JOURNAL ARTICLE
RESEARCH SUPPORT, U.S. GOV'T, P.H.S.
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Use of Medicare diagnosis and procedure codes to improve detection of surgical site infections following hip arthroplasty, knee arthroplasty, and vascular surgery.

OBJECTIVE: To evaluate the use of routinely collected electronic health data in Medicare claims to identify surgical site infections (SSIs) following hip arthroplasty, knee arthroplasty, and vascular surgery.

DESIGN: Retrospective cohort study.

SETTING: Four academic hospitals that perform prospective SSI surveillance.

METHODS: We developed lists of International Classification of Diseases, Ninth Revision, and Current Procedural Terminology diagnosis and procedure codes to identify potential SSIs. We then screened for these codes in Medicare claims submitted by each hospital on patients older than 65 years of age who had undergone 1 of the study procedures during 2007. Each site reviewed medical records of patients identified by either claims codes or traditional infection control surveillance to confirm SSI using Centers for Disease Control and Prevention/National Healthcare Safety Network criteria. We assessed the performance of both methods against all chart-confirmed SSIs identified by either method.

RESULTS: Claims-based surveillance detected 1.8-4.7-fold more SSIs than traditional surveillance, including detection of all previously identified cases. For hip and vascular surgery, there was a 5-fold and 1.6-fold increase in detection of deep and organ/space infections, respectively, with no increased detection of deep and organ/space infections following knee surgery. Use of claims to trigger chart review led to confirmation of SSI in 1 out of 3 charts for hip arthroplasty, 1 out of 5 charts for knee arthroplasty, and 1 out of 2 charts for vascular surgery.

CONCLUSION: Claims-based SSI surveillance markedly increased the number of SSIs detected following hip arthroplasty, knee arthroplasty, and vascular surgery. It deserves consideration as a more effective approach to target chart reviews for identifying SSIs.

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