EMR and Public Health

1. EMR and Public Health Ninad Mishra MD, MS 07/09/2009

2. Anatomy of the Presentation (1) • EHR: functions, definitions, potential • Current state: adoption, stakeholders • Future state: drivers, barriers • Public health and EHR interoperability • An immunization example • Preventive assessment & quality • Our work: • Obesity and co-morbidity detection from medical discharge summaries • Disease prevention and automatic classification of medical records

3. EMR Vs EHR EMR (Electronic Medical Record): Electronic record with full interoperability within an enterprise (hospital, clinic, practice) EHR (Electronic Health Record): Generic term applied to electronic patient care systems Original Source: an article entitled EHR vs. CPR vs. EMR in the May 2003 issue of - Healthcare Informatics

4. Health info & data Result management Order management Decision support Electronic communication Patient support Administrative reporting Population health & reporting EHR Functions IOM Report: Key Capabilities of EHR system, July 2003

5. Status of EHR Adoption • Only 4% of physicians use an extensive, fully functional system for electronic health records, and 13% use some form of basic electronic records • Those who use electronic records are generally satisfied with the systems and believe that they improve the quality of care that patients receive Source: Jha & DesRoches N ENGL J MED 359;1

6. Status of EHR Adoption Source: CDC National Ambulatory Medical Survey (NAMC) of ~2700 physicians RR 62% AHA~3037 hospitals; RR 63%

8. Effect of Adoption of EHR Systems DesRoches CM et al. N Engl J Med 2008;359:50-60

9. Barriers to Adoption of EHR Systems • COST • Financial ROI • Privacy and security of electronic health information • Clinical workflow disruption

10. Bottom Line • EHRs are not bring used the way IOM 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

11. Executive Sponsorship • “Within ten years, every American must have a personal electronic medical record….The federal government has got to take the lead..” Pres. GWB, April 26, 2004, AACC, Minneapolis • “To improve the quality of our health care while lowering its cost, we will make the immediate investments necessary to ensure that within five years, all of America’s medical records are computerized…” Pres-Elect Barack Obama, Jan 8, 2009

12. The Investment in Health IT: Recovery Act of 2009 • $19 billion over 10 years • Promote the adoption and use of health information technology and electronic health records • $17 billion of that • Financial incentives for physicians and hospitals • Early adopters (individual physicians) can collect over $44,000 over the 5 year period starting 2011

13. Other Health IT Measures $2 billion for ONC to put HIT support systems in place $300 million to support the development of health information exchange capabilities Grants to create regional technology centers to help physicians and hospitals install EHRs Funds to train a workforce Grants and loans to states to assist with adoption and interoperability

14. ONCHIT • ONCHIT stands for Office of the National Coordinator of Health Information Technology • Located within the Department of Health and Human Services • Currently exists under executive authority but the new Law expands its roles • 2 committees to advise NCHIT

15. ONCHIT NCHIT Health Information Policy Committee Health Information Standards Committee

16. ONCHIT New Coordinator: David Blumenthal, MD Dr. Farzad Motashari New Focus Meaningful use of EHRs by 2011 Primary care providers are the first target Regional health information technology extension enters as the driver for dissemination of EHR A policy-based approach Modified Source: Dr. Leslie Lenert National Center for Public Health Informatics

17. Meaningful use of Health IT • 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.”

18. Certified EMRs • The Certification Commission for Healthcare Information Technology (CCHIT®) is a private, 501(c)3 nonprofit organization • CCHIT recommendations need to be certified by National Institute of Standards and Technology (NIST)

19. Opportunity for the Public Health • It seems we would be reaching an EMR adoption tipping point • It would be a good opportunity for public health to engage with all the other stakeholders in the process • ‘Meaningful use’ • ‘Certification criteria’ • Using EMRs for population health

20. Clinical Care Patients Resources for Dx, Rx, Prev. Personnel (MD’s,RN’s, educators) Facilities (labs, OR’s, etc.) Programs (control measures, screening, education) Outcomes Public Health Cases Resources for Dx, Rx, Prev. Personnel (MD’s,RN’s, epidemiologists, educators) Facilities (labs) Programs (Rx recommendations, control measures, screening, education) Outcomes Who Has What? Modified source : Jeff Perry’s presentation

21. EHR-PH Data Exchange Potential • Registry data (immunization registry) • Reportable disease surveillance data • Case management data • Vital statistics data • Acute event detection data • Chronic disease and injury surveillance data

22. 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

23. National Objective for Registries Increase to 95% the proportion of children aged <6 years who participate in fully operational immunization registries (Healthy People 2010, objective 14.26)

