Cohort Development includes the creation, curation, and exposure of novel datasets enabling precision health research throughout campus, as well as the recruitment, engagement, and retention of a large, diverse community of consented participants.

Leadership:

Jennifer Smith is an Associate Professor in the Department of Epidemiology. She studies the ways that genetic factors influence age-related chronic diseases, subclinical phenotypes, and their risk factors. Her work encompasses a broad range of phenotypes. She is particularly interested in the interaction between genetic and nongenetic determinants of health (such as demographic, social, and psychosocial factors) in shaping disease risk. Her research also includes biological markers that may lend insight into disease etiology and molecular mechanisms, including epigenetics, gene expression, and telomere length. Dr. Smith holds appointments in the Department of Epidemiology (School of Public Health) and the Survey Research Center (Institute for Social Research) at the University of Michigan.

Michael Dorsch, PharmD, MS
Associate Director

Michael Dorsch is the Lynda S. Welage Collegiate Professor of Pharmacy who studies digital health. His current work focuses on patient and provider-centered clinical decision support. Dr. Dorsch received his PharmD from Ohio Northern University. He completed a PGY1 pharmacy practice residency at Riverside Methodist Hospital in Columbus, Ohio, and a PGY2 cardiology specialty residency at the University of North Carolina Hospitals in Chapel Hill. He earned an MS in clinical research design and statistical analysis from the University of Michigan with an institutional K30 award from the Michigan Institute for Clinical & Health Research. Dr. Dorsch is a Board Certified Cardiology Pharmacist and named Fellow of the American College of Clinical Pharmacy, American Heart Association, and American College of Cardiology.

Cohort Development Goals:

• Develop and expose a novel integrated dataset
  • Integrate data spanning various clinical, administrative, and mobile sources, obviating the need for individual researchers to perform data integration
  • Transparently curate and clean data to allow researchers access to re-usable datasets
  • Incorporate techniques to minimize privacy risks while maximizing re-use of data
  • Identify and overcome internal and external regulatory burdens to data access
  • Integrate publicly available datasets regarding environmental exposure, socioeconomic status, and disparities
• Transform the Michigan Genomics Initiative recruiting process into a modern, scalable participant community for precision health research across campus
  • Continue to recruit, consent, and retain 10,000 participants per year through the Michigan Medicine perioperative process
  • Expand to include patients recruited through outpatient clinics
  • Expand to include pediatric patients recruited through the perioperative process
  • Enrich the dataset with novel datastreams including wearables, new sensors, and focused sub-groups
  • Transform specimen collection, processing, and analysis into a CLIA-compliant system that enables novel analytics
  • Increase outreach, participant engagement, and follow-up communication