METHOD FOR SEPARATING PATIENT AND PROCEDURAL FACTORS WHILE ANALYZING INTERDEPARTMENTAL DIFFERENCES IN RATES OF SURGICAL INFECTIONS - THE ISRAELI STUDY OF SURGICAL INFECTION IN ABDOMINAL OPERATIONS

Citation
E. Simchen et al., METHOD FOR SEPARATING PATIENT AND PROCEDURAL FACTORS WHILE ANALYZING INTERDEPARTMENTAL DIFFERENCES IN RATES OF SURGICAL INFECTIONS - THE ISRAELI STUDY OF SURGICAL INFECTION IN ABDOMINAL OPERATIONS, Journal of clinical epidemiology, 49(9), 1996, pp. 1003-1007
Citations number
11
Categorie Soggetti
Public, Environmental & Occupation Heath","Medicine, General & Internal
ISSN journal
08954356
Volume
49
Issue
9
Year of publication
1996
Pages
1003 - 1007
Database
ISI
SICI code
0895-4356(1996)49:9<1003:MFSPAP>2.0.ZU;2-U
Abstract
The objective of this study was to develop a method for analyzing diff erences in the performance of hospitals with respect to outcome by sep arating patient factors from procedural factors. The setting included a prospective follow-up of a sample of 5571 patients undergoing all ty pes of surgical procedures in general surgery departments of 11 hospit als (20 surgical departments) across Israel. Of these, 769 underwent s urgery involving the opening of the bowel, and they are the subjects o f this report. Our method consisted of a prospective follow-up by a nu rse epidemiologist, including detailed clinical data from the day of a dmission to hospital discharge. Analysis was directed at identifying r easons for the observed variability in wound infections among departme nts. Observed rates were compared with ''expected'' rates calculated f rom a logistic model pooled over departments. An attempt was made to s eparate patient-inherent characteristics, such as age, sex, and diagno sis, from procedural factors, depicting the patient's experience durin g his hospitalization. Results indicated that the marked interdepartme ntal differences in the observed infection rates were not accounted fo r by differences in the ''case mix'' among departments. Procedural ris k factors in this data set played the main role in explaining the obse rved variability among surgical departments. We conclude that the simp le method presented here used the data pooled over departments to defi ne the main risk determinants for infection in this data set, It separ ated intrinsic patient factors from procedural characteristics, and co uld be used in studies where the main interest is to compare instituti ons, and point at reasons behind the differences in outcomes.