Multilevel Analysis of Readmissions After Radical Cystectomy for Bladder Cancer in the USA: Does the Hospital Make a Difference?

Eur Urol Oncol. 2019 Jul;2(4):349-354. doi: 10.1016/j.euo.2018.08.027. Epub 2018 Sep 25.

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.

Keywords: Cystectomy; Healthcare quality, access, and evaluation; Multilevel analysis; Patient readmission; Quality of health care; Reimbursement incentive; Urinary bladder neoplasms; Urological surgical procedures.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Cystectomy*
  • Female
  • Hospitals / statistics & numerical data*
  • Humans
  • Male
  • Middle Aged
  • Patient Readmission / statistics & numerical data*
  • United States
  • Urinary Bladder Neoplasms / surgery*