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


METHODS
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.


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.
Dexter
Franklin
F
Division of Management Consulting, Department of Anesthesia, University of Iowa, Iowa City, IA 52242, USA. Franklin-Dexter@UIowa.edu
Lubarsky
David A
DA
D000761:Anesthesia Department, Hospital / Q000191:economics / Q000458:organization & administration; D019985:Benchmarking; D016208:Databases, Factual / Q000706:statistics & numerical data*; D003953:Diagnosis-Related Groups; D017558:Elective Surgical Procedures / Q000191:economics / Q000706:statistics & numerical data*; D006784:Hospitals, Teaching / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay / Q000191:economics / Q000706:statistics & numerical data*; D006278:Medicare / Q000706:statistics & numerical data