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