1. SWEA1 CSE 5810 HIEx TM : Health Link Information Exchange  Review the elements of, and differences between health information technology and health information exchange  Relate the importance of HIE to primary care physicians for both practice management and clinical information  Develop an understanding of the functionalities in the HIExTM system, and how this provides a flexible infrastructure for a cross-disciplinary Regional Health Information Organization (RHIO)  Excerpted from From Presentation by: David R. Little, Katherine L. Cauley, and Mary M. Crimmins – Wright State Univ. Medical School  See: http://pciwg.amia.org/pmwiki/PapersAndPresentations/HomePage

2. SWEA2 CSE 5810 Objectives of Effort  Personal health information  Continuity of care  Coordination of care  Family and community information  Public Health, Epidemiology

3. SWEA3 CSE 5810 Overall Architecture and Technologies  Scalable multi-tier application architecture  Microsoft SQL database  Supports source and time stamps and log tables to assure audit functions.  Fully customizable role based access for each data element.

4. SWEA4 CSE 5810 Current components of HIEx™  Demographic and individual health status information  Contacts module for emergency contacts, caseworkers, PC physicians, guarantors, etc.  Electronic Medicaid and PRC applications  Referrals module with workflow history  Scanned documents  Reporting on individual productivity  Full audit trail for all transactions

5. SWEA5 CSE 5810 © Wright State University, Boonshoft School of Medicine Welcome Screen for HIEx

6. SWEA6 CSE 5810 © Wright State University, Boonshoft School of Medicine Tracking Patients

7. SWEA7 CSE 5810 © Wright State University, Boonshoft School of Medicine Tracking Household

8. SWEA8 CSE 5810 © Wright State University, Boonshoft School of Medicine Detailed Data on Household Members

9. SWEA9 CSE 5810 © Wright State University, Boonshoft School of Medicine More Details on Household

10. SWEA10 CSE 5810 © Wright State University, Boonshoft School of Medicine

11. SWEA11 CSE 5810 Referrals module Provides Tracking  Service utilization patterns are recorded  Source of referrals  For example one uninsured family presents at two hospitals  The first referral for Medicaid would be recorded from hospital A and the second from hospital B.  Community Health Advocates track the progress of each referral.  The system displays the history of the progress.

12. SWEA12 CSE 5810 © Wright State University, Boonshoft School of Medicine Tracking Referrals for a Patient

13. SWEA13 CSE 5810 Scanned documents module adds flexibility  Designed to capture documentation from paper  Examples include:  Immunization records  Birth certificates  Driver’s license or other identity documents

14. SWEA14 CSE 5810 © Wright State University, Boonshoft School of Medicine Tracking Scanned Documents

15. SWEA15 CSE 5810 Massachusetts eHealth Collaborative  Presentation by David W. Bates, MD, MSc, 2005  Presentation by David W. Bates, MD, MSc, 2005 http://pciwg.amia.org/presentations/MaEHCShortAMIA_files/frame.html http://pciwg.amia.org/presentations/MaEHCShortAMIA_files/frame.html  Three-Fold Objective:  Tools for Health care  Incorporation into Clinical Practice  Sustained Usage over Time  Pilot in Different Communities  Collect Experiences  Look at Larger Scale Roll out

16. SWEA16 CSE 5810 eHealth Collaborative Vision

17. SWEA17 CSE 5810 Three Areas of Activity for Pilots

18. SWEA18 CSE 5810 EHRs and Selection Process

19. SWEA19 CSE 5810 Physician EHR Selections

20. SWEA20 CSE 5810 Patient Interactions – Opting In Process Patient Interactions – Opting In Process

21. SWEA21 CSE 5810 Patient Interactions – Opting In Process Patient Interactions – Opting In Process

22. SWEA22 CSE 5810 Patient Interactions – Opting Out Process Patient Interactions – Opting Out Process

23. SWEA23 CSE 5810 Comments Options

24. SWEA24 CSE 5810 Thomas Agresta MD Associate Professor and Director of Medical Informatics Department of Family Medicine University of Connecticut School of Medicine July 12, 2007 © content developed by Society of Teachers of Family Medicine Physicians’ Track Knowledge Management and Clinical Decision Support

25. SWEA25 CSE 5810 Current Definition of CDS  Providing clinicians, patients or individuals with knowledge and person-specific or population information, intelligently filtered or presented at appropriate times to foster better health processes, better individual patient care, and better population health.  From: A Roadmap for National Action on Clinical Decision Support © content developed by Society of Teachers of Family Medicine Physicians’ Track

26. SWEA26 CSE 5810 Computerized Clinical Decision Support?  Need machine interpretable data (Standards Help)  Lab values in standardized formats - K+ (LOINC)  Patients with specific conditions – Afib (ICDM 9, SnoMed CT)  Need to monitor for condition (Event Monitor)  Order for a medication – Digoxin (RxNorm)  Event Monitor watches the EMR for a specific event that “triggers” specific program  Can be internal to forms, or “watching” as a separate program  Need “Rules” to guide response © content developed by Society of Teachers of Family Medicine Physicians’ Track

