Webinar Series: Mathematical Foundations of Data Science

Off-Policy Estimation of Long-Term Average Outcomes with Applications to Mobile Health

Speaker

Susan Murphy (Harvard University)

Abstract

Due to the recent advancements in wearables and sensing technology, health scientists are increasingly developing mobile health (mHealth) interventions.  The interventions include treatments, delivered via mobile devices, that are designed to provide in-the-moment support, that is, have the greatest impact on a proximal outcome such as near-time stress or physical activity.  Frequently expert-derived treatment policies are used; these are decision rules that map an individual's current state (e.g., individual's past behaviors as well as current observations of time, location, social activity, stress and urges to smoke) to a particular treatment at each of many time points. Many mHealth interventions are designed for long-term use in chronic disease management.    An important first step toward developing data-based, effective mHealth interventions is to properly measure the long-term performance of the treatment policies. In this presentation, we describe an approach for conducting inference about the performance of one or more such policies using historical data collected under a possibly different policy. Our measure of performance is the average of proximal outcomes over a long time period should the particular treatment policy be followed. We provide an estimator as well as confidence intervals. This work is motivated by HeartSteps, a mobile health physical activity intervention.

 Bio

Susan A. Murphy is Professor of Statistics and Computer Science, and a Radcliffe Alumnae Professor at the Radcliffe Institute, all at Harvard University. Her research focuses on improving sequential, individualized, decision making in health, in particular on clinical trial design and data analysis to inform the development of just-in-time adaptive interventions in mobile health. She graduated from Louisiana State University with a degree in mathematics and earned her PhD in Statistics at the University of North Carolina, Chapel Hill in 1989. Susan is a Fellow of the Institute of Mathematical Statistics, a Fellow of the College on Problems in Drug Dependence, a former editor of the Annals of Statistics, a member of the U.S. National Academy of Sciences, the U.S. National Academy of Medicine and a 2013 MacArthur Fellow.