24. US Participation in IIS – 2007 Group Percentage Children <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

25. 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 2005

26. Public Health Programs <1 Year Old

27. Integration Status of Specific Programs (N=31) Source: Alan R. Hinman, MD, MPH

28. EHR-PH Interoperability System Prototype Source: PHDSC

29. EHR-PH Interoperability System Prototype Source: PHDSC

30. EHR-PH Interoperability System Prototype

31. An Example from Indiana Network of Patient Care

32. PH-EHR Integration DTaP Dose Count: 30936-9 HIB Dose Count: 30938-5 IPV Dose Count: 33555-4 VZV Dose Count: 30943-5 MMR Dose Count: 30940-1 HepB Dose Count: 30937-7 Jane Doe’s Immunizations: 3/1/04 DipTetaPur 3/1/04 HemInfB 3/1/04 PolioVir 3/1/04 HepaB Patient ID: 123LMNOP Name: Jane Doe DOB: 01/01/04 SSN: N/A Address: 555 Johnson Road City: Indianapolis State: Indiana ZIP: 46202 30936-9 30938-5 33555-4 30937-7 Global Patient Index Immunization Registry Global ID: 45678 Name: Jane Ellen Doe Lots of Demographics.. MRF1 ID: OU81247 MRF2 ID: 4564356 PH MRF ID: 123LMNOP MRF3 ID: 6789XYZ Patient ID: 6789XYZ Name: Jane Ellen Doe DOB: 01/01/04 SSN:123-45-6789 Address: 555 Johnson Road City: Indianapolis State: Indiana ZIP: 46202 Jane Ellen Doe’s Shots: 5/1/04 DTaP Imm 5/1/04 HIB Imm 5/1/04 IPV Imm 7/9/04 DTaP Imm 7/9/04 IPV Imm 30936-9 30938-5 33555-4 30936-9 33555-4 Concept Dictionary Electronic Medical Record System

33. Population Health, Preventive Assessment and Informatics

34. Population Health • “The health outcomes of a group of individuals, including the distribution of such outcomes within the group.”1 • Is at the cross section of medicine and public health 1Kindig D, Stoddart G. What is population health?American Journal of Public Health 2003 Mar;93(3):380-3. Retrieved 2008-10-12.

35. Population Health • Disease management • Preventive health • Cancer screenings • Childhood immunization gap • Quality improvement • Aggregate population data exchange/ statistical reporting • Data mining and predictive modeling

36. Population Health

37. Data Sources • Patient management systems • EHRs • RHIOs • Labs • Registries • Pharmacies

38. What 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)

39. Example: Diabetes Measurement Set (foot exam) Measure:Percentage of patients who received at least one complete foot exam (visual inspection, sensory exam with monofilament, and pulse exam) • Numerator = patients who received at least one complete foot exam (visual inspection, sensory exam with monofilament, and pulse exam) • Denominator = All patients with diabetes 18-75 years of age Source: Alliance of Chicago: Community Health Services

40. Technical SpecificationsDenominator • All patients with diabetes 18-75 years of age • Codes to identify patients with diabetes include: • ICD-9-CM codes: 250, 357.2, 362.0, 366.41, 648.0) (DRGs) 294, 205 • Prescriptions to identify patients with diabetes include: • Insulin prescriptions (drug list is available) and oral hypoglycemic/ antihyperglycemics prescriptions (drug list is available)

41. Data Analysis Best Practices(Example: Diabetes patients with A1c >7) Source: Wisconsin Research Education Network

42. Benefits • Providers (physicians): patient alerts, decision support, work flow assistance, evidence based practice • Management: case management, cost control, quality control, outreach • Patients: quality of care • Public health: reduce disparities, increase quality, better research data

43. Our Two Cents • We are working at small POCs to establish methods for data capture and algorithm development • We have been primarily focused on unstructured data analysis but combination of structured with unstructured is the goal • Two examples: • I2b2 obesity challenge • Family health history analysis

44. I2b2 Obesity Challenge • NIH-funded National Center for biomedical computing based at Partners HealthCare System • i2b2 issues ‘challenges’ to correctly classify health records based on conditions and co-morbidities and invites various institutions/teams to compete

45. Results

46. JAMIA: Jul-Aug 2009

47. Next: Family Health History & Screening • Previous work (i2b2): detect occurrences of specific morbidities in medical discharge summaries • Future directions: • Extract other information • Experiencer (sic): Who is experiencing the condition (patient or other family member)? • Temporality • Other co-information: lab results, screening test results, medications, etc. • Apply rules to extracted information to make recommendations

48. 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.” Better preventive care assessment and public health functions 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