Leveraging Electronic Data for TJR SSI Surveillance

Article

Maria C. S. Inacio, MS, of the Surgical Outcomes and Analysis Unit of Clinical Analysis at Kaiser Permanente in San Diego, and colleagues, endeavored 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 surgical site infection (SSI) is sensitive and specific for SSI detection and reduces chart review volume for SSI surveillance.

For this validation study conducted in a health maintenance organization (HMO) with 8.6 million members, the researchers screened each TJR procedure performed between January 2006 and December 2008 for possible infections, 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. The researchers report that 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 the HMO. Positive predictive values (PPVs), negative predictive values (NPVs), and specificity and sensitivity values were calculated, and absolute reduction of chart review volume was evaluated.

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

Inacio, et al. report that 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, and that the algorithm successfully reduced the volume of chart review for surveillance by 90.5 percent. Their research was published in Infection Control & Hospital Epidemiology.

Reference: Inacio MCS, Paxton EW, Chen Y, Harris J, Eck E, Barnes S, Namba RS and Ake CF. Leveraging Electronic Medical Records for Surveillance of Surgical Site Infection in a Total Joint Replacement Population. Infection Control & Hospital Epidemiology. Vol. 32, No. 4, April 2011.

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