Big data, but for health care and treatment. That’s the idea that Jukka-Pekka “JP” Onnela, PhD had that led to the creation of the Beiwe app, the mobile side of the Beiwe research platform that uses modern smartphone technology to collect data for clinical studies. Rocket Farm Studios was honored to work with Onnela on this mobile app that is providing a better way to gather better information.
Onnela is a transplant from Finland brought to Boston as a result of winning a Fulbright scholarship, and is now an Assistant Professor of Biostatistics at Harvard University. There, he runs the Onnela Lab which focuses on statistical network science and digital phenotyping. Explains Onnela, “in the former, we study social and biological networks and develop new mathematical models for them. The latter refers to moment-by-moment quantification of human social and behavioral data from personal digital devices.”
In essence, Onnela and his team are looking to use data to explain how and why people act like they do. One tangible area Onnela is researching is in patient care. Traditionally, gathering patient outcome data before or after treatment has been difficult. “We have worked with CDR (call detail records) data to learn about social networks, but people are generally bad at recalling events and the networks are very large,” Onnela said. “So we thought smartphones would be a good tool to collect real-time data to create social and behavioral phenotypes for people who suffer from certain diseases.”
“Medical data collection or intervention usually takes place in hospitals, but this only happens every so often. But the paradigm is starting to change. For example, one collaborator is a neurosurgeon who operates on people with brain tumors. How do we know if the patients are doing well? My collaborators meet with his patients twice, once before and once after surgery. Then the patients are sent surveys by mail. Traditionally, there’s about four points of data collection. Our idea is to use digital smartphone “breadcrumbs,” collect much more data, and turn them into biomedically useful information.”