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Technology to Improve Care

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Presentation on theme: "Technology to Improve Care"— Presentation transcript:

1 Technology to Improve Care
Steve Daviss MD DFAPA Chief Medical Informatics Officer M3 Information, LLC Rockville, MD

2 Hats I Wear CMIO, M3 Information President, Fuse Health Strategies
Assembly Recorder, American Psychiatric Association Chair, APA Committee on Mental Health IT Chair, Parity Accreditation Committee, ClearHealth Quality Institute Psychiatrist Family member Shrink Rap Blog/Book, My Three Shrinks Podcast SAMHSA? @HITshrink

3

4 @HITshrink

5 Basic infrastructure Assessment tools Electronic Health Records (EHRs)
Health Information Exchange (HIE) Care coordination/Care management “Big data” Assessment tools Active vs Passive Telehealth Genetics Neuroimaging

6 App Reviews – APA Guidelines APA Innovation Lab
@HITshrink

7 @HITshrink

8 @HITshrink

9 @HITshrink

10 EHRs BH left behind - market, privacy, HITECH $, state laws
lack of features need - psychotherapy notes interoperability, datablocking usability Valant, Askesis, Netsmart, Credible @HITshrink

11 @HITshrink

12 HIEs HL7, interoperability, CCDA
opt-in, opt-out, DS4P, who owns the data states, privacy PDMPs third-party APIs Mirth, Intersystems, Medicity @HITshrink

13 @HITshrink

14 Care coordination, Care management
web, texting, apps scheduling, logistics, transportation population health, analytics Phytel, CareManager, Mindoula, Quartet @HITshrink

15 Mindoula @HITshrink

16 Big Data data analytics, machine learning, cognitive computing
predictive modeling, comorbidities limitations, poor quality data, claims sensor-based data — phone as tracker Netsmart, Explorys, ginger.io @HITshrink

17 @HITshrink

18 Active Assessment Measurement-based care Multidimensional assessments
USPSTF - screen for depression, look beyond depression EHR integration, workflow M3 Checklist, LabCorp, BH-Works @HITshrink

19

20 LabCorp’s M3 Checklist @HITshrink

21 M3 Checklist @HITshrink

22 Passive Assessment sensor-based: phone/text activity, GPS, fitbit
voice & speech characteristics privacy Ginger.io, Neurolex, MindStrong @HITshrink

23 Telehealth real-time televideo for teletherapy, consultations
effectiveness same as face-to-face access to care standards, licensing, privacy, reimbursement Breakthrough, Arcadian, BetterMynd, Silvercloud @HITshrink

24 @HITshrink

25 Genetics pharmacogenetics costs, privacy Genomind, Assurex, 23andMe
@HITshrink

26 @HITshrink

27 Neuroimaging fMRI QEEG MEG NeuroGuide, BrainMaster @HITshrink

28 Mental Health Apps: iTunes
@HITshrink

29 Mental Health Apps: Android
@HITshrink

30 App Stores Ratings are Not Helpful
K Singh et al. Many Mobile Health Apps Target High-Need, High-Cost Populations, But Gaps Remain. Health Affairs. 2016 Slides courtesy of @JohnTorousMD

31 Why Static Scores Don’t Work
Apps are always changing and updating SCORE? Dynamic Health Context Personal There is no A+ or ’95/100’ medication or therapy or treatment Many personal factors ratings cannot account for It depends on the context and patient at hand. @JohnTorousMD

32 American Psychiatric Association Jan 2017: App Evaluation Model – A Customized Framework
No Static Score Instead a hierarchy and questions to guide informed decision making, ensuring relevant information is considered. @JohnTorousMD

33 APA App Evaluation Model
Safety Efficacy Usability Interoperability App App App Remaining Apps Apps that share data in useful ways App Apps that easy to use and stick with App Apps that have evidence to support use Apps that respect privacy and secure data @JohnTorousMD

