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Leveraging Electronic Medical Records for Surveillance of Surgical Site Infection in a Total Joint Replacement Population

Part of: BARRY FARR AWARD RECIPIENTS

Published online by Cambridge University Press:  02 January 2015

Maria C. S. Inacio ,
Elizabeth W. Paxton ,
Yuexin Chen ,
Jessica Harris ,
Enid Eck ,
Sue Barnes ,
Robert S. Namba  and
Christopher F. Ake
Maria C. S. Inacio*
Affiliation:
Surgical Outcomes and Analysis Unit of Clinical Analysis, Kaiser Permanente, San Diego, California 92109
Elizabeth W. Paxton
Affiliation:
Surgical Outcomes and Analysis Unit of Clinical Analysis, Kaiser Permanente, San Diego, California 92109
Yuexin Chen
Affiliation:
Surgical Outcomes and Analysis Unit of Clinical Analysis, Kaiser Permanente, San Diego, California 92109
Jessica Harris
Affiliation:
Surgical Outcomes and Analysis Unit of Clinical Analysis, Kaiser Permanente, San Diego, California 92109
Enid Eck
Affiliation:
Quality and Risk Management, Infection Prevention and Control Department, Kaiser Permanente, Pasadena, California 91188
Sue Barnes
Affiliation:
Program Offices, Infection Prevention and Control Department, Kaiser Permanente, Oakland, California 94612
Robert S. Namba
Affiliation:
Department of Orthopedics, Kaiser Permanente Orange County, Irvine, California 92618
Christopher F. Ake
Affiliation:
Surgical Outcomes and Analysis Unit of Clinical Analysis, Kaiser Permanente, San Diego, California 92109
*
Surgical Outcomes and Analysis Unit of Clinical Analysis, Kaiser Permanente, 3033 Bunker Hill Street, San Diego, California 92109 ([email protected])
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Abstract

Objective.

TO evaluate whether a hybrid electronic screening algorithm using a total joint replacement (TJR) registry, electronic surgical site infection (SSI) screening, and electronic health record (EHR) review of SSI is sensitive and specific for SSI detection and reduces chart review volume for SSI surveillance.

Design.

Validation study.

Setting.

A large health maintenance organization (HMO) with 8.6 million members.

Methods.

Using codes for infection, wound complications, cellullitis, procedures related to infections, and surgeon-reported complications from the International Classification of Diseases, Ninth Revision, Clinical Modification, we screened each TJR procedure performed in our HMO between January 2006 and December 2008 for possible infections. Flagged charts were reviewed by clinical-content experts to confirm SSIs. SSIs identified by the electronic screening algorithm were compared with SSIs identified by the traditional indirect surveillance methodology currently employed in our HMO. Positive predictive values (PPVs), negative predictive values (NPVs), and specificity and sensitivity values were calculated. Absolute reduction of chart review volume was evaluated.

Results.

The algorithm identified 4,001 possible SSIs (9.5%) for the 42,173 procedures performed for our TJR patient population. A total of 440 case patients (1.04%) had SSIs (PPV, 11.0%; NPV, 100.0%). The sensitivity and specificity of the overall algorithm were 97.8% and 91.5%, respectively.

Conclusion.

An electronic screening algorithm combined with an electronic health record review of flagged cases can be used as a valid source for TJR SSI surveillance. The algorithm successfully reduced the volume of chart review for surveillance by 90.5%.

Type
Original Article
Information
Infection Control & Hospital Epidemiology , Volume 32 , Issue 4 , April 2011 , pp. 351 - 359
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2011

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