A 2019 awarded grant under the Robert Wood Johnson Foundation’s Health Data for Action program, managed by AcademyHealth.
The goal of the study is to contribute toward a more efficient and effective hospital readmission quality measure. Using data from the Health Care Cost Institute (HCCI), the researchers will develop and test condition-specific hospital readmission algorithms that could augment or replace the current 30-day all-cause remission measure. The researchers will identify admitted hospital patients with the 3-5 most common conditions using diagnostic and procedure codes on HCCI claims, as well as any subsequent hospitalization for the same individual. These pairs would form the basis for the analysis and the development of the Downstream Clinically Related Readmissions (DCRR) classification algorithm. They would develop a series of algorithms to deploy via their risk scoring information system architecture with a goal of allowing payers and providers to have their administrative data scored dynamically if they do not possess the relevant infrastructure to do it themselves. Deliverables will include a project work plan and final narrative report. The researchers will also produce paper(s) suitable for publication and present findings at national research meetings and to other stakeholder audiences as appropriate, including policymakers at the federal, state, and local levels and other key stakeholders, as part of the deliverables for this grant.
Predicting Hospital Readmissions in a Commercially Insured Population over Varying Time Horizons
Journal of General Internal Medicine | May 2023
Ian Stockwell is the senior director of analytics and research/chief data scientist at The Hilltop Institute. Read Bio
Jon Mark Hirshon, M.D., Ph.D., M.P.H., FACEP, FAAEM, FACPM is a Professor in the Department of Emergency Medic... Read Bio
Grant: #76774
Grantee Institution: University of Maryland, Baltimore County
Grant Period: 9/15/19 – 1/31/21