MedBiquitous’ Emerging Virtual Patient Architecture

1. MedBiquitous’ Emerging Virtual Patient Architecture Valerie SmothersDeputy DirectorMedBiquitous Prepared for the Johns Hopkins Division of Health Sciences Informatics February 16, 2007

2. Disclosure • I have no relevant financial relationships to disclose.

3. Learning Objectives By the end of this session, you will be able to: • Articulate the need for virtual patients • Compare existing approaches to virtual patients • Describe components of the MedBiquitous Virtual Patient Architecture

4. Quandry • How do you teach clinical reasoning and protect patient safety? • Let the student watch attendings and residents and listen to lectures • Have an attending closely monitor student interaction with a patient and provide feedback • Do small group exercises that explore certain cases or types of cases and how to handle them • Use tools that simulate the clinical environment

5. Simulating the Clinical Environment • Can be expensive and time consuming to develop these tools • Often home grown and disconnected from other learning systems Need a way to share resources and integrate with external resources and systems

6. MedBiquitous Mission To advance healthcare education through technology standards that promote professional competence, collaboration, and better patient care. Non-profit, member-driven, standards development organization

7. Fast Facts Professional Profile LearningObjects • 60 member organizations • 7 working groups • ANSI process • Openness • Transparency • Consensus • Due Process • Work with leading organizations that can drive adoption (AAMC, ABMS, ACCME, NBME, FSMB, AMA, AAFP, VA) ActivityReport Metrics Virtual Patient Competency Point of Care Learning

8. Building the Foundation POCLearning E-portfolio Activity Report Virtual Patients Metrics SCORMfor Healthcare ProfessionalProfile HealthcareLOM Competency

9. MedBiquitous Goals • Better tracking and evaluation of professional education and certification activities • Easier discovery of relevant education and information resources when and where needed • Interoperability and sharing of high quality online education • Coordination and tracking of competence assessment data

10. Virtual Patients • Interactive computer programs that simulate real life clinical scenarios Some examples: • Sarah Jane, St. George’s University of London (narrative, node based)http://labyrinth.mvm.ed.ac.uk • Web SP, Karolinska Institute (linear w/data) http://websp.lime.ki.se

16. Virtual Patients • Component based approach • Enables sharing and reuse of entire virtual patient or components • Engaging and relevant • Provides feedback on practice • Hewlett funded grant for VP player (Tufts) • U of Edinburgh, Pittsburgh, NYU, Tufts, Karolinska Institute implementing

17. Susan Albright, Tufts University Chris Candler, M.D., Association of American Medical Colleges David Davies, Ph.D., IVIMEDS Parvati Dev, Stanford University Shona Dippie, HEAL Rachel Ellaway, Ph.D., University of Edinburgh Uno Fors, D.D.S., Ph.D., Karolinska Institute Robert Galbraith, M.D., National Board of Medical Examiners Michael Hagen, M.D., American Board of Family Medicine Grace Huang, M.D., Harvard University Carol Kamin, University of Colorado Joy Leffler, WE MOVE Ross Martin, M.D., Pfizer J.B. McGee, M.D., University of Pittsburgh Sandra McIntyre, M.Ed., HEAL Yanko Michea, M.D., University of Connecticut Dick Moberg, Moberg Research Kitty O'Meara, Oregon Health and Science University Beth Powell, Centers for Disease Control Dan Rehak, Ph.D., Carnegie Mellon University Kathie Rose, National Board of Medical Examiners Kevin Souza, University of California, San Francisco Hemal Thakore, M.D., University College, Dublin Greg Thompson, M.D., Medantic Marc Triola, M.D., New York University Nabil Zary, Karolinska Institute MedBiquitous Virtual Patient Working Group

18. The MVP Architecture Virtual Patient Data Media Resource Data Availability Model ActivityModel Global State Model

19. Virtual Patient Data • Personal and clinical data • Similar to a clinical chart • May include references to healthcare terminologies • Draft schema available

20. Media Resource • Images, animations, videos, etc. • Leverages IMS Content Packaging to catalogue, uniquely identify, and package resources with other components. Content Package chest_anatomy.jpg id=xyz123respiration.mov id=xyz234circulation.fla id=xyz345Virtual Patient Data id=xyz5 Activity Model id=xyz456

21. Data Availability Model DAM • Aggregates virtual patient data and media resources for reference in an activity • Enables progressive disclosure of virtual patient data and media resources Part 1: Patient History Part 2:Diagnostics Virtual Patient data MediaResources Text Interview item Diagnostic test

22. ActivityModel • Integrates VPD, MR, and DAM into a cohesive learning activity • Many models are possible • Linear • Branching • Free flow

23. Global State Model • Top level modeling of student activity • Virtual ward • Multiplayer game

24. What’s the benefit? • Facilitate the exchange and reuse of virtual patients across institutions • Promote a more engaging (and safe) way to learn and assess • Expose students to conditions they may not see in the hospital

27. What do you see as opportunities for leveraging virtual patients?

28. Working Group Participation • Teleconferences every 6 weeks • Groupware to facilitate collaboration • Contact me for more informationvalerie.smothers@medbiq.org