An intranet-based automated system for the surveillance of nosocomial infections: prospective validation compared with physicians' self-reports.
OBJECTIVE
To examine the reliability of the data produced by an automated system for the surveillance of nosocomial infections.


METHODS
A 906-bed, tertiary-care teaching hospital.


METHODS
Three surveillance techniques were concurrently performed in seven high-risk units during an 11-week period: automated surveillance (AS) based on the prospective processing of computerized medical records; laboratory-based ward surveillance (LBWS) based on the retrospective verification by ward clinicians of weekly reports of positive bacteriologic results; and a reference standard (RS) consisting of the infection control team reviewing case records of patients with positive bacteriology results. Bacteremia, urinary tract infections, and catheter-related infections were recorded for all inpatients. The performances (sensitivity, specificity, and time consumption) of AS and LBWS were compared with those of RS.


RESULTS
Of 548 positive bacteriology samples included during the study period, 229 (42%) were classified as nosocomial infections. The overall sensitivity was 91% and 59% for AS and LBWS, respectively. The two methods had the same overall specificity value (91%). Kappa measures of agreement were 0.81 and 0.54 for AS and LBWS, respectively. AS required less time to collect data (54 seconds per week per unit) compared with LBWS (7 minutes and 43 seconds per week per unit) and RS (37 minutes and 15 seconds per week per unit).


CONCLUSIONS
Our results confirm that the retrospective review of charts and laboratory data by physicians lacks sensitivity for the surveillance of nosocomial infections. The intranet-based automated method developed for this purpose was more accurate and less time-consuming than the weekly, retrospective LBWS method.
Bouam
Samir
S
Département de Biostatistiques et d'Information Hospitalier, Hôpital Henri Mondor, Assistance Publique-Hôpitaux de Paris, Créteil, France.
Girou
Emmanuelle
E
Brun-Buisson
Christian
C
Karadimas
Harry
H
Lepage
Eric
E
D001331:Automation; D003428:Cross Infection / Q000453:epidemiology*; D006751:Hospital Information Systems; D006784:Hospitals, Teaching / Q000706:statistics & numerical data; D006801:Humans; D008485:Medical Audit; D008499:Medical Records / Q000592:standards* / Q000706:statistics & numerical data; D010820:Physicians; D011159:Population Surveillance; D011446:Prospective Studies; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D014342:Truth Disclosure