MIT H@cking Medicine is PSYCHED to announce our collaboration with the Office of the National Coordinator for Health IT, Tufts MedStart, and the White House Innovation Fellows surrounding the first Boston Blue Button Innovation Challenge! The event is taking place Friday, January 17th to Sunday, January 19th at Tufts Medical School, which is located in the Sackler Building at 145 Harrison Ave in Boston.. Also we will hold a Blue Button developer workshop on MIT’s campus in Building E-62 on Friday afternoon prior to the event.
Blue Button is an international movement to engage patients in their health through access to their health data in both human and machine-readable formats. This fall, all providers using MU2 certified technology will be able to support patients viewing, downloading, and transmitting their clinical data to a consumer endpoint, like a personal health record, or provider through Blue Button + Direct.
This codeathon is an opportunity for providers, patients, and the developers of consumer facing technology to come together to learn about Blue Button, identify high priority use cases, and build exciting new products that are ready to receive Blue Button data. We hope this event will foster collaborations that exist long after the codeathon ends. The ONC recently sponsored a successful codeathon on device data and health financial data in San Francisco, and we are excited to work with a new community in Boston!
The event will focus on use cases that take advantage of patient clinical data liberated through Blue Button + Direct, a technology available in all Meaningful Use certified technology starting winter 2014. The event will open with patients and providers sharing their highest priority Blue Button use cases which will guide development over the weekend and judging criteria. Example ideas may include but are not limited to:
- Co-designed applications that can improve communication between the health care provider and the patient. (ie. care plans and notes that both the patient and physician can contribute to)
- Simplifying medical jargon, content, and diagnoses for patients. (ie. consumer friendly definitions of clinical terms)
- Clinical health information visualizations. (ie. interactive lab results)
- Population trend analysis. (ie. seasonal, location specific tracking of symptoms at an aggregate level)
- Patient record matching to clinical trials.