34 APA App Evaluation Model
Ground Understanding the context of the app Ease of Use Understanding usability and adherence Risk / Privacy / Security Assessing for potential risk and harm Interoperability Making sure data is used meaningfully Evidence Ensuring the app may offer benefits @JohnTorousMD

35 Ground Level ☐ Business model / If free then how does it support?
☐ Developer ? ☐ Does it claim to be medical? ☐ Cost / In-App Purchases / Free? ☐ Advertising? ☐ What platforms does it work on? ☐ When was it last updated? @JohnTorousMD

36 Risk, Privacy, and Security Level
Apps present some unique risks that may often be overlooked including profiling, loss of confidentiality, and misinformation RISK RISK @JohnTorousMD

37 Risks: Privacy / Transparency
@JohnTorousMD

38 Risk/Privacy and Safety
Is there a privacy policy? What data is collected? Is personal data de-identified? Can you opt out of data collection? Can you delete data? Are cookies placed? Who is data shared with; what data is shared? Is data maintained on the device or the web? What security measures are in place? Is data encrypted on the device and server? Does it say it meets HIPAA / (or not need to) @JohnTorousMD

39 Evidence Level App developers often make many claims even though there is currently little clinical evidence to support such. This does not mean that apps don’t work, but rather that there is much we still do not know. Evidence Evidence @JohnTorousMD

40 Evidence ☐ What does it claim to do vs actually do?
☐ Is there peer-reviewed, published evidence about tool or science behind it? ☐ Is there any feedback from users to support claims (App store, website, Review sites, etc)? ☐ Does the content appear of at least reasonable value?

41 Ease of Use Level An app is only as useful as you find it to actually use Use Use

42 @HITshrink

43 Adherence Owen et al. mHealth in the Wild: Using Novel Data to Examine the Reach, Use, and Impact of PTSD Coach. JMIR Mental Health. Dec 2015 @JohnTorousMD

44 Ease of Use Is it easy to access for the patient at hand?
Would it be easy to use on a long term basis? Is it customizable? Does it need internet to work? What platforms does it work on? Accessible for those with impaired vision or other disabilities? @JohnTorousMD

45 APA App Evaluation Model
Interoperability Making sure data is used meaningfully Risk / Privacy / Security Assessing for potential risk and harm Ease of Use Understanding usability and adherence Ground Understanding the context of the app Evidence Ensuring the app may offer benefits @JohnTorousMD

46 Data Sharing Can it share data with EHR? Can you print out your data?
Can you export/download you data? Can it share data with other user data tools (eg, Apple HealthKit, FitBit)? @JohnTorousMD

47 Online at Psychiatry.org

48 APA Psychiatry Innovation Lab
How It Works The event will be a highly collaborative and hands-on experience guided by a panel of expert judges. The Psychiatry Innovation Lab has four parts: Pitch an Idea Learn from Experts Build a Team + Design a Venture Win Prizes psychiatryinnovation.com @HITshrink

49 2017 Grand Prize Winner: Jeff Clark – Slumber Camp
@HITshrink

50 Fall 2016 Grand Prize Winner: Joseph Insler – Overdose Recovery Bracelet
@HITshrink

51 Spring 2016 Grand Prize Winner: Jim Schwoebel -- NeuroLex
neurolex.ai @HITshrink

52 AlzHelp @HITshrink

53 PTSD Nightmare Prevention
@HITshrink

54 MiHelper @HITshrink

55 App Reviews – APA Guidelines APA Innovation Lab
Basic infrastructure Electronic Health Records (EHRs) Health Information Exchange (HIE) Care coordination/Care management “Big data” Assessment tools Active vs Passive Telehealth Genetics Neuroimaging App Reviews – APA Guidelines APA Innovation Lab

56 Technology to Improve Care
Steve Daviss MD DFAPA Chief Medical Informatics Officer M3 Information, LLC Rockville, MD

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