Workgroups

PROMPT Precision Health Study

Workgroup Leaders:

Srijan SenSrijan Sen, MD, PhD

Srijan Sen is the Frances and Kenneth Eisenberg Professor of Depression and Neurosciences and Associate Chair for Research and Faculty Development in the Department of Psychiatry at the University of Michigan. He received his MD and PhD from the University of Michigan, completed a psychiatry residency at the Yale University and returned to Michigan as faculty in 2009. The Sen Lab’s Intern Health Study is a longitudinal cohort study that assesses stress and mood in medical interns. In addition to understanding physician depression, Dr. Sen utilizes physician training as a model to better understand how stress leads to depression in general. The work has advanced our understanding of the biology of depression under stress and influenced medical education policies put forward by healthcare institutions and the ACGME. Sen has received many awards including the Seymour Lustman Award, the American Psychological Association/Lilly Resident Research Award, the NIMH BRAINS Award and the U-M Endowment for the Basic Sciences.

 


Amy Bohnert, PhD, MHS

Amy S.B. Bohnert is a mental health services researcher with training in public health who focuses her research on epidemiology and brief interventions regarding substance use and related disorders. Within a team of collaborators at the University of Michigan and the Department of Veterans Affairs, she has led a number of projects related to overdose and prescription drug safety. A number of her research activities have been specifically aimed at improving care occurring in substance use disorder treatment settings. Dr. Bohnert has demonstrated a particular expertise in applying epidemiology methods to the analysis of electronic health records-based datasets to answer important questions for health services delivery. Dr. Bohnert earned her PhD in Public Health at Johns Hopkins University and completed her postdoctoral fellowship with the Department of Veterans Affairs, National Serious Mental Illness Treatment Research and Evaluation Center in Ann Arbor, MI. She has an appointment as an Associate Professor in the Department of Psychiatry at the University of Michigan.

 

Use Case

The PROviding Mental health Precision Treatment (PROMPT) Precision Health Study is the second use case funded by Precision Health (PH) and has the potential to position the University of Michigan as the leader in precision mental health.

Depression, sleep disorders, addiction, and anxiety are leading and growing causes of disability, productivity loss, and premature mortality globally. The number of behavioral health clinicians available to provide face-to-face, traditional care, however, is woefully inadequate to meet the growing need. Further, a substantial proportion of patients who receive traditional care do not get better. With inadequate evidence to meaningfully guide treatment decisions and little objective measures of mental health symptoms available, choice of treatment is often based on clinician preference and simple heuristics.

More than any other advancement in the past decades, mobile technology has the potential to address the dual problems of limited clinical capacity and inadequate and untimely data. Mobile technology holds the potential to both track and intervene in depressive symptoms in powerful ways not previously possible. Little is known about how to derive the greatest value from this technology, however, be it targeting patients most likely to benefit or providing clinicians with the most useful information from the data collection process.

The overall goal of PROMPT is to reduce the burden of depression by 1) increasing capacity in the mental health care system through expanding use of mobile technology-delivered interventions and 2) accelerating recovery from mental illness by better matching patients to pharmacological, psychological, and mobile-based treatments. To do so, investigators will assess the independent and combined effectiveness of two kinds of mobile technology interventions for four weeks, among patients on the waitlist for traditional care. They will use machine learning to identify key predictors of treatment response from mobile technology, genomic, and environmental data collected from patients receiving either mobile technology interventions while on the waitlist for care, or traditional face-to-face psychotherapy and/or medication treatment

This collaborative project will draw on the expertise of researchers and schools across campus. PROMPT collaborators include, among others, Emily Mower Provost, PhD, and Jenna Weins, PhD, from the College of Engineering; Daniel Forger, PhD, and Ambuj Tewari, PhD, from LSA; Vicki Ellingrod, PharmD, FCCP, and Corey Lester, PharmD, PhD, from the College of Pharmacy; and Daniel Eisenberg, PhD, and Zhenke Wu, PhD, from the School of Public Health. Partner organizations on the project include Michigan Medicine Outpatient Psychiatry (for recruitment of community members), and University Health Service (for recruitment of students).