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Accounting for Incomplete Postdischarge Follow-Up During Surveillance of Surgical Site Infection by Use of the National Nosocomial Infections Surveillance System's Risk Index

Published online by Cambridge University Press:  02 January 2015

Fernando Martín Biscione*
Affiliation:
Health Sciences Postgraduate Course, Medicine High School, Federal University of Minas Gerais, Santa Efigênia, Belo Horizonte, Minas Gerais, Brazil
Renato Camargos Couto
Affiliation:
Health Sciences Postgraduate Course, Medicine High School, Federal University of Minas Gerais, Santa Efigênia, Belo Horizonte, Minas Gerais, Brazil
Tânia M. G. Pedrosa
Affiliation:
Health Sciences Postgraduate Course, Medicine High School, Federal University of Minas Gerais, Santa Efigênia, Belo Horizonte, Minas Gerais, Brazil
*
Health Sciences Postgraduate Course, Medicine High School, Minas Gerais, 190 Alfredo Balena Avenue, Room 7003, Santa Efigênia, Belo Horizonte, Federal University of Minas Gerais, 30-130-100, Brazil ([email protected])

Abstract

Objective.

We examined the usefulness of a simple method to account for incomplete postdischarge follow-up during surveillance of surgical site infection (SSI) by use of the National Nosocomial Infections Surveillance (NNIS) system's risk index.

Design.

Retrospective cohort study that used data prospectively collected from 1993 through 2006.

Setting.

Five private, nonuniversity healthcare facilities in Belo Horizonte, Brazil.

Patients.

Consecutive patients undergoing the following NNIS operative procedures: 20,981 operations on the genitourinary system, 11,930 abdominal hysterectomies, 7,696 herniorraphies, 6,002 cholecystectomies, and 6,892 laparotomies.

Methods.

For each operative procedure category, 2 SSI risk models were specified. First, a model based on the NNIS system's risk index variables was specified (hereafter referred to as the NNIS-based model). Second, a modified model (hereafter referred to as the modified NNIS-based model), which was also based on the NNIS system's risk index, was specified with a postdischarge surveillance indicator, which was assigned the value of 1 if the patient could be reached during follow-up and a value of 0 if the patient could not be reached. A formal comparison of the capabilities of the 2 models to assess the risk of SSI was conducted using measures of calibration (by use of the Pearson goodness-of-fit test) and discrimination (by use of receiver operating characteristic curves). Goodman-Kruskal correlations (G) were also calculated.

Results.

The rate of incomplete postdischarge follow-up varied between 29.8% for abdominal hysterectomies and 50.5% for cholecystectomies. The modified NNIS-based model for laparotomy did not show any significant benefit over the NNIS-based model in any measure. For all other operative procedures, the modified NNIS-based model showed a significantly improved discriminatory ability and higher G statistics, compared with the NNIS-based model, with no significant impairment in calibration, except if used to assess the risk of SSI after operations on the genitourinary system or after a cholecystectomy.

Conclusions.

Compared with the NNIS-based model, the modified NNIS-based model added potentially useful clinical information regarding most of the operative procedures. Further work is warranted to evaluate this method for accounting for incomplete postdischarge follow-up during surveillance of SSI.

Type
Original Articles
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2009

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