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Health Apps by Design: A reference architecture

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Presentation to the IEEE Toronto Section on designing health apps that work.

Published in: Health & Medicine
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Health Apps by Design: A reference architecture

  1. 1. CREATING THE NEXT GENERATION MHEALTH APP: A REFERENCE ARCHITECTURE Karim Keshavjee MD, MBA, CCFP, CPHIMS-CA Pannel Chindalo, PhD Arsalan Karim, MD, MBA Ronak Brahmbhatt, MD, MPH Nishita Saha Ryerson University, Feb 27, 2017
  2. 2. OUTLINE • Background • Challenges • Complexities, rabbit holes and confusion • Solution • Reference architecture • Conclusion
  3. 3. BACKGROUND: MOBILE APPS ARE TAKING OFF
  4. 4. DOCTORS WANT TO RX HEALTH APPS
  5. 5. BUT: HEALTH APP USE IS LOW
  6. 6. WHY?: HEALTH APPS DON’T WORK
  7. 7. SOME EXCEPTIONS Use a wearable fitness tracker Use a smart- phone application Do not use a device or app Plan to start using a device or app
  8. 8. TYPE 1 DIABETES APPS • Patients have traditionally always written down their insulin dosages and their blood sugar readings • Apps are a natural replacement of paper logs and provide some additional useful functionality • But does not apply to Type 2 diabetes, who make up 90% of patients with diabetes.
  9. 9. COMPLEXITIES, RABBIT HOLES AND CONFUSION What is preventing patients and health practitioners from adopting mHealth apps?
  10. 10. METHODS • Searched: PubMed & Google Scholar • Used gap analysis: that drew on philosophy, data science, education, life science and business analyses methods to develop a concept that would overcome the constraints and meet the goals identified • Through analysis, discussion and iteration: arrived at an evidence-informed proposed architecture • Works within the framework of clinical practice • Values the patient-physician relationship • Uses scientifically validated tools effectively
  11. 11. OUR PUBLICATION
  12. 12. 9 BARRIERS TO MHEALTH USE Conflicting Information: App provides information that conflicts with that received from health care providers (Bierbrier, Lo & Wu, 2014); Health Literacy: Language and terminology of the app may not be compatible with the patient’s health literacy (Caburnay, 2015); Data Entry: Patient has to enter the data themselves (Gruman, 2013); Meaningful Use: Patient cannot use information in a meaningful way; e.g., he or she cannot order diagnostic testing or prescribe medications to himself or herself; Lack of incentives like cost saving or social approval;
  13. 13. BARRIERS TO MHEALTH USE (CONT’D.) Not Habit Forming: Daily use of the app is not required and therefore the patient does not get into the habit of using it; Unknown Provenance: Providers don’t value data collected by patients in apps downloaded from an app store whose provenance and pedigree is not known or established (Terry, 2015); Lack of Tools: There is no way for providers to consume the large amounts of data that are collected in apps (Terry, 2015); i. i.e., visualize, analyze, derive meaning from; Lack of Interoperability: Providers unable to integrate app data into their own (EMR) for analysis or follow-up or share the data in their EMR with their patient’s apps (Abebe, 2013).
  14. 14. AT HEART – INFORMATION ASYMMETRY…
  15. 15. …AND INFORMATION CREDIBILITY Doctors are trained to trust only their own data Patient-entered data is not trusted
  16. 16. OPEN MHEALTH GROUP  Lots of technology and data × No workflow or information
  17. 17. ENGAGING THE PATIENT Does not happen in a vacuum
  18. 18. GAMIFICATION IS NOT ENOUGH • Patient engagement needs to be rooted in science, not games • Need behavior change models with evidence behind them • Prochaska’s Model • Behavior Change Wheel • Commitment needs to be cemented • Accountability to health care team • Follow-up by physician and their staff • App is ‘prescribed’ from EMR which activates App • Doctors are regulated by their colleges and are expected to act according to professional rules
  19. 19. SOLUTION: NEEDS LOTS OF INFORMATION (DATA) A. Healthcare without data is meaningless B. Must meet evidence-based content and process requirements C. Also need to track patient experience and outcome measures
  20. 20. Solution:
