Multilevel analysis of readmissions after radical cystectomy for bladder cancer in the USA: Does the hospital make a difference?

Document Type

Article

Department

General Surgery

Abstract

Background: Hospitals are increasingly being held responsible for their readmissions rates. The contribution of hospital versus patient factors (eg, case mix) to hospital readmissions is unknown.
Objective: To estimate the relative contribution of hospital and patient factors to readmissions after radical cystectomy (RC) for bladder cancer.
Design, setting, and participants: We identified individuals who underwent RC in 2014 in the Nationwide Readmissions Database (NRD). The NRD is a nationally representative (USA), all-payer database that includes readmissions at index and nonindex hospitals. Survey weights were used to generate national estimates.
Outcome measurements and statistical analysis: The main outcome was readmission within 30 d after RC. Using a multilevel mixed-effects model, we estimated the statistical association between patient and hospital characteristics and readmission. A hospital-level random-effects term was used to estimate hospital-level readmission rates while holding patient characteristics constant.
Results and limitations: We identified a weighted sample of 7095 individuals who underwent RC at 341 hospitals in the USA. The 30-d readmission rate was 29.5% (95% confidence interval [CI] 27.8-31.2%), ranging from 1.4% (95% CI 0.6-2.2%) in the bottom quartile to 73.6% (95% CI 68.4-78.7) in the top. In our multilevel model, female sex and comorbidity score were associated with a higher likelihood of readmission. The hospital random-effects term, encompassing both measured and unmeasured hospital characteristics, contributed minimally to the model for readmission when patient characteristics were held constant at population mean values (pseudo-R2<0.01% for hospital effects). Surgical volume, bed size, hospital ownership, and academic status were not significantly associated with readmission rates when these terms were added to the model.
Conclusions: After adjusting for patient characteristics, hospital-level effects explained little of the large between-hospital variability in readmission rates. These findings underscore the limitations of using 30-d post-discharge readmissions as a hospital quality metric.
Patient summary: The chance of being readmitted after radical cystectomy varies substantially between hospitals. Little of this variability can be explained by hospital-level characteristics, while far more can be explained by patient characteristics and random variability.

Comments

This work was published before the author joined Aga Khan University

Publication (Name of Journal)

European Urology Oncology

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