Below is a listing of select Hilltop publications and presentations. You can search by type, topic, date, and/or title. The search function searches for key words in both the title and the publication summary. Click on the publication’s title below to go to its summary.
Accessibility Notice: Publications released before April 24, 2026 have not been remediated for Section 508 compliance.
Principal Policy Analyst Christine Gill, PhD, presented this poster at the 2026 AcademyHealth Annual Research Meeting (ARM) held May 30–June 2 in Seattle.
Principal Policy Analyst Christine Gill, PhD, presented this poster at the 2026 AcademyHealth Annual Research Meeting (ARM) held May 30–June 2 in Seattle.
Policy Analyst Morgane Mouslim, DVM, ScM, presented this poster at the 2026 AcademyHealth Annual Research Meeting (ARM) held May 30–June 2 in Seattle.
Policy Analyst Morgane Mouslim, DVM, ScM, participated on a panel and gave this presentation at the 2026 AcademyHealth Annual Research Meeting (ARM) held May 30–June 2 in Seattle.
Hilltop Senior Director of Analytics & Research Morgan Henderson, Senior Director of Health Reform Studies Laura Spicer, and Executive Director Alice Middleton discuss the only two states that implemented Medicaid work requirements: Arkansas (which reported high compliance) and Georgia (where enrollment has remained extremely low) in this article published in AEA Papers and Proceedings.
Leigh Goetschius, PhD, Danielle Barefoot, MEd, Fei Han, PhD, Ruichen Sun, MS, and Morgan Henderson, PhD, co-authored this article published in The American Journal of Managed Care.
The authors discuss the results of Hilltop’s large-scale risk predictive model based on administrative claims and conclude that the model can predict severe type 2 diabetes events for the Medicare FFS population in Maryland.
In 2014, the state of Maryland partnered with the Centers for Medicare and Medicaid Services (CMS) to modernize its unique all-payer rate-setting system for hospital services to improve the overall health of Maryland residents by increasing health care quality and reducing the cost of care. In service of providing better care at lower costs, The Hilltop Institute at UMBC, in partnership with the Maryland Department of Health, has developed predictive risk stratification models to identify patients at high risk for potentially preventable health care utilization that can be used to help target care resources to the patients who need them most.
This document strives to explain the intended use, technical implementation, and model performance of the Hilltop Pre- Models as of January 2026. The Pre- Models are a suite of prediction tools spanning the Pre-AH Model, Pre-DC Model, and Pre-HE Model. This document will be updated as the models are updated or when new models become operational, and significant changes will be noted in the documentation edit history table and in the text when necessary.
The Hilltop Pre-HE Model—which generates the rankings for the Hospice Eligibility and Advanced Care Planning (Pre-HE) scores—is designed to support proactive advanced care planning discussions by estimating a patient’s risk of eligibility for hospice. The Pre-HE Model provides risk scores and reasons for risk for all attributed beneficiaries of Maryland Primary Care Program (MDPCP) practices every month in order to identify patients that are potentially appropriate for hospice care and to provide care teams with information that can guide the sensitive and difficult conversations about end-of-life care with patients and their families.
The Hilltop Pre-DC Model—which generates the rankings for the Severe Diabetes Complications (Pre-DC) scores—is designed to facilitate the active management of type 2 diabetes by estimating individuals’ risk of incurring inpatient admissions or emergency department (ED) visits for severe diabetes complications. The Pre-DC Model provides risk scores and reasons for risk for all attributed beneficiaries of Maryland Primary Care Program (MDPCP) practices every month to help care teams proactively identify high-risk individuals and allocate scarce care management resources.
The Hilltop Pre-AH Model—which generates the rankings for the Avoidable Hospitalizations (Pre-AH) scores—is designed to assist providers by allowing them to easily identify patients at a high risk of incurring an avoidable inpatient hospitalization or emergency department (ED) visit. The Pre-AH Model provides risk scores and reasons for risk for all attributed beneficiaries of Maryland Primary Care Program (MDPCP) practices every month to help care teams make informed decisions about how to direct scarce care coordination resources to the individuals who will benefit from them the most.