ArticleHealth services research2022
High-frequency hospital users: The tail that wags the readmissions dog.
Article in Health services research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
6 citing papers in PubMed, 5 citations in OpenAlex.
- The SUPREME Index for 30-day all-cause readmission: development and internal validation of a machine learning-based risk stratification index in community-dwelling adults.BMC medical informatics and decision making · 2026Article
- Article
- Differential associations of homelessness with emergency department visits and hospitalizations by race, ethnicity, and gender.Health services research · 2022Article
- High-frequency hospital users: The tail that wags the readmissions dog.Health services research · 2022Article
- Readmissions performance and penalty experience of safety-net hospitals under Medicare's Hospital Readmissions Reduction Program.BMC health services research · 2022Article
- Serious Mental Illness Exacerbation Post-Bereavement: A Population-Based Study of Partners and Adult Children.Clinical epidemiology · 2022Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo describe the characteristics of high-frequency hospital users (four or more hospitalizations in a year) and the consequences of including or excluding their data from a readmission-based measure. DATA SOURCES: 2015 and 2016 Massachusetts Medicaid data. STUDY
designWe compare demographics, morbidity burden, and social risk factors for high- and low-frequency hospital users, and membership in 17 accountable care organizations. We evaluate how excluding hospitalizations of high-frequency users from a 30-day readmission measure (with or without risk adjustment) changes its rate and variability and affects performance rankings of accountable care organizations. The outcome is readmission within 30 days; each live discharge from a hospital contributes one observation. DATA COLLECTION/EXTRACTION
methodsWe studied 74 706 hospitalizations of 42 794 MassHealth members, 18-64 years old, managed-care-eligible, and ever hospitalized in 2016. PRINCIPAL
findingsAmong adult managed-care-eligible MassHealth members with at least one acute hospitalization, 8.7% were high-frequency hospital users; they contributed 30.2% of hospitalizations and 69.4% of readmissions. High-frequency users were more often male (77.1% vs. 50.0%; P < 0.001) and sicker (mean medical morbidity score was 3.3 vs. 1.9; P < 0.001) than others. They also had significant social risks: 33.1% with housing problems, 44.1% disabled, 83.2% with serious mental illness, and 77.1% with substance abuse disorder (vs. 22.0%, 27.3%, 60.2%, and 50.0%, respectively, for other hospital users [all P values <0.001]). Fully 50.7% of hospitalizations for high-frequency users led to 30-day readmissions (vs. 9.7%), contributing 72.0% of the variance in 30-day readmission, and substantially affecting judgments about the relative performance of accountable care organizations.
conclusionsA small group of high-frequency hospital users have a disproportionate effect on 30-day readmission rates. This negatively affects some Medicaid ACOs, and more broadly is likely to adversely affect safety net hospitals. How these metrics are used should be reconsidered in this context.
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