ArticleJAMA internal medicine2018
Assessment of the Effect of Adjustment for Patient Characteristics on Hospital Readmission Rates: Implications for Pay for Performance.
Article in JAMA internal medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.
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Who cites it
47 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Social Risk Adjustment In The Hospital Readmissions Reduction Program: A Systematic Review And Implications For Policy.Health affairs (Project Hope) · 2022Pooled it
- Characteristics of Health Care Organizations Associated With Clinician Trust: Results From the Healthy Work Place Study.JAMA network open · 2019Trial
- Assessing the Impact of Sociodemographic Factors on Artificial Intelligence Models in Predicting Dementia: Retrospective Cohort Study.JMIR medical informatics · 2026Article
- Hospitalized patients' health-related social needs: A comparison of screenings conducted by hospital staff and research staff.Journal of hospital medicine · 2026Observational
- Effect of disability, homelessness, and neighborhood marginalization on risk adjustment for hospital performance measurement.American journal of epidemiology · 2025Article
- Measurement Bias in Documentation of Social Risk Among Medicare Beneficiaries.JAMA health forum · 2025Article
- Cohort study examining social determinants of health and their association with mortality among hospitalised adults in New York and California.BMJ public health · 2025Article
- Socioeconomic disadvantage is a leading variable in risk score for major amputation following emergent infrainguinal arterial bypass surgery.Journal of vascular surgery · 2024Article
- Medicare's Hospital Readmission Reduction Program reduced fall-related health care use: An unexpected benefit?Health services research · 2024Article
- Population Characteristics and Organ Procurement Organization Performance Metrics.JAMA network open · 2023Article
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- Social risk adjustment in the hospital readmission reduction program: Pitfalls of peer grouping, measurement challenges, and potential solutions.Health services research · 2023Article
- Operative Techniques to Reduce Hip and Knee Arthroplasty Complications in Morbidly Obese Patients.Arthroplasty today · 2022Article
- Neighborhood-Level Socioeconomic Deprivation, Rurality, and Long-Term Outcomes of Patients Undergoing Total Joint Arthroplasty: Analysis from a Large, Tertiary Care Hospital.Mayo Clinic proceedings. Innovations, quality & outcomes · 2022Article
- Association of Rurality and Neighborhood Level Socioeconomic Deprivation with Perioperative Health Status in Total Joint Arthroplasty Patients: Analysis from a Large, Tertiary Care Hospital.The Journal of arthroplasty · 2022Article
- Readmission After ACS: Burden, Epidemiology, and Mitigation.Current cardiology reports · 2022Review
- Assessing socioeconomic bias in machine learning algorithms in health care: a case study of the HOUSES index.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- Neighborhood Socioeconomic Disadvantage and Mortality Among Medicare Beneficiaries Hospitalized for Acute Myocardial Infarction, Heart Failure, and Pneumonia.Journal of general internal medicine · 2022Article
- Weak correlations in health services research: Weak relationships or common error?Health services research · 2022Article
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6 authors.
Funding
Abstract
Importance: In several pay-for-performance programs, Medicare ties payments to readmission rates but accounts only for a limited set of patient characteristics-and no measures of social risk-when assessing performance of health care providers (clinicians, practices, hospitals, or other organizations). Debate continues over whether accounting for social risk would mitigate inappropriate penalties or would establish lower standards of care for disadvantaged patients if they are served by lower-quality providers. Objectives: To assess changes in hospital performance on readmission rates after adjusting for additional clinical and social patient characteristics by using methods that distinguish the association between patient characteristics and readmission from between-hospital differences in quality. Design, Setting, and Participants: Using Medicare claims for admissions in 2013 through 2014 and linked US Census data, we assessed several clinical and social characteristics of patients that are not currently used for risk adjustment in the Hospital Readmission Reduction Program. We compared hospital readmission rates with and without adjustment for these additional characteristics, using only the average within-hospital associations between patient characteristics and readmission as the basis for adjustment, thereby appropriately excluding hospitals' distinct contributions to readmission from the adjustment. Main Outcomes and Measures: All-cause readmission within 30 days of discharge. Results: The study sample consisted of 1 169 014 index admissions among 1 003 664 unique Medicare beneficiaries (41.5% men; mean [SD] age, 79.9 [8.3] years) in 2215 hospitals. Compared with adjustment for patient characteristics currently implemented by Medicare, adjustment for the additional characteristics reduced overall variation in hospital readmission rates by 9.6%, changed rates upward or downward by 0.37 to 0.72 percentage points for the 10% of hospitals most affected by the additional adjustments (±30.3% to ±58.9% of the hospital-level standard deviation), and would be expected to reduce penalties (in relative terms) by 52%, 46%, and 41% for hospitals with the largest 1%, 5%, and 10% of penalty reductions, respectively. The additional adjustments reduced the mean difference in readmission rates between hospitals in the top and bottom quintiles of high-risk patients by 0.53 percentage points (95% CI, 0.50-0.55; P < .001), or 54% of the difference estimated with CMS adjustments alone. Both clinical and social characteristics contributed to these reductions, and these reductions were considerably greater for conditions targeted by the Hospital Readmission Reduction Program. Adjustment for social characteristics resulted in greater changes in rates of readmission or death than in rates of readmission alone. Conclusions and Relevance: Hospitals serving higher-risk patients may be penalized substantially because of the patients they serve rather than their quality of care. Adjusting solely for within-hospital associations may allow adjustment for additional patient characteristics to mitigate unintended consequences of pay for performance without holding hospitals to different standards because of the patients they serve.
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