3037 hospitals; RR 63%
EHR components Basic Full
Health Info & Data * *
Order EntryMedication Orders * *Lab Orders *Radiology orders *Rx sent electronically *Orders sent electronically
*
Results ManagementView lab results * *View imaging results * *Images returned *
Clinical Decision support
*
Public Health
Effect of Adoption of EHR Systems
DesRoches CM et al. N Engl J Med 2008;359:50-60
Barriers to Adoption of EHR Barriers to Adoption of EHR SystemsSystems
COST Financial ROI Privacy and security of
electronic health information Clinical workflow disruption
Bottom Line
EHRs are not bring used the way EHRs are not bring used the way IOM had hopedIOM had hoped Physician’s report limited availability
of key functions (order entry, clinical decision support)
Physician’s report limited use of most of the functions
Many institutions with an EHR cannot produce patients list (registry function)
Public health/population health related measures are lacking
Executive SponsorshipExecutive Sponsorship
““Within ten years, every American must Within ten years, every American must have a personal electronic medical have a personal electronic medical record….The federal government has got record….The federal government has got to take the lead..” to take the lead..” Pres. GWB, April 26, 2004, Pres. GWB, April 26, 2004, AACC, MinneapolisAACC, Minneapolis
““To improve the quality of our health care To improve the quality of our health care while lowering its cost, we will make the while lowering its cost, we will make the immediate investments necessary to immediate investments necessary to ensure that within five years, all of ensure that within five years, all of America’s medical records are America’s medical records are computerized…” computerized…” Pres-Elect Barack Obama, Jan Pres-Elect Barack Obama, Jan 8, 20098, 2009
The The Investment in in Health IT: Recovery Act of 2009IT: Recovery Act of 2009
$$19 billion over 10 years 19 billion over 10 years Promote the adoption and use of Promote the adoption and use of
health information technology and health information technology and electronic health recordselectronic health records
$17 billion of that$17 billion of that Financial incentives for physicians Financial incentives for physicians
and hospitalsand hospitals Early adopters (individual Early adopters (individual
physicians) can collect over $44,000 physicians) can collect over $44,000 over the 5 year period starting 2011over the 5 year period starting 2011
Other Health IT Measures $2 billion for ONC to put HIT support $2 billion for ONC to put HIT support
systems in placesystems in place $300 million to support the $300 million to support the
development of health information development of health information exchange capabilitiesexchange capabilities
Grants to create regional technology Grants to create regional technology centers to help physicians and centers to help physicians and hospitals install EHRshospitals install EHRs
Funds to train a workforce Funds to train a workforce Grants and loans to states to assist Grants and loans to states to assist
with adoption and interoperabilitywith adoption and interoperability
ONCHITONCHIT
ONCHIT stands for Office of the ONCHIT stands for Office of the National Coordinator of Health National Coordinator of Health Information TechnologyInformation Technology
Located within the Department of Located within the Department of Health and Human ServicesHealth and Human Services
Currently exists under executive Currently exists under executive authority but the new Law authority but the new Law expands its rolesexpands its roles
2 committees to advise NCHIT2 committees to advise NCHIT
ONCHITONCHIT
Health Information
Policy Committee
Health Information Standards Committee
NCHIT
ONCHIT
New Coordinator: David Blumenthal, New Coordinator: David Blumenthal, MDMD
Dr. Farzad MotashariDr. Farzad Motashari New FocusNew Focus
Meaningful useMeaningful use of EHRs by 2011 of EHRs by 2011 Primary care providers are the first Primary care providers are the first
targettarget Regional health information technology Regional health information technology
extension enters as the driver for extension enters as the driver for dissemination of EHRdissemination of EHR
A policy-based approachA policy-based approachModified Source: Dr. Leslie LenertNational Center for Public Health Informatics
Meaningful use of Health IT
Key desired policy outcomes: Key desired policy outcomes: efficiency, patient safety, care coordination
Drivers: Medicare and Medicaid incentive payments
Being formulated: “measurement of key public health conditions, measuring health care efficiency, and measuring the avoidance of certain adverse events.”
