Thursday, April 14, 2011

Open #mHealth meeting - Washington DC #omhe followed by #mCitizen summit on Saturday

For the next two days I am participating in a working meeting with a great group of thought leaders involved in mHealth. Then, on Saturday I am attending the mCitizen summit. So, you have been warned. Watch out for a stream of tweets and posts over the next 3 days. 

I will be listening to the discussions and many of my notes will be my interpretation of those discussions and NOT a recording of quotes by the participants.


Thanks to the Kaiser Family Foundation for providing the space for this meeting at the Barbara Jordan Conference Center.

Deborah Estrin and Ida Sim have co-ordinated this meeting.

The Open mHealth initiative is seeking to put an open architecture in place - a reference implementation that others can leverage to deliver health solutions. The target is to build 1-3 real consumer oriented applications in 2011.

some of the participants:

- Chris Hall of HealthCentral
- Ralph Coates of CDC
- Steve Ondra of OSTP (The White House) 
- Doug Blough of Georgia Tech
- David Aylward of Ashoka
- Glenn Moy of California Healthcare Foundation
- Julia Hoffman of the VA
- Juhan Sonin of MIT
- Brian Chapman of iDASH
- Myself of HealthCamp Foundation
- Keith Marsolo of Collaborative Chronic Care network - C3N - University of Cincinnati
- Michael Sied of C3N - University of Cincinnati
- Josh Mandel 0f SMARt at Harvard
- Daniel Myung of Dimagi
- Alan Viars of Videntity (@aviars)
- Mike Swiemik of UCLA
- Ali Emami of Microsoft HealthVault
- Umesh Madan of Microsoft Health Solutions
- Nadav Aharony of MIT
Jyoti Pathak of 4th SHARP (Mayo)  
- Paul Biondich of OpenMRS (Open Medical Record System)
- Howard  of NSF
- Bob Evans of Google - Builder of a Quantified Self platform
- Aman Bhandari of HHS
- Bakul Patel of FDA
- Stacy Lindau of University of Chicago
- Mark Begale of Northwestern
- David Mohr of Northwestern
- Tony Wasserman of Open Source for America and Carnegie Mellon
- Jeremy S of HealthCentral/Johns Hopkins
- Susannah Fox of Pew Research Center (@susannahfox)

Session 1 - Identify Core Functional Requirements through Straw Apps.

Self Monitoring as input into self care treatment

- 1/3 of US deaths due to poor lifestyle behaviors.
- Self monitoring to support treatment adherence
- personal strategies  (self awareness - actions/triggers/correlations)

Use of "Narrow-waist" term. Narrow Waist of Hourglass Architecture.

Simple protocol: IP allowed servers and clients to talk to each other easily without re-engineering and central coordination and management.

Discussion: Functional Capabilities needed for Behavior Change

There have been lots of discussions about mHealth but no discussions about core open architecture.

Post-Partum Weight Loss. 

At 6 months post-artum mean retained weight is 11.8lbs. 25% retain more than 20lbs. This is a predictor of long term obesity.

Anti-Depression in Vets

14% of depression in Vets. Response to drug regimen. 60% with active drug and 30% with placebo.

Personal Discovery and Mapping of Asthma Triggers

Trigger discovery and monitoring. Learn form others, how to filter and augment data.

Spatial mapping of triggers.

Public Health Surveillance and Delivery.

I can see this effort need ing to tie in to the Rainbow button initiative.


- Reputation / Credibility (include the crowd) / Trust / Authenticity
- high level objects
-- geospatial information
-- notifications
-- reminders
-- messages
-- Alerts
-- extensible structured data

"ecological momentary assessment" = gathering realtime real life data collection

It seems like we need a discussion about what APIs we need to enable mHealth solutions.

What are the open building blocks we need to enable mHealth Apps.

Let's start with the simple stuff we can predict and make sure we have standardized data formats. This implies we need a dictionary or directory to allow discovery of new formats. This can encourage semantic standardization. Isn't this just an extension of XML standards?

Let's leverage data models that have been previously developed. e.g. how to represent a person (what data attributes etc.)


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