Use of electronic health record data to identify skin and soft tissue infections in primary care settings: a validation study

BACKGROUND: Epidemiologic studies of skin and soft tissue infections (SSTIs) depend upon accurate case identification. Our objective was to evaluate the positive predictive value (PPV) of electronic medical record data for identification of SSTIs in a primary care setting. METHODS: A validation study was conducted among primary care outpatients in an academic healthcare system. Encounters during four non-consecutive months in 2010 were included if any of the following were present in the electronic health record: International Classification of Diseases, Ninth Revision (ICD-9) code for an SSTI, Current Procedural Terminology (CPT) code for incision and drainage, or a positive wound culture. Detailed chart review was performed to establish presence and type of SSTI. PPVs and 95% confidence intervals (CI) were calculated among all encounters, initial encounters, and cellulitis/abscess cases. RESULTS: Of the 731 encounters included, 514 (70.3%) were initial encounters and 448 (61.3%) were cellulitis/abscess cases. When the presence of an ICD-9 code, CPT code, or positive culture was used to identify SSTIs, 617 encounters were true positives, yielding a PPV of 84.4% [95% CI: 81.8–87.0%]. The PPV for using ICD-9 codes alone to identify SSTIs was 90.7% [95 % CI: 88.5–92.9%]. For encounters with cellulitis/abscess codes, the PPV was 91.5% [95% CI: 88.9–94.1%]. CONCLUSIONS: ICD-9 codes may be used to retrospectively identify SSTIs with a high PPV. Broadening SSTI case identification with microbiology data and CPT codes attenuates the PPV. Further work is needed to estimate the sensitivity of this method.