Certified EMRsCertified EMRs
The Certification Commission for The Certification Commission for Healthcare Information Healthcare Information Technology (CCHIT®) is a Technology (CCHIT®) is a private, 501(c)3 nonprofit private, 501(c)3 nonprofit organization organization
CCHIT recommendations need to CCHIT recommendations need to be certified by National Institute be certified by National Institute of Standards and Technology of Standards and Technology (NIST)(NIST)
Opportunity for the Public Opportunity for the Public HealthHealth
It seems we would be reaching It seems we would be reaching an EMR adoption tipping pointan EMR adoption tipping point
It would be a good opportunity It would be a good opportunity for public health to engage with for public health to engage with all the other stakeholders in the all the other stakeholders in the processprocess ‘‘Meaningful use’Meaningful use’ ‘‘Certification criteria’Certification criteria’ Using EMRs for population healthUsing EMRs for population health
Who Has What?Clinical CareClinical Care
PatientsPatients
Resources for Dx, Rx, Prev.Resources for Dx, Rx, Prev.
Personnel (MD’s,RN’s, Personnel (MD’s,RN’s, educators) educators)
Facilities (labs, OR’s, Facilities (labs, OR’s, etc.)etc.)
Programs (control Programs (control measures, screening, measures, screening, education)education)
OutcomesOutcomes
Public Health Public Health Cases Cases
Resources for Dx, Rx, Resources for Dx, Rx, Prev.Prev.
Personnel (MD’s,RN’s, Personnel (MD’s,RN’s, epidemiologists, epidemiologists, educators)educators)
Facilities (labs)Facilities (labs)
Programs (Rx Programs (Rx recommendations, recommendations, control measures, control measures, screening, education)screening, education)
OutcomesOutcomes
Modified source : Jeff Perry’s presentation
EHR-PH Data Exchange Potential
Registry data (immunization registry)Registry data (immunization registry) Reportable disease surveillance dataReportable disease surveillance data Case management dataCase management data Vital statistics dataVital statistics data Acute event detection dataAcute event detection data Chronic disease and injury surveillance Chronic disease and injury surveillance
data data
Considerations for EHR-Based Population Health Applications
Data has to be defined and captured in uniform ways
Data capture has to be simple and integrated into the workflow
System must be modifiable as measures and recommendations change over time
Population level analysis, and algorithms for measures require more complex analysis or queries
Source: Alliance of Chicago: Community Health Services
National Objective for Registries
Increase to 95% the proportion Increase to 95% the proportion of children aged <6 years who of children aged <6 years who participate in fully operational participate in fully operational immunization registriesimmunization registries
((Healthy People 2010Healthy People 2010, objective , objective 14.26)14.26)
US Participation in IIS – 2007
Group PercentageChildren <6 (2+ doses) 71%Children 11-18 (2+ doses) 64% Adults >19 (1+ dose)20% Public provider sites 73% Private provider sites 48%
Source: Alan Hinman, Public Health Informatics Institute
Barriers to IIS
Cost and/or time of data entry and retrieval
Practices are too busy to consider a new procedure and implement change
Concerns about privacy, confidentiality, and HIPAA
Provider does not see any value to their practice of the new information they can get from the registry.
Coordination required between clinical, administrative and information systems departments
Source: AIRA/CDC report “Turning barriers into opportunities” Dec 2005Source: AIRA/CDC report “Turning barriers into opportunities” Dec 2005
