{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T03:24:30Z","timestamp":1787282670715,"version":"build-2736575974"},"reference-count":19,"publisher":"Hindawi Limited","license":[{"start":{"date-parts":[[2011,1,1]],"date-time":"2011-01-01T00:00:00Z","timestamp":1293840000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Infectious Diseases in Obstetrics and Gynecology"],"published-print":{"date-parts":[[2011]]},"abstract":"<jats:p>ICD-9 codes are conventionally used to identify pelvic inflammatory disease (PID) from administrative data for surveillance purposes. This approach may include non-PID cases. To refine PID case identification among women with ICD-9 codes suggestive of PID, a case-finding algorithm was developed using additional variables. Potential PID cases were identified among women aged 15\u201344 years at Group Health (GH) and Kaiser Permanente Colorado (KPCO) and verified by medical record review. A classification and regression tree analysis was used to develop the algorithm at GH; validation occurred at KPCO. The positive predictive value (PPV) for using ICD-9 codes alone to identify clinical PID cases was 79%. The algorithm identified PID appropriate treatment and age 15\u201325 years as predictors. Algorithm sensitivity (<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><mml:mrow><mml:mtext>GH<\/mml:mtext><mml:mo>=<\/mml:mo><mml:mn>96.4<\/mml:mn><\/mml:mrow><\/mml:math>%;<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><mml:mrow><mml:mtext>KPCO<\/mml:mtext><mml:mo>=<\/mml:mo><mml:mn>90.3<\/mml:mn><\/mml:mrow><\/mml:math>%) and PPV (<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><mml:mrow><mml:mtext>GH<\/mml:mtext><mml:mo>=<\/mml:mo><mml:mn>86.9<\/mml:mn><\/mml:mrow><\/mml:math>%;<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><mml:mrow><mml:mtext>KPCO<\/mml:mtext><mml:mo>=<\/mml:mo><mml:mn>84.5<\/mml:mn><\/mml:mrow><\/mml:math>%) were high, but specificity was poor (<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><mml:mrow><mml:mtext>GH<\/mml:mtext><mml:mo>=<\/mml:mo><mml:mn>45.9<\/mml:mn><\/mml:mrow><\/mml:math>%;<mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><mml:mrow><mml:mtext>KPCO<\/mml:mtext><mml:mo>=<\/mml:mo><mml:mn>37.0<\/mml:mn><\/mml:mrow><\/mml:math>%). In GH, the algorithm offered a practical alternative to medical record review to further improve PID case identification.<\/jats:p>","DOI":"10.1155\/2011\/428351","type":"journal-article","created":{"date-parts":[[2011,11,14]],"date-time":"2011-11-14T14:03:29Z","timestamp":1321279409000},"page":"1-7","source":"Crossref","is-referenced-by-count":11,"title":["Detection of Pelvic Inflammatory Disease: Development of an Automated Case-Finding Algorithm Using Administrative Data"],"prefix":"10.1155","volume":"2011","author":[{"given":"Catherine L.","family":"Satterwhite","sequence":"first","affiliation":[{"name":"Division of STD Prevention, Centers for Disease Control and Prevention, 1600 Clifton Road, Mailstop E-02, Atlanta, GA 30333, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Onchee","family":"Yu","sequence":"additional","affiliation":[{"name":"Group Health Research Institute, Group Health Cooperative, Seattle, WA 98101, 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