To keep a finger on the pulse of digital health developments at the bleeding edge, I attended the final presentations at MIT Hacking Medicine’s Grand Hack 2016.
There were three tracks:
Connected Health Track
Redesign care pathways and patient health management through smarter use of healthcare data.
Healthcare at Home Track
Design solutions to enable patients and patient families to maintain their health and independence comfortably in their homes.
Chronic Conditions Track
Transform the way those with chronic conditions manage their health and experience their day-to-day lives.
The organizers (led by Zen Chu, working mostly in the background, with his students doing the heavy lifting all weekend), pulled together an impressive roster of mentors and judges for the event. Even split up into three tracks and with presentations limited to just a couple of minutes, there were enough teams at the Grand Hack to make the final presentations last several hours. I wandered from track to track, and offer my tweets (and a link to the broader tweetstream) for your perusal.
Across all tracks, the range of issues being tackled by the hackathon teams was as staggeringly diverse as anyone with passing familiarity with the U.S. health care (non) system might imagine, ranging from medication adherence, to anonymous STD diagnosis sharing, to early diagnostics for Parkinson’s, to building better communities and coaching for diabetics, to a tool seeking to protect against opioid abuse relapse by monitoring communications with “friends” taggged as “safe” or as on a “watchlist,” to online bill payment, to physical therapy compliance and coaching, to a SaaS tool for traumatic brain injury treatment for veterans. The ideas presented (developed within the confines of the hackathon) of course were early-stage, and some showed more promise than others. Some seemed to demonstrate a lack of awareness of other tools already out there doing the same or similar things — but I will chalk that up mostly to youthful enthusiasm; frankly, while a handful of ideas hashed out at a hackathon like this may proceed to development as features, products or even companies, the key output of an event like this is energized hackers eager to solve big problems in healthcare. As the organizers said more than once in the lead-up to the announcement of the winners of various categories of prizes, the judges are often wrong, meaning that it is often the teams that do not win recognition at hackathons that go on to develop products and form companies that are successful in the digital health space.
I spoke with Alejandro Scaffa, a member of the “alzEYEmer’s” team, after they won one of the prizes in the Healthcare at Home track. The team’s presentation included a demo of software recognizing household objects and hazards from a camera to be worn around the neck of an Alzheimer’s patient living alone with, say, some hours of daily help (family or home health aide) but with many hours of each day home alone. Upon recognizing a hazard (say, a stovetop fire or other image identified by the system as hazardous), the device can alert the patient with recorded redirection prompts, alert a family member, alert a caregiver, or even initiate a 911 call, depending on the severity of the situation.
The team came to the Grand Hack together, but without a definite plan for a problem to work on. (All but one are graduate students or on research staff at Brown University, and most of them are actively working on other projects together.) They gravitated to the Healthcare at Home track and a project focused on computer vision, AI, neuroscience and Alzheimer’s based on the expertise and personal experience of team members. Alejandro spoke very highly of the mentors at the Grand Hack, whose expertise in coding, financing and disease-specific matters was invaluable to the team. For example, once they had determined to work on an Alzheimer’s related project, a mentor was able to connect the team with a number of family members of Alzheimer’s patients in order to vet ideas for their hack.
The team’s various members bring different competencies to the table, all of which are needed in order to tackle a complex problem with a solution that looks simple. This is, of course, one of the hallmarks of a successful product: something that can be explained easily, sounds and looks simple and intuitive, but requires a good deal of “plumbing” and attention to triggering motivations to initiate and continue using the product.
Alejandro articulated his view of the Grand Hack as “not just a hackathon” — but also a nurturing environment. From what I saw at the MIT Media Lab, his perspective was shared by many.
Images courtesy MIT Hacking Medicine
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