Detection of Pelvic Inflammatory Disease: Development of an Automated Case-Finding Algorithm Using Administrative Data - Catherine L. Satterwhite; Onchee Yu; Marsha A. Raebel; Stuart Berman; Penelope P. Howards; Hillard Weinstock; David Kleinbaum; Delia Scholes (Hindawi Limited, 2011)
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 15-44 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 15-25 years as predictors. Algorithm sensitivity (GH=96.4%; KPCO=90.3%) and PPV (GH=86.9%; KPCO=84.5%) were high, but specificity was poor (GH=45.9%; KPCO=37.0%). In GH, the algorithm offered a practical alternative to medical record review to further improve PID case identification.