3 results match your criteria: "The Hilltop Institute at the University of Maryland[Affiliation]"
Impact of the patient-centered medical home on consistently high-cost patients.
Am J Manag Care
December 2023
The Hilltop Institute at the University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250. Email:
Objective: To evaluate the effect of a statewide multipayer patient-centered medical home (PCMH) demonstration on patients consistently within the highest ranks of health services expenditure across Maryland.
Study Design: Post hoc longitudinal analyses of administrative data on privately insured patients of medical homes that participated in the Maryland Multi-Payer PCMH Program (MMPP), matched for comparison to medical homes in a single-payer PCMH program and to non-PCMH practices.
Methods: Consistently high-cost patients (CHPs) were defined as being in the top statewide quintile of payer expenditure over a 2-year baseline period.
Outpatient apheresis billing: A photopheresis model shows that hospital price transparency data remain difficult to interpret.
Am J Clin Pathol
October 2023
The Hilltop Institute at the University of Maryland, Baltimore County, Baltimore, MD, US.
Article Synopsis
- The study examines the availability and compliance of chargemaster and negotiated rates for extracorporeal photopheresis (ECP) across 20 health care institutions, highlighting the complexity of the US health care payment system.
- Results show that while the availability of chargemaster data increased from 2019 to 2022, only 65% of institutions provided both types of pricing data, with significant variations in rates observed.
- The findings indicate that current pricing resources are often insufficient for consumers needing ECP, and institutions lacking proper data face substantial financial penalties.
Assessing performance of ZCTA-level and Census Tract-level social and environmental risk factors in a model predicting hospital events.
Soc Sci Med
June 2023
Department of Information Systems, College of Engineering and Information Technology, UMBC, Baltimore, MD, 21250, USA; Erickson School of Aging Studies, UMBC, Baltimore, MD, 21228, USA.
Predictive analytics are used in primary care to efficiently direct health care resources to high-risk patients to prevent unnecessary health care utilization and improve health. Social determinants of health (SDOH) are important features in these models, but they are poorly measured in administrative claims data. Area-level SDOH can be proxies for unavailable individual-level indicators, but the extent to which the granularity of risk factors impacts predictive models is unclear.
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