Predictive Modeling
Hilltop is at the forefront in the use of artificial intelligence (AI) and machine learning in applied health services research and analytics. Hilltop is collaborating with the Maryland Primary Care Program (MDPCP) to support the delivery of advanced primary care throughout the state and allow community providers to play a vital role in prevention, improving health outcomes, and controlling total health care spending growth. Hilltop designed and implemented the Hilltop Pre-AH Model that predicts the risk of avoidable hospitalizations for individuals in Maryland’s Medicare population. Hilltop also developed models to predict inpatient admissions or emergency department visits for severe diabetes complications and all-cause mortality, as well as a model of COVID-19 hospitalizations and a model of readmission for commercially insured patients.
11/22/2024
Evaluating a Predictive Model of Avoidable Hospital Events for Race- and Sex-Based Bias
08/04/2024
Behind the Curtain: Comparing Predictive Models Performance in 2 Publicly Insured Populations
12/19/2023
Risk Score Specifications and Codebook for The Hilltop Institute’s Pre- Models, Version 2
04/01/2023
The Hilltop Pre- Models: In Brief
04/01/2023
The Hilltop Pre-HE Model™: Hospice Eligibility & Advanced Care Planning Fact Sheet
03/01/2023
The Hilltop Pre-AH Model™: Avoidable Hospitalizations Fact Sheet
11/28/2022
Predicting Hospital Readmissions in a Commercially Insured Population over Varying Time Horizons
09/01/2022
The Hilltop Pre-DC Model™: Severe Diabetes Complications Fact Sheet
07/01/2022
Hilltop Pre-AH Model™ Infographic
11/01/2020
Predictive Modeling Suite: How We Do It
06/29/2020
Maryland Primary Care Program (MDPCP) Pre-AH Risk Score Specifications and Codebook, Version 3
01/01/2020