The association between hospital volume and total shoulder arthroplasty outcomes

Clin Orthop Relat Res. 2005 Mar:(432):132-7. doi: 10.1097/01.blo.0000150571.51381.9a.

Abstract

The purpose of this study was to evaluate the relationship between increasing hospital volume and the following outcomes for total shoulder arthroplasties done in the state of New York: length of stay, hospital costs, readmission within 60 days, revision surgery within 24 months, and death within 60 days. The Statewide Planning and Research Cooperative System (SPARCS) database from the New York State Department of Health, a census of all hospital discharges in the state, was used to evaluate the relationship between hospital volume and outcomes for total shoulder arthroplasties for 1996 to 1999. One thousand three hundred seven total shoulder arthroplasties were done in New York from 1996 to 1999. Nearly (1/2) were done at the five highest-volume hospitals. Middle-volume hospitals has the least lengths of stay and hospital costs. Independent of age and comorbidities, patients at hospitals with greater volumes of total shoulder arthroplasties were at reduced risk of patients being readmitted within 60 days. No other outcomes were significantly associated with hospital volume. The finding that greater hospital volume decreases risk of readmission may have important public health implications, but additional research is needed before implementing policy changes.

Publication types

  • Evaluation Study

MeSH terms

  • Age Distribution
  • Aged
  • Aged, 80 and over
  • Arthroplasty / statistics & numerical data*
  • Female
  • Hospital Costs / statistics & numerical data
  • Hospitalization / statistics & numerical data*
  • Humans
  • Length of Stay / statistics & numerical data
  • Male
  • Models, Statistical
  • New York
  • Outcome Assessment, Health Care
  • Patient Readmission / statistics & numerical data
  • Reoperation / statistics & numerical data
  • Shoulder Joint / surgery*
  • Surgery Department, Hospital / statistics & numerical data*
  • Survival Analysis