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Detection of Pelvic Inflammatory Disease: Development of an Automated Case-Finding Algorithm Using Administrative Data ; Infect Dis Obstet Gynecol

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  • معلومة اضافية
    • Contributors:
      Satterwhite, Catherine L.; Yu, Onchee; Raebel, Marsha A.; Berman, Stuart; Howards, Penelope P.; Weinstock, Hillard; Kleinbaum, David; Scholes, Delia
    • Collection:
      CDC Stacks (Centers for Disease Control and Prevention)
    • نبذة مختصرة :
      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.
    • Relation:
      https://stacks.cdc.gov/view/cdc/4003
    • الدخول الالكتروني :
      https://stacks.cdc.gov/view/cdc/4003
    • الرقم المعرف:
      edsbas.A588CE80