Do you ever wake up in the middle of the night with a flash of creativity (or good idea)?
The idea for “Communities, Platforms and Data” came to me in the middle of the night as one of those flashes of creativity. While researching “Mobile Social Games for Health,” I found an evolving ecosystem of experimenters (shown below) across the disease spectrum from chronic disease to health and wellness. As a dentist interested in behavior change, I was excited to discover new technology approaches built upon integrating concepts from behavioral economics, behavioral psychology, and cognitive neuroscience.
I explored BJ Fogg’s approach to tiny habits, Charles Duhigg’s The Power of Habit, and Michael Christakis’s view on the importance of social networks and health.
I got hooked on understanding how data is collected, managed, analyzed and applied by users, while researching “Big Data in Healthcare – Hype and Hope.”
Examining the sources and users of health data shows a series of complex interrelationships: big sources of data are also big users of data. Sources include both structured and unstructured data. Examples of structured data include CDC epidemiological data, CMC and Medicare, some research & development data, and most financial data. Despite ongoing government initiatives, much of electronic medical and health records (EMR, EHR) data remain unstructured, including handwritten text, audio files (voice annotations), historical microfiche records, diagnostic images on CDs, and incompatible digital images. On the other side of the equation, users of data already include practically all payers, an increasing number of providers, some employers, policy makers, and a few patients, caregivers and consumers of fitness data from media old and new.
Throughout my interviews with 125 companies, I kept hearing “we need more data.” I began to understand that due to the complexity of the sources and conflicting interests of the users, data sharing, data pooling, and their sister endeavor, citizen science are just in their infancy.
During all of my research projects, I wondered how the combination of mobile social games, online support networks and data could help close the feedback loop (above) to nudge individual behavior change and get patients more interested in taking care of themselves. The concept of a feedback loop, originally an audio engineering concept and now applied in IT circles to data flow, can also be applied to behavior change in both individuals and populations.
This panel will give us three different perspectives and real-world examples on how to engage patients using data, social media and games.
- Dan Conroy of Aetna CarePass, will give us the view from an insurance company.
- Anmol Madan will describe how Ginger.io uses passive data collection.
- Bruce Springer will describe how OneHealth uses active data collection to spur behavior change.