Public Health Programs <1 Public Health Programs <1 Year OldYear Old
Integration Status of Specific Programs (N=31)
7%
7%
13%
13%
23%
32%
39%
39%
42%
13%
10%
10%
19%
10%
16%
13%
13%
16%
10%
26%
26%
26%
29%
36%
26%
26%
32%
0 0.5 1
EPSDTEIP
LeadWIC
Birth DefectsNewborn …
Vital …Immunizati…
EHDI
Already integrated Next Year Next Three Years
Source: Alan R. Hinman, MD, MPH
Source: PHDSC
EHR-PH Interoperability System Prototype
EHR-PH Interoperability System Prototype
Source: PHDSC
EHR-PH Interoperability System Prototype
An Example from An Example from Indiana Network of Indiana Network of
Patient CarePatient Care
PH-EHR IntegrationPH-EHR Integration
ImmunizatioImmunization Registryn Registry
Electronic Electronic Medical Record Medical Record
SystemSystem
Patient ID: 123LMNOPPatient ID: 123LMNOPName: Jane Doe Name: Jane Doe DOB: 01/01/04DOB: 01/01/04SSN: N/A SSN: N/A Address: 555 Johnson RoadAddress: 555 Johnson RoadCity: IndianapolisCity: IndianapolisState: IndianaState: IndianaZIP: 46202ZIP: 46202
Patient ID: 6789XYZPatient ID: 6789XYZName: Jane Ellen DoeName: Jane Ellen DoeDOB: 01/01/04DOB: 01/01/04SSN:123-45-6789SSN:123-45-6789Address: 555 Johnson Address: 555 Johnson RoadRoadCity: IndianapolisCity: IndianapolisState: IndianaState: IndianaZIP: 46202ZIP: 46202
Global Global Patient Patient IndexIndex
Concept Concept DictionaryDictionary
Global ID:Global ID: 4567845678Name: Name: Jane Ellen Doe Jane Ellen Doe Lots of Demographics..Lots of Demographics..MRF1 ID: MRF1 ID: OU81247OU81247MRF2 ID: MRF2 ID: 45643564564356PH MRF ID: PH MRF ID: 123LMNOP123LMNOPMRF3 ID:MRF3 ID: 6789XYZ6789XYZ
DTaP Dose Count:DTaP Dose Count: 30936-930936-9HIB Dose Count:HIB Dose Count: 30938-530938-5IPV Dose Count:IPV Dose Count: 33555-433555-4VZV Dose Count:VZV Dose Count: 30943-530943-5MMR Dose Count:MMR Dose Count: 30940-130940-1HepB Dose Count:HepB Dose Count: 30937-730937-7
Jane Doe’s Immunizations:Jane Doe’s Immunizations:
3/1/043/1/04 DipTetaPurDipTetaPur3/1/043/1/04 HemInfBHemInfB3/1/043/1/04 PolioVirPolioVir3/1/043/1/04 HepaBHepaB
Jane Ellen Doe’s Shots:Jane Ellen Doe’s Shots:
5/1/045/1/04 DTaP ImmDTaP Imm5/1/045/1/04 HIB ImmHIB Imm5/1/045/1/04 IPV ImmIPV Imm7/9/047/9/04 DTaP ImmDTaP Imm7/9/047/9/04 IPV ImmIPV Imm
30936-30936-9 9 30938-30938-5 5 33555-33555-4 4 30937-30937-77
30936-30936-9 9 30938-30938-5 5 33555-33555-4 4 30936-30936-9 9 33555-33555-44
Population Health, Population Health, Preventive Assessment Preventive Assessment
and Informaticsand Informatics
Population Health
““The health outcomes of a group The health outcomes of a group of individuals, including the of individuals, including the distribution of such outcomes distribution of such outcomes within the group.”within the group.”11
Is at the cross section of Is at the cross section of medicine and public healthmedicine and public health
11 Kindig D, Stoddart G. What is population health? American Journal of Public
Health 2003 Mar;93(3):380-3. Retrieved 2008-10-12.
Population Health
Disease managementDisease management Preventive healthPreventive health
Cancer screeningsCancer screenings Childhood immunization gapChildhood immunization gap
Quality improvementQuality improvement Aggregate population data Aggregate population data
exchange/ statistical reportingexchange/ statistical reporting Data mining and predictive Data mining and predictive
modelingmodeling
Population HealthPopulation Health
Data SourcesData Sources
Patient management systemsPatient management systems EHRsEHRs RHIOsRHIOs LabsLabs Registries Registries PharmaciesPharmacies
What is neededWhat is needed Develop algorithms to appropriately
identify cases Billing data is usually not enough –
consider addition of free text data, medication data, medical summary abstraction etc.
