The Clinical Informatics and Clinical Innovation Program at the University of Michigan serves as a cornerstone for the establishment of a comprehensive Learning Health System (LHS) focused on diabetes and metabolism. This program leverages advanced informatics, data science, and cutting-edge clinical research to drive innovative solutions and improve patient outcomes in the realm of metabolic diseases.
Our program integrates electronic health records (EHRs), patient-reported outcomes, and other real-world data to create a dynamic and continuously learning environment. By employing sophisticated analytics and machine learning, we aim to identify trends, predict disease progression, and personalize treatment strategies. This iterative process of data accumulation and analysis not only enhances our understanding of diabetes and metabolic disorders but also informs clinical practice and guides future research.
Collaboration is at the heart of our initiative, bringing together a multidisciplinary team of clinicians, researchers, data scientists, and patients. By creating a robust Learning Health System, we aim to improve patient outcomes, advance our knowledge of metabolic diseases, and set new standards for clinical practice and research at the University of Michigan and beyond.
How We Serve Your Research Needs
CDI Data Repository
The team develops and produces specialized curated data elements focused on obesity and diabetes using local electronic health record data of patients seen at Michigan Medicine. Key data elements include metrics such as diabetes complications, relevant anti-glycemic medications, data from diabetes devices including meters, continuous glucose monitors, and insulin pumps, longitudinal growth and weight trajectories, patient questionnaires on nutrition, sleep, and physical activity, and social determinants of health. The Repository includes information from the Diabetes Research Registry (DRR) which consented >8750 Michigan Medicine’s ambulatory care clinics’ diabetes patients who are interested to participate in clinical diabetes research, completed questionnaires about their diabetes, consented to have their medical records searched, and agreed to be contacted by investigators with UM IRB-approved research.
Custom Data Pulls
Provides varying datasets for researchers and clinical stakeholders, including summary-level data, limited/coded datasets, or full-PHI (identifiable) datasets of Michigan Medicine electronic health record data for the purposes of clinical care, research, or quality improvement.
Custom Visual Dashboards
Creates customized visual dashboards using Tableau business intelligence software to support real-time operations, research recruitment, and cohort monitoring.
Consultative Services
Offers one-on-one consultations to provide guidance on study design, data availability, statistical methods, regulatory requirements, and customized health IT tools to help researchers integrate their work into the “real-world” healthcare delivery setting.
The team helps stakeholders navigate the complexities of the electronic health record by:
- understanding which provider-facing tools can be used to capture data in the context of clinical care
- identifying which patient-facing tools can be used to capture patient-reported outcomes
- communicating how the tools can be integrated seamlessly into clinical workflows.
Key Personnel
Joyce Lee, MD, MPH
Program Director
joyclee@med.umich.edu
Emily Dhadphale, CCRP
Project Manager
ehirschf@med.umich.edu
Jung Eun Lee, MS
Data Analyst
lejungeu@med.umich.edu
Contact Us
CDI Informatics and Clinical Research Innovation
Joyce Lee, MD, MPH and Emily Dhadphale, CCRP
joyclee@med.umich.edu and ehirschf@med.umich.edu