The Center for Population Health Informatics (CPHI) is working across disciplines and harnessing the power of data and technology to better the lives of those in St. Louis and beyond. CPHI is actively engaged in developing and studying innovative uses for data and technology at the point of care and beyond to improve population health outcomes.
Research highlights
CPHI leads in population health informatics research and serves to provide access to and training in the use of computationally-derived (“synthetic”) and health services administrative data. We additionally provide services in data analysis and visualization to advance applied clinical and population health research, including:
- Maintaining data repositories and managing data assets and data dictionaries
- Training investigators, laboratory staff, and students on the ethical and secure use of data assets
- Providing leadership on the analysis and visualization of clinical and population health data
- Facilitating collaboration among interdisciplinary investigators
- Advancing the use of data to inform researchers and the St. Louis community about health and healthcare
Randi Foraker, PhD, MA, FAHA, FAMIA, FACMI
Director, Center for Population Health Informatics
Professor of Medicine, Division of General Medical Sciences
Professor of Public Health, Brown School
randi.foraker@wustl.edu
Sunny Lin, PhD, MS
Assistant Professor of Medicine, Division of General Medical Sciences
linsc@wustl.edu
Beth Prusaczyk, PhD, MSW
Assistant Professor of Medicine, Division of General Medical Sciences
beth.prusaczyk@wustl.edu
- Joshua Landman, MS
PhD Candidate, Division of Computational & Data Sciences - Abigail Lewis, BA
PhD Candidate, Division of Computational & Data Sciences - Alicia Cicerelli
Project Manager, CPHI, Institute for Informatics, Data Science and Biostatistics
Bringing the campus ‘synthetic data’ via MDClone
MDClone is a free, secure, self-service platform for building queries and downloading computationally-derived (“synthetic”) data from the research data core (RDC). Since the data do not contain protected health information (PHI), use of these data is not classified as human subjects research.
- Spot the Difference: Comparing Results of Analyses from Real Patient Data and Synthetic Derivatives. JAMIA Open
- The Use of Synthetic Electronic Health Record Data and Deep Learning to Improve Timing of High-Risk Heart Failure Surgical Intervention by Predicting Proximity to Catastrophic Decompensation. Frontiers in Digital Health
- Predicting Mortality among Patients with Liver Cirrhosis in Electronic Health Records with Machine Learning. PLoS One
- The National COVID Cohort Collaborative: Analyses of Original and Computationally Derived Electronic Health Record Data. Journal of Medical Internet Research
Request a service
Email i2help@wustl.edu for consultation or inquiries.
Facilities and other resources
Facilities and Resources: Informatics (pdf)
Contact
For more information on the Center for Population Health Informatics, please email Alicia Cicerelli at acicerelli@wustl.edu.