Develop statistical measures for aggregated summary and analysis for public health use
Modified Source: Arndt et al (WREN)
Example: Diabetes Example: Diabetes Measurement Set (foot Measurement Set (foot
exam)exam)Measure:Measure: Percentage of patients who Percentage of patients who
received at least one complete foot received at least one complete foot exam (visual inspection, sensory exam exam (visual inspection, sensory exam with monofilament, and pulse exam)with monofilament, and pulse exam)
NumeratorNumerator = patients who received at = patients who received at least one complete foot exam (visual least one complete foot exam (visual inspection, sensory exam with inspection, sensory exam with monofilament, and pulse exam)monofilament, and pulse exam)
DenominatorDenominator = All patients with = All patients with diabetes 18-75 years of agediabetes 18-75 years of age
Source: Alliance of Chicago: Community Health Services
Technical SpecificationsDenominator
All patients with diabetes 18-75 years of ageAll patients with diabetes 18-75 years of age Codes to identify patients with diabetes Codes to identify patients with diabetes
include: include: ICD-9-CM codes: 250, 357.2, 362.0, ICD-9-CM codes: 250, 357.2, 362.0,
366.41, 648.0) (DRGs) 294, 205 366.41, 648.0) (DRGs) 294, 205 Prescriptions to identify patients with Prescriptions to identify patients with
diabetes include: diabetes include: Insulin prescriptions (drug list is Insulin prescriptions (drug list is
available) and oral hypoglycemic/ available) and oral hypoglycemic/ antihyperglycemics prescriptions (drug antihyperglycemics prescriptions (drug list is available) list is available)
Data Analysis Best Practices(Example: Diabetes patients with
A1c >7)Analysis TypeAnalysis Type ExampleExample UtilityUtility
1 – Case series1 – Case series 60% in clinic have A1c >760% in clinic have A1c >7 Lowest
2 – Simple 2 – Simple comparisoncomparison
Clinic rate of 60% is higher Clinic rate of 60% is higher than statewide rate of 50%than statewide rate of 50%
Low
3 – Comparison + 3 – Comparison + TestTest
Medium
4 – Adjusted 4 – Adjusted comparison + Test comparison + Test (ie, adjust for principal (ie, adjust for principal determinant)determinant)
Age adjusted clinic rate of Age adjusted clinic rate of 60% is significantly higher60% is significantly higher
Higher
5 – Multivariate model 5 – Multivariate model + Test (ie, adjust for + Test (ie, adjust for all important risk all important risk factors / factors / determinants)determinants)
Clinic rate of 60% adjusted Clinic rate of 60% adjusted for age, gender, race, and for age, gender, race, and insurance status is insurance status is significantly highersignificantly higher
Highest
Source: Wisconsin Research Education Network
BenefitsBenefits
Providers (physicians): patient alerts, Providers (physicians): patient alerts, decision support, work flow decision support, work flow assistance, evidence based practiceassistance, evidence based practice
Management: case management, cost Management: case management, cost control, quality control, outreachcontrol, quality control, outreach
Patients: quality of care Patients: quality of care Public health: reduce disparities, Public health: reduce disparities,
increase quality, better research dataincrease quality, better research data
Our Two CentsOur Two Cents
We are working at small POCs to We are working at small POCs to establish methods for data capture establish methods for data capture and algorithm developmentand algorithm development
We have been primarily focused on We have been primarily focused on unstructured data analysis but unstructured data analysis but combination of structured with combination of structured with unstructured is the goalunstructured is the goal
Two examples:Two examples: I2b2 obesity challengeI2b2 obesity challenge Family health history analysisFamily health history analysis
I2b2 Obesity Challenge
NIH-funded National Center for NIH-funded National Center for biomedical computing based at biomedical computing based at Partners HealthCare System Partners HealthCare System
i2b2 issues ‘challenges’ to i2b2 issues ‘challenges’ to correctly classify health records correctly classify health records based on conditions and co-based on conditions and co-morbidities and invites various morbidities and invites various institutions/teams to competeinstitutions/teams to compete
ResultsResults
JAMIA: Jul-Aug 2009JAMIA: Jul-Aug 2009
Next: Family Health History & Screening
Previous work (i2b2): detect Previous work (i2b2): detect occurrences of specific morbidities in occurrences of specific morbidities in medical discharge summariesmedical discharge summaries
Future directions:Future directions: Extract other informationExtract other information
Experiencer (sic): Who is experiencing the condition Experiencer (sic): Who is experiencing the condition (patient or other family member)?(patient or other family member)?
TemporalityTemporality Other co-information: lab results, screening test Other co-information: lab results, screening test
results, medications, etc.results, medications, etc. Apply rules to extracted information to make Apply rules to extracted information to make
recommendationsrecommendations
Bending the Curve :Achieving Meaningful Use of
Health Data“Phased-in series of improved clinical data capture supporting more rigorous and robust quality measurement and improvement.”
Modified after: Connecting for Health, Markle Foundation “Achieving the Health IT Objectives of the American Recovery and Reinvestment Act” April 2009
Meaningful Use Workgroup Presentation : Paul Tang & Farzad Mostashari
Better preventive care assessment and public health
functions