News & Bulletins
The Hilltop Institute periodically posts news items and issues electronic bulletins to disseminate information about Hilltop activities and publications. Below are the three most recent. Go to the News and Bulletin Archive, below, to view previous posts.
Bulletin: Hilltop Researchers Publish Study on Predictive Model Bias
In a new article in Health Services Research titled Evaluating a Predictive Model of Avoidable Hospital Events for Race- and Sex-Based Bias, Hilltop researchers Leigh Goetschius, Fei Han, Ruichen Sun, and Morgan Henderson—along with UMBC researcher Ian Stockwell—assessed a large, productionized predictive model of avoidable hospital (AH) events for bias based on patient race and sex.
11/26/2024
Bulletin: Charting the Next Decade for the State University Partnership Learning Network
In a new blog post written for AcademyHealth, published by AcademyHealth, and also published by The Hilltop Institute, Hilltop Interim Executive Director Alice Middleton discusses her pride in the accomplishments of the State University Partnership Learning Network (SUPLN) in its first decade—forging deep connections, sharing innovative approaches, and amplifying the real-world impact of its members’ work—and her vision for the network in the next decade—playing an even more critical role in sharing information and best practices as university researchers assist states to weather policy changes, public health crises, technology advances, and other unknowns in health care.
11/20/2024
Bulletin: Hilltop Researchers Study Adaptability of the Hilltop Pre-AH Model
In a new article in Medical Care titled Behind the Curtain: Comparing Predictive Models Performance in 2 Publicly Insured Populations, Hilltop researchers Morgan Henderson, Leigh Goetschius, Fei Han, and Ruichen Sun—along with UMBC researcher Ian Stockwell—share the findings of a study they conducted on the inner workings of the Hilltop Pre-AH Model™, a large-scale predictive model that predicts the risk of avoidable hospitalizations and has been deployed in two distinct populations—Medicare and Medicaid—with a particular emphasis on adaptability issues.
09/10/2024