27. SWEA27 CSE 5810 Example of Architecture © content developed by Society of Teachers of Family Medicine Physicians’ Track

28. SWEA28 CSE 5810 History of CDS  1970’s – Artificial Intelligence  AAP Help – Leeds University – diagnosis abdominal pain – Bayesian Model  Internist 1 – Pittsburgh – Decision Tree diagnosis aid for complex cases. Relied on Master clinicians  MYCIN – Rules based antimicrobial diagnosis and treatment aid. (If then rules) © content developed by Society of Teachers of Family Medicine Physicians’ Track

29. SWEA29 CSE 5810 History of CDS Cont..  1980’s – Some Commercialization  DxPlain - Uses clinical findings and produces a ranked list of possible clinical diagnosis.  Knowledge base includes 5,000 symptoms and 2,200 diseases.  Still available today - Web based  QMR – Quick Medical Reference  Diagnostic Support System – expert consultant  Turns out Physicians didn’t want / like / need help with diagnosis most of the time © content developed by Society of Teachers of Family Medicine Physicians’ Track

30. SWEA30 CSE 5810 Potential Benefits of CDS  Prevent Errors  Commission – (drug/allergy interaction)  Omission – (rapidly respond to critical labs)  Optimize Decision Making  Optimize choices available (drug formulary)  Improve compliance with guideline  Improve compliance complex protocols (Cancer)  Optimize treatment chronic conditions over time (HbA1c - diabetes, steroids - asthma) © content developed by Society of Teachers of Family Medicine Physicians’ Track

31. SWEA31 CSE 5810 Potential Benefits of CDS  Improve Care Processes  Documentation of care (allergies, smoking status, faster more complete diabetes documentation)  Patient education and empowerment (communication, patient understanding and self management)  Communication among providers (shared, timely data available to consultant / covering physician) © content developed by Society of Teachers of Family Medicine Physicians’ Track

32. SWEA32 CSE 5810 Rationale For The Use of CDS  Mixed overall results – improving with time  CDS effective with other interventions  Diabetes - care processes & outcomes (Shojania)  Review 100 studies showed 64% improved clinical outcomes (Garg)  Improved Screening & Immunizations – ~80% studies  Most improved prescribing  Some decreased hospital length of stay and cost  HIT effects on Quality most with adherence guideline care, surveillance and monitoring and decreased medication errors. (Chaudry) © content developed by Society of Teachers of Family Medicine Physicians’ Track

33. SWEA33 CSE 5810 Diabetes Care – Intelligent Forms John Janas M.D. Forms from Clinical Content Consultants © content developed by Society of Teachers of Family Medicine Physicians’ Track

34. SWEA34 CSE 5810 Alerts and Reminders  Point of Care  Drug / drug interactions  Drug / allergy alerts  Prompt for disease specific medications  Preventive services due © content developed by Society of Teachers of Family Medicine Physicians’ Track

35. SWEA35 CSE 5810References  Bates DW et al. Ten Commandments for Effective Clinical Decision Support: Making the Practice of Evidence Based Medicine a Reality. J Am Med Inform Assoc. 10:523-530, 2003.  Chaudry B, et al. Systematic review: Impact of Heath Information Technology on Quality, Efficiency and Cost of Medical Care. Ann of Int Med. 144(10): 742-752, 2006  Classen DC. Clinical Decision Support Systems to Improve Clinical Practice and Quality of Care. JAMA. 280(15)1360-1361, 1998.  Garg AX et al. Effects of Computerized Clinical Decision Support Systems on Physician Performance and Patient Outcomes. JAMA 293(10)1223-1238, 2005.  Hunt DL et al. Effects of Computer-Based Clinical Decision Support Systems on Physician Performance and Patient Outcomes. JAMA 290(15)1339-1346, 1998.  Hunt DL et al. Patient-specific evidence-based care recommendations for diabetes mellitus: development and initial clinic experience with a computerized decision support system. Int J Med Inform. 51(2-3):127-135, 1998.  Judge J et al. Prescribers' responses to alerts during medication ordering in the long term care setting. J Am Med Inform Assoc. 13(4):385-90, 2006.  Nagykaldi Z, Mold J. J Am Board of Family Medicine 2007; 20: 188-195  Mcglynn E, Asch S, et al. The Quality of Health Care Delivered to Adults in the United States. NEJM. 348(26):2635-45. 2003.  Miller RA et al. Clinical Decision Support and Electronic Prescribing Systems: A Time for Responsible Thought and Action. J Am Med Inform Assoc. 12:403-409, 2005.  Osheroff J, et al. A Roadmap for National Action on Clinical Decision Support Accessed at http://www.amia.org/inside/initiatives/cds/ on November 26,2006http://www.amia.org/inside/initiatives/cds/  Osheroff J, et al. Improving Outcomes with Clinical Decision Support: An Implementer’s Guide. Healthcare Information Management Systems Society. Chicago 2005  Sequist TD et al. A Randomized Trial of Electronic Clinical Reminders to Improve Quality of Care for Diabetes and Coronary Artery Disease. J Am Med Inform Assoc. 12:431-437, 2005. © content developed by Society of Teachers of Family Medicine Physicians’ Track