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Quality Assessment of Hospital Discharge Database for Routine Surveillance of Hip and Knee Arthroplasty–Related Infections

Published online by Cambridge University Press:  10 May 2016

Leslie Grammatico-Guillon ,
Sabine Baron ,
Christophe Gaborit ,
Emmanuel Rusch  and
Pascal Astagneau
Leslie Grammatico-Guillon*
Affiliation:
Université Pierre et Marie Curie, Paris, France Service d’Information Médicale, d’Epidémiologie et d’Economie de la Santé, Centre Hospitalière Régionale Universitaire (CHRU) de Tours, Tours, France Equipe Emergente 1 Education Ethique Santé, Université François Rabelais, Tours, France Unité Régionale d’Épidémiologie Hospitalière, CHRU de Tours, France
Sabine Baron
Affiliation:
Equipe Emergente 1 Education Ethique Santé, Université François Rabelais, Tours, France Unité Régionale d’Épidémiologie Hospitalière, CHRU de Tours, France
Christophe Gaborit
Affiliation:
Equipe Emergente 1 Education Ethique Santé, Université François Rabelais, Tours, France Unité Régionale d’Épidémiologie Hospitalière, CHRU de Tours, France
Emmanuel Rusch
Affiliation:
Service d’Information Médicale, d’Epidémiologie et d’Economie de la Santé, Centre Hospitalière Régionale Universitaire (CHRU) de Tours, Tours, France Equipe Emergente 1 Education Ethique Santé, Université François Rabelais, Tours, France Unité Régionale d’Épidémiologie Hospitalière, CHRU de Tours, France
Pascal Astagneau
Affiliation:
Ecole des Hautes Etudes en Santé Publique Université Sorbonne Paris Cité, Paris, France Centre de Coordination pour la Lutte Contre les Infections Associées aux Soins, Paris, France
*
SIMEES, CHRU de Tours, Hôpital Bretonneau, 2 BD Tonnellé 37000, Tours, France ([email protected]).
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Abstract

Objective.

Surgical site infection (SSI) surveillance represents a key method of nosocomial infection control programs worldwide. However, most SSI surveillance systems are considered to be poorly cost effective regarding human and economic resources required for data collection and patient follow up. This study aims to assess the efficacy of using hospital discharge databases (HDDs) as a routine surveillance system for detecting hip or knee arthroplasty–related infections (HKAIs).

Methods.

A case-control study was conducted among patients hospitalized in the Centre region of France between 2008 and 2010. HKAI cases were extracted from the HDD with various algorithms based on the International Classification of Diseases, Tenth Revision, and procedure codes. The control subjects were patients with hip or knee arthroplasty (HKA) without infection selected at random from the HDD during the study period. The gold standard was medical chart review. Sensitivity (Se), specificity (Spe), positive predictive value (PPV), and negative predictive value (NPV) were calculated to evaluate the efficacy of the surveillance system.

Results.

Among 18,265 hospital stays for HKA, corresponding to 17,388 patients, medical reports were checked for 1,010 hospital stays (989 patients). We identified 530 cases in total (incidence rate, 1% [95% confidence interval (CI), 0.4%–1.6%), and 333 cases were detected by routine surveillance. As compared with 480 controls, Se was 98%, Spe was 71%, PPV was 63%, and NPV was 99%. Using a more specific case definition, based on a sample of 681 hospital stays, Se was 97%, Spe was 95%, PPV was 87%, and NPV was 98%.

Conclusions.

This study demonstrates the potential of HDD as a tool for routine SSI surveillance after low-risk surgery, under conditions of having an appropriate algorithm for selecting infections.

Infect Control Hosp Epidemiol 2014;35(6):646–651

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 35 , Issue 6 , 01 June 2014 , pp. 646 - 651
Copyright
© 2014 by The Society for Healthcare Epidemiology of America. All rights reserved.

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