  21. 21. APPLICATION TO DIABETES TYPE 2 APPS • We developed screening criteria using our reference architecture for design and development of mhealth apps, • Apple iTunes and Google Play app stores were searched for diabetes apps –found 201 • Following a calibration exercise, two individuals independently reviewed and evaluated each app against the screening criteria • Data was collated and analyzed
  22. 22. RESULTS: • 201 total apps were reviewed • No app met all the criteria outlined • Most apps were replacement of paper journals or diaries • Many apps were recipe apps • Majority of the apps provided education/recommendations • Most of the apps failed at integrations with devices (glucometer, BP machine) and patients medical records (EMR, primary care provider)
  23. 23. RESULTS
  24. 24. SCORES (MAX = 15)
  25. 25. WE INTERRUPT THIS BROADCAST….. • Bluestar is a new diabetes app that must be prescribed! • It recently obtained FDA approval • Got a score of 12 (out of 15) on our rating scale • Very promising development
  26. 26. REASONS FOR NOT MEETING CRITERIA • Many apps were conference apps or guideline apps for professionals • Of the highest scoring apps, major reasons for not getting a higher score • Lack of integrations with devices–relatively easy these days (but requires FDA approval) • Lack of integration with EMRs –many features are dependent on this
  27. 27. DISCUSSION • There is great need for high quality apps which can be prescribed by a physician and whose use can be monitored by the health care team • Apps need to focus on managing the whole patient along with their disease and not a small part of a patient’s care such as self management • Better embedding physician patient relationship into patient app interactions for provider guided management
  28. 28. LIMITATIONS • Due to budgetary constraints, we did not download apps from the stores • Some vendors had poorer descriptions of their product than others • A very small number of apps were in languages that are not understood by the people conducting the review • We were not able to quantitate which apps are used and which ones are not • We did not include any patients in defining the criteria nor in reviewing the apps.
  29. 29. RECOMMENDATIONS • Apps should be prescribed and monitored by health care providers • Requires participation of EMR vendors in developing APIs for apps • mhealth app certification by a standards organization would go a long way to ensuring higher quality apps and increasing the level of trust for apps by health providers • An Interoperability Kit for EMRs and Apps would help make it easier to deploy an app • Standard interoperability for apps with medical devices would lower the investments required to create good apps
  30. 30. CONCLUSION • mHealth Apps show lots of promise, but not being used • Information asymmetry, data credibility and entering own data are main causes • Engagement framework requires a commitment to communication and empowerment • Need to use scientific, proven behavior change models • Needs to be grounded in clinical practice and within the patient-provider relationship –needs to support on-going communication and interaction after the visit is over
  31. 31. CONCLUSION • Health behavior changes are difficult to sustain • Need external motivation and commitment –App needs to be “prescribed” • Needs consistent follow-up and reinforcement • mHealth Apps need to have bi-directional integration with EMRs • Need to collect lots of experience, process and outcome data – lab, questionnaire and system use data • Use the data to constantly improve the user engagement and user experience • Use the data to improve patient disease outcomes
  32. 32. REFERENCES Chindalo P, Karim A, Brahmbhatt R, Saha N, Keshavjee K. Health Apps by Design: A Reference Architecture for Mobile Engagement. International Journal of Handheld Computing Research (IJHCR). 2016 Apr 1;7(2):34-43. Balouchi S, Keshavjee K, Zbib A, Vassanji K, Toor J. Creating a Supportive Environment for Self-Management in Healthcare via Patient Electronic Tools. Social Media and Mobile Technologies for Healthcare. 2014 Jun 30;109. Brahmbhatt R, Niakan S, Saha N, Tewari A, Pirani A, Keshavjee N, Mugambi D, Alavi N, Keshavjee K. Diabetes mHealth Apps: Designing for Greater Uptake. Studies in health technology and informatics. 2017;234:49.

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