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Bayesian estimation of the accuracy of ICD-9-CM- and CPT-4-based algorithms to identify cholecystectomy procedures in administrative data without a reference standard
  • Published Date:
    Sep 09 2015
  • Source:
    Pharmacoepidemiol Drug Saf. 25(3):263-268.


Public Access Version Available on: March 01, 2017 information icon
Please check back on the date listed above.
Details:
  • Pubmed ID:
    26349484
  • Pubmed Central ID:
    PMC4775358
  • Funding:
    FOA# CK11-001/CK/NCEZID CDC HHS/United States
    U54 CK000162/CK/NCEZID CDC HHS/United States
    U54 CK000162/CK/NCEZID CDC HHS/United States
  • Document Type:
  • Collection(s):
  • Description:
    Purpose

    To estimate the accuracy of two algorithms to identify cholecystectomy procedures using International Classification of Diseases, 9th Edition, Clinical Modification (ICD-9-CM) and Current Procedural Terminology (CPT-4) codes in administrative data.

    Methods

    Private insurer medical claims for 30,853 patients 18–64 years with an inpatient hospitalization between 2006 and 2010, as indicated by providers/facilities place of service in addition to room and board charges, were cross-classified according to the presence of codes for cholecystectomy. The accuracy of ICD-9-CM- and CPT-4-based algorithms was estimated using a Bayesian latent class model.

    Results

    The sensitivity and specificity were 0.92 [probability interval (PI): 0.92, 0.92] and 0.99 (PI: 0.97, 0.99) for ICD-9-CM-, and 0.93 (PI: 0.92, 0.93) and 0.99 (PI: 0.97, 0.99) for CPT-4-based algorithms, respectively. