Health Implementation will devise the overall process by which promising precision health discoveries can be integrated into Michigan Medicine patient care and health systems throughout the state of Michigan, as well as informing improvements in health care nationwide. Leaders and providers throughout the health system are key partners in the success of this initiative.
Sachin Kheterpal is associate professor of anesthesiology and associate dean for research information technology at the University of Michigan Medical School. He received his bachelor’s, medical degree and master’s in business administration from the University of Michigan. Kheterpal’s career has been focused on the novel use of IT and electronic health records for patient care, quality improvement and research. He is recognized as a national leader in perioperative large dataset clinical research and has published numerous articles, editorials and book chapters regarding intraoperative management and long-term postoperative outcomes. Using innovative techniques to integrate administrative, EHR and registry data across institutions, he leads the Multicenter Perioperative Outcomes Group, a research and quality improvement consortium of more than 40 anesthesiology and surgical departments.
Hae Mi Choe is Associate Dean and Chief Quality Officer for the University of Michigan College of Pharmacy and University of Michigan Medical Group, respectively. She earned her PharmD from the University of California, San Francisco, and completed her pharmacy practice residency with Kaiser Permanente. Choe created a group practice model for ambulatory clinical pharmacists at Michigan Medicine. She is recognized as a national leader for developing innovative clinical programs for pharmacists. She also leads a statewide initiative involving more than 20 physician organizations to improve quality and patient outcomes through embedding pharmacists in direct patient care. She has focused her research efforts on improving chronic disease management and care delivery models.
- Identify barriers to the evaluation of algorithms, AI, clinical therapeutics, novel diagnostics, and process redesign interventions in IRB-approved patient populations at Michigan Medicine
- Identify and correct data source limitations that prevent implementation science
- Design an open-source decision support and visualization framework that allows integration of electronic health records, social determinants of health, digital phenotype, and genetics with novel algorithms to provide clinical decision support at the point of care
- Enable novel algorithms and AI to be exposed and tested in micro-randomization trials of patients and providers at Michigan Medicine
- Implement the decision-support system throughout various Michigan Medicine clinical settings, enabling campus researchers to work with patients and providers with a range of scientific needs
- Enable at-scale implementation science of precision health data streams at Michigan Medicine clinical sites
- Partner with statewide Collaborative Quality Initiatives (CQIs) led by U-M faculty to disseminate advances in clinical guidelines, decision support tools, clinical therapeutics, and novel diagnostics
- Work with payers and policymakers to identify and overcome financial and regulatory barriers to implementation of reproducible, generalizable evidence
- Enhance U-M’s reputation in implementation science and precision health implementation via peer-reviewed publications and enhanced competitiveness for sponsored research