McMaster Ehealth Program & Research Collaboration

1. McMaster Ehealth Program & Research Collaboration Joseph Tan, PhD Michael Dohan, MSc

2. Agenda • =========== Introduction • MScEhealth at McMaster • Complexity in a Healthcare System • Healthcare in Ontario, Canada • A Model for Health IT: CAHCS • =========== Question Period I • What is Ehealth? • Considerations for Implementation • Ehealth Applications • Current Research Topics • =========== Conclusion/Question Period II

3. MScEhealth at McMaster “Our students come from a wide variety of background in these fields, with common interests in information technology to support health services delivery and research.”

4. A Culture of Innovation in Hamilton http://www.softwarehamilton.com http://www.appsforhealth.ca McMaster eHealth Research Network @mcmasterehealth #mcmasterehealth

5. Pillars of the Canadian Healthcare Accessibility Public Administration Comprehensiveness Portability Universality

6. Healthcare as a CAS CAS = Complex Adaptive System System of (semi-)autonomous agents. All agents related by flows of data/resources. One agent’s output is another’s input. Each agent “learns” by scanning the environment, and taking in information. The “best of breed” information will be sought by the self interested agents. Incremental learning of new rules, and forgetting obsolete ones, is the result.

7. On the Edge of Chaos Environment Repeatability Edge of Chaos! STABLE CHAOTIC • Reactability Environment fluctuates between stability and chaos Environment demands flexibility to react to evolving needs, yet repeatability to sustain efficiency and effectiveness Requires a system to be reactive, spontaneous, alive! Utility/usability of health IT is key to support a CAS!

8. CAS Learning

9. Continuous Quality Improvement (CQI) Change is best made incrementally. A sustainable system must evolve with the changing environment Teamwork, collaboration, knowledge sharing, interdisciplinarity

10. Provincial Role • Feds – Create policy & transfer payment • Province – Execute policy & monitor cost • Payer – Ontario Health Insurance Program (OHIP)

11. Local Health Integration Networks Plan, integrate and fund local health services, including: • Hospitals • Community Care Access Centres • Community Support Services • Long-term Care • Mental Health and Addictions Services • Community Health Centres. Source: http://www.lhins.on.ca

12. Model of Health IT within a Complex Adaptive Healthcare System

13. Question Period I

14. *http://www.cbc.ca/news/canada/toronto/story/2009/10/07/ehealth-auditor.html*http://www.cbc.ca/news/canada/toronto/story/2009/10/07/ehealth-auditor.html

16. What is Ehealth? More than just “technology applied to health” Ehealth gives us the power to transform healthcare processes in a way that increases efficiency and realize new capabilities

17. Considerations – Implementation

18. Behavioural Model for Health IT Outcome Expectancies Adherence to Behaviour Outcome - Variable(s) of interest

19. Chronic Disease Self Management/Personal Health and Wellness Management • Clinician • Enhanced Decision Making • Efficient Patient Management • Knowledge Discovery • Patient • Positive health outcomes • Convenience • Empowerment • Less travel time needed • Gain of knowledge as learning occurs • Membership in a community

20. Lose It! Obesity Self-Management

21. DiaMonD wireless diabetes management

22. Application – Clinical Practice Audit Six Sigma – Audit and Feedback • A scientific approach to quality improvement • Requires incessant measurement of key indicators • Data analysis leads to hypotheses as to sources of low quality

23. Clinical Practice Audit with e-Tools Social Networks/ Social Media Mobile/Ubiquitous Devices Cloud Computing/ Shared Services Web Portals

24. Challenges to Clinical Practice Audit

25. Application - Global e-Health • Healthcare delivery to developing nations • Maternal care • Using technology to deliver the best expertise to where it is needed. • Interjurisdictional delivery of care

26. Application – Knowledge Discovery in Databases (KDD) From Raw Data… …discover patterns… To Knowledge. Fayyad, U., Piatetsky-Shapiro, G., and Smyth, P. (1996). The KDD process for extracting useful knowledge from volumes of data, Communications of the ACM, 39, 11, 27-34.

27. Application – types of KDD Sequences Association Prediction Classification Clustering

28. A Wealth of Healthcare Related Data

29. From Research To Practice Collaboration between those who create knowledge and those who use it is KEY! PROBLEMS FINDINGS SOLUTIONS APPLICATIONS DISSEMINATIONS SYNTHESES KNOWLEDGE TO ACTION!!!

30. Our Current Research – Adherence • Diabetes AND Obesity • Facilitators and barriers to Adherence • Predicting discontinuance • Collaborating with Lose It! and INET (DiaMonD) • www.loseit.com • www.inet-international.com

31. Our Current Research –Practice Audit • Devices (eg mobile, handheld, RFID) • Learning/Knowledge Resources and Tools • Knowledge discovery in audit data • Research team in place, submitted several proposals

32. Out Current Research – Ontario Wait Times • Predicting Gridlock • Scheduling of Resources • Emerging Trends • Preliminary Stage • Seeking data from CIHI, CCAC

33. Conclusion • Flexibility is critical in healthcare due to an evolving, and sometimes chaotic, environment • Technology has the ability to transform, innovate and realize new capabilities in healthcare • In order to realize the benefits of technology in healthcare, considerations before implementation are necessary • Ehealth is an active and growing area of research with new challenges and possibilities – a call for teamwork, collaboration, and knowledge sharing

34. Discussion/Questions? • Opportunities for collaboration?