Using length of stay data from a hospital to evaluate whether limiting elective surgery at the hospital is an inappropriate decision

J Clin Anesth. 2004 Sep;16(6):421-5. doi: 10.1016/j.jclinane.2003.11.003.

Abstract

Study objective: At hospitals without detailed managerial accounting data but with overall longer than average diagnosis-related groups (DRG)-adjusted lengths of stays (LOS), some administrators do not aggressively hire the nurses needed to maintain surgical hospital capacity. The consequence of this (long-term) decision is that day-of-surgery admit cases are delayed or cancelled from a lack of beds. The anesthesiologists suffer financially. In this paper, we show how publicly released national LOS data can be applied specifically to these cases.

Design: We applied the method to 1 year of data from two academic hospitals. Each case's LOS was compared to the United States national average LOS for cases with the same DRG.

Measurements and main results: A total of 8,050 and 10,099 hospitalizations, respectively. Among all surgical admissions, mean LOS was 2.5 days longer than the national average for Hospital #1 (95% confidence interval [CI], 2.1 to 2.8) and 3.1 days longer for Hospital #2 (95% CI, 2.8 to 3.4). Among patients undergoing elective, scheduled surgery with day of surgery admission, mean LOS was 0.7 days less than average for Hospital #1 (0.6 to 0.9) and 1.2 days less than average for Hospital #2 (1.1 to 1.4).

Conclusions: This method can be used by anesthesiologists to show that LOS are not longer than average among patients whose surgeries may be cancelled or delayed for a lack of hospital ward staff.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Anesthesia Department, Hospital / economics
  • Anesthesia Department, Hospital / organization & administration
  • Benchmarking
  • Databases, Factual / statistics & numerical data*
  • Diagnosis-Related Groups
  • Elective Surgical Procedures / economics
  • Elective Surgical Procedures / statistics & numerical data*
  • Hospitals, Teaching / statistics & numerical data*
  • Humans
  • Length of Stay / economics
  • Length of Stay / statistics & numerical data*
  • Medicare / statistics & numerical data