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The Impact of Hospital Size on CMS Hospital Profiling

Bibliographic Data

ID9101918
AuthorsEugene A Sosunov (Mount Sinai Medical Center), Natalia Egorova (0000-0002-9244-2900), Natalia N Egorova, Hung-Mo Lin (0000-0001-5885-3135), Hung‐Mo Lin (0000-0003-3176-6570), Ken McCardle (0000-0002-1645-4977), Vansh Sharma, Vanshdeep Sharma (0000-0002-6266-9944), Annetine C Gelijns (0000-0001-5389-953X), Alan J Moskowitz (0000-0002-4412-9450)
Year2016
Volume54
Issue4
Pages373-379
Publication date2016-04-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueMedical Care (JOURNAL)
Journal identifiersISSN: 0025-7079 • E-ISSN: 1537-1948
PublisherOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/mlr.0000000000000476
PMID26683782
OpenAlexW2328658266
LanguageEN
Citations received2
References cited27

BACKGROUND: The Centers for Medicare & Medicaid Services (CMS) profile hospitals using a set of 30-day risk-standardized mortality and readmission rates as a basis for public reporting. These measures are affected by hospital patient volume, raising concerns about uniformity of standards applied to providers with different volumes. OBJECTIVES: To quantitatively determine whether CMS uniformly profile hospitals that have equal performance levels but different volumes. RESEARCH DESIGN: Retrospective analysis of patient-level and hospital-level data using hierarchical logistic regression models with hospital random effects. Simulation of samples including a subset of hospitals with different volumes but equal poor performance (hospital effects=+3 SD in random-effect logistic model). SUBJECTS: A total of 1,085,568 Medicare fee-for-service patients undergoing 1,494,993 heart failure admissions in 4930 hospitals between July 1, 2005 and June 30, 2008. MEASURES: CMS methodology was used to determine the rank and proportion (by volume) of hospitals reported to perform "Worse than US National Rate." RESULTS: Percent of hospitals performing "Worse than US National Rate" was ∼40 times higher in the largest (fifth quintile by volume) compared with the smallest hospitals (first quintile). A similar gradient was seen in a cohort of 100 hospitals with simulated equal poor performance (0%, 0%, 5%, 20%, and 85% in quintiles 1 to 5) effectively leaving 78% of poor performers undetected. CONCLUSIONS: Our results illustrate the disparity of impact that the current CMS method of hospital profiling has on hospitals with higher volumes, translating into lower thresholds for detection and reporting of poor performance

Health care · Logistic regression · Medicaid · Retrospective cohort study · Emergency Medicine · Healthcare Policy and Management · Internal Medicine · Medicine · Patient Satisfaction in Healthcare · Primary Care and Health Outcomes

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Unique citing works2
Citations per year0,25
Citation span2018 - 2021 (4)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 2

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