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Excess Length of Stay Attributable to Surgical Site Infection Following Hip Replacement: A Nested Case-Control Study

Published online by Cambridge University Press:  21 June 2016

Vicente Monge Jodra*
Affiliation:
Servicio de Medicina Preventiva, Hospital Ramón y Cajal, Madrid, Spain
Lourdes Sainz de los Terreros Soler
Affiliation:
Servicio de Medicina Preventiva, Hospital Ramón y Cajal, Madrid, Spain
Cristina Díaz-Agero Pérez
Affiliation:
Servicio de Medicina Preventiva, Hospital Ramón y Cajal, Madrid, Spain
Carmen María Saa Requejo
Affiliation:
Servicio de Medicina Preventiva, Hospital Ramón y Cajal, Madrid, Spain
Nieves Plana Farrás
Affiliation:
Servicio de Medicina Preventiva, Hospital Ramón y Cajal, Madrid, Spain
*
Servicio de Medicina Preventiva, Hospital Ramón y Cajal, Carretera de Colmenar km 9, 1, Madrid 28034, Spain ([email protected])

Abstract

Objective.

We estimated the impact of hip replacement-associated surgical site infection (SSI) on morbidity and length of stay.

Methods.

This was a pairwise matched (1 : 1) case-control study nested in a cohort. All patients who underwent hip replacement from January 1, 2000, to June 30, 2004, were prospectively enrolled for the nested case-control design analysis and were monitored from the time of surgery until hospital discharge, including any patients readmitted because of infection.

Results.

Among the 1,260 hip replacements performed, 28 SSIs were detected, yielding a crude SSI rate of 2.2%. The median excess length of stay attributable to SSI was 32.5 days (P< .001), whereas the median prolonged postoperative stay due to SSI was 31 days (P< .001). Deep-wound SSI was the type that prolonged hospital stay the most (up to 49 days). Of the patients who developed an SSI, 4 required revision surgery, for an SSI-related morbidity rate of 14.3%.

Conclusion.

SSI prolongs hospital stay; however, although hospital stay is a rough indicator of the cost of this complication, to accurately estimate the costs of SSI, we would need to consider individual costs in a linear regression model adjusted for all possible confounding factors.

Type
Original Articles
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2006

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