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Twitter to Tablet - Weekend Open Source Project...

Twitter to Tablet - Weekend Open Source Project for Visualizing HHS/CMS Meaningful Use Data

LIVE at http://hitech.socialhealthinsights.com

This is a presentation I gave at the 3/13/2013 @DataCommunityDC meetup at @microsoft. It s about a weekend project I started that gained traction in Health 2.0 and HIMSS circles. I have open sourced the code at https://github.com/marks/ONC-EHR-Incentives-Program-Payout-Data and welcome any additions or comments!

Mark Silverberg

March 13, 2013
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Transcript

  1. About Me & Social Health Insights Me Biz school student

    that can code Previously: Dual analytics/ engineering team member at a consumer health website Social Health Insights Yes, we really found each other via Twitter (nurses + developer) We won the HHS challenge and formed LLC to pursue our passions Honorable mention in the ONC Health Design Challenge Custom development & consulting
  2. Timeline 1. Saturday PM: Found out Sherry was having some

    difficulty geocoding data en mass in order to further analyze it 2. Sunday AM: I wanted to help so I wrote code to get the several CSVs into a schema-less database and use APIs to geocode and export back into CSV 3. Sunday-Monday: Curiosity led to me creating a web app so others can see which hospitals and providers; Sherry shows to colleagues at ONC and we tweak in order to “release” at #HIMSS13
  3. How? Ruby + Sinatra - my go-to GTD language &

    web framework MongoDB for data store - no need to worry about a schema which could restrict future mashups Data Science Toolkit for geocoding - because I could spin up a server and run it for fast and inexpensive address to lat/long translations Leaflet + clustermarker plugin for mapping Added in Foundation UI framework for responsiveness
  4. What’s Next? Government and private sector have shown interest including

    championing attestations and sales/competitive analysis Add additional views from existing data such as top/bottom states/cities in terms of attestation Mashup with more data like: Hospital/Provider compare Financial data such as claims and incentive amounts Referral graph Study outcomes & metrics of MU attesters Query data via SMS and phone call