In this exclusive interview Indu Subaiya, CEO of Health 2.0 talks with Ginger.io’s CEO Anmol Madan and Julia Winn, previous CEO of BetterFit Technologies, to discuss how their respective companies came together to make sense of the duality of active and passive patient data collection. They also dive into the challenges facing clinicians to make timely interventions across a large-scale patient population and how Ginger.io is creating the solution.
Join Health 2.0 at the 2013 mHealthSummit on Monday December 9th in Washington DC to see Julia Winn demo how BetterFit Technologies has integrated with Ginger.io on the panel Future of Self-Tracking and Personalized Medicine. Register here.
Indu Subaiya: Let me start by welcoming you, Anmol and Julia, to the conversation. We’re looking forward to having you at Health 2.0. Why don’t we begin by starting with you, Anmol. Give us a bit of a background and history of Ginger.io. We had you present at Health 2.0 in 2011. Tell us a bit about your roles in the company and how you’ve developed in the last couple of years.
Anmol Madan: We’ve been around for about 2 ½ years and presented at Health 2.0 in our very early days. At Ginger.io we work with passive mobile phone data and behavior analytics for chronic patient populations. For providers and other players in the health care ecosystem, we help them manage their patient populations better so we help identify which of their patients are likely asymptomatic at that point of time. The idea is to enable doctors, nurses, and also family members and friends to reach out to their patients and support them when they need help the most.
Indu Subaiya: The term that you use often in describing what you do is ‘passive data’. Can you tell us a little bit more about what that means specifically and how you distinguish passive data from other types of data that consumers are collecting about themselves?
Anmol Madan: Absolutely. Every one of us is carrying a mobile phone and it’s an incredibly powerful diary of your life because it has all sorts of sensors built in. There is a tremendous amount of data generated, and the complexity around interpreting this data, delivering insights, and making them actionable is a really interesting problem for us at Ginger.io.
