@mandl. Bringing Big Data to the Point of Care by Creating the App Store for Health

Transcription

1 Bringing Big Data to the Point of Care by Creating the App Store for Kenneth D. Mandl, MD, MPH Professor, Harvard Medical School Director, Boston Children s Hospital Computational Health Informatics Program chip.org

2 Virginia 2011

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4 r, Mandl, ne JAMA Boston Children s Hospital Computational Health Informatics Program

5 No Linker

6 ? How do we learn from All the Patients... All the Time? (Instead of Some of the Patients All of the Time... )... or really, just a couple of the patients, not that often.

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8 Brownstein, Mandl PLoS One

9 Introduction of COX-2 Inhibitors Brownstein, Mandl PLoS One

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12 Autism Phenotype Clusters Seizures Psychiatric Disorders

13 WE USE LITTLE (AND BIASED) DATA TO MAKE OUR INFERENCES

14 Pick a number Bourgeois, Mandl PLoS One

15 Predictive Medicine: Domestic Violence High Impact Paper!! Impact on practice? Nada Reis, Kohane, Mandl BMJ

16 13 EHRs Data Returns to Health System + 13 i2b2 Sidecars SMART Apps for Patient Review Trial Matching Contact Surveys PRO Collection = SHRINE Query for Network-wide Patient List

17 Federated EHR Networks Mandl, Nature Biotechnology 2015

18 ??Data IN and Insights BACK to Point of Care??

19 2000 Conclusion: Computerized physician order entry is a powerful and effective tool for improving physician prescribing practices.

20 $48 BILLION DOLLAR FEDERAL INVESTMENT IN HIT

21 But 6 years later, we have an infrastructure that shows the clinician, one patient at a time, what he or she typed in in the past--a very narrow slice of big data

22 INNOVATORS AND INNOVATIONS CAN T GET TO THE POINT OF CARE

23 Motivation: Innovation Med-tastic is a well-funded NewCo which has developed an elegant medication list application that has physician and consumer facing functionality. Patients can annotate medication lists for accuracy. To work, Med-tastic needs Prescribing history Dispensed medication history Allergies Problem list diagnoses

24 Personalization of Therapy

25 BIG DATA COLLECTED AT POINT OF CARE DISAPPEARS

26 Turns out it Matters

27 DATA ARE NOT INTEROPERABLE

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29 BIG DATA DON T GET TO THE POINT OF CARE

30 Contextualization Annals of Internal Med 2011

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32 Designing the App Store for Health

33 API Can EMRs behave like iphones or Androids in that innovators readily create and widely distribute SUBSTITUTABLE apps across thousands of installs?

34 18.12 Issue

35 State-of-the-Art???

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37 1 Design + 1 Developer + 1 Week

38 1 SMART App in 3 SMART Systems

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40 SMART BP Centiles App Running on Cerner

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42 Decision Support Integration e.g., Immunization Forecasting

43 Monograph app e.g., Diabetes

44 Merge App e.g., Microsoft HeatlhVault and Diabetes

45 Precision Medicine App

46 Linkage to external decision support services Pharmacogenomic rule sets Decision support for doctors Big Data Mashups: e.g., Personalized Medicine: There s an App for that

47 Clayton Christensen, HBS Susanna Fox American Medical Association The Advisory Board Company AARP BMJ Canadian Institutes of Health Research CMS HCA Lily MyHealthBook Polyglot Systems Premier Surescripts UK NHS Vecna

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50 i2b2 the side car in action: EMR-like function

51 Some SMART Hotbeds

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53 Activities now Jason I and II HL7 Argonaut The SMART App Gallery Meaningful Use 3

54 gallery.smarthealthit.org

55 Kenneth D. Mandl, MD, MPH Professor, Harvard Medical School Director, Boston Children s Hospital Informatics