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Multilevel analysis of readmissions after radical cystectomy for bladder cancer in the USA: Does the hospital make a difference?
European Urology Oncology
  • Alexander P Cole, Harvard Medical School, Boston
  • Ashwin Ramaswamy, Harvard Medical School, Boston
  • Sabrina Harmouch, Harvard Medical School, Boston
  • Sean A Fletcher, Harvard Medical School, Boston
  • Philipp Gild, Hamburg University Hospital, Hamburg
  • Maxine Sun, Harvard Medical School, Boston
  • Stuart R Lipsitz, Harvard Medical School, Boston
  • H Abraham Chiang, Harvard Medical School, Boston
  • Adil H Haider, Brigham and Women's Hospital, Harvard Medical School, Boston
  • Mark A Preston, Harvard Medical School, Boston
Publication Date
7-1-2019
Document Type
Article
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

Citation Information
Alexander P Cole, Ashwin Ramaswamy, Sabrina Harmouch, Sean A Fletcher, et al.. "Multilevel analysis of readmissions after radical cystectomy for bladder cancer in the USA: Does the hospital make a difference?" European Urology Oncology Vol. 2 Iss. 4 (2019) p. 49 - 354
Available at: http://works.bepress.com/adil_haider/30/