Highly sensitive and efficient computer-assisted system for routine surveillance for surgical site infection.
OBJECTIVE
Surveillance of surgical site infections (SSIs) is effective in reducing the rates of these complications, but it is extremely time-consuming and, consequently, underused. We determined the sensitivity and specificity of a computer-assisted surveillance system, compared with a conventional method involving review of medical records, and the time saved with the computer-assisted system.


METHODS
A prospective study was conducted from January 1 to December 31, 2001. With the computer-assisted method, screening for SSIs relied on identification in the laboratory database of positive results of microbiological tests of surgical-site specimens; confirmation was obtained via computer-generated questionnaires completed by the surgeon in charge of the patient. In the conventional method, SSIs were identified by exhaustive chart review. The time spent on surveillance was recorded for both methods.


METHODS
A 25-bed gastrointestinal surgery unit in a tertiary care hospital.


METHODS
A total of 766 consecutive patients who underwent gastrointestinal surgery.


RESULTS
The sensitivity of the computer-assisted method was 84.3% (95% confidence interval, 0.66-0.94); the specificity was 99.9%. For the 807 surgical procedures in the study, 197 had an SSI identified by culture of a surgical-site specimen. After elimination of 63 duplicate cultures with positive results, 134 questionnaires were sent to the surgeons, who confirmed 27 SSIs. The conventional method identified 32 SSIs. The computer-assisted method required 60% less time than the conventional method (90 hours vs 223 hours).


CONCLUSIONS
Surveillance for SSIs using computer-assisted, laboratory-based screening and case confirmation by surgeons is as efficient as and far less time-consuming than the conventional method of chart review. This method permits routine surveillance for SSIs with reliable accuracy.
Chalfine
Annie
A
Infection Control Unit, Saint-Joseph Hospital, Paris, France. achalfine@hopital-saint-joseph.org
Cauet
Daniel
D
Lin
Wei Chi
WC
Gonot
Jacqueline
J
Calvo-Verjat
Nadine
N
Dazza
François-Emile
FE
Billuart
Olivier
O
Kitzis
Marie Dominique
MD
Blériot
Jean Pierre
JP
Pibarot
Marie Laure
ML
Carlet
Jean
J
D003199:Computer Systems / Q000706:statistics & numerical data*; D003625:Data Collection / Q000379:methods*; D006801:Humans; D011159:Population Surveillance / Q000379:methods*; D011446:Prospective Studies; D012680:Sensitivity and Specificity; D013530:Surgical Wound Infection / Q000453:epidemiology* / Q000382:microbiology; D011795:Surveys and Questionnaires; D014947:Wounds and Injuries / Q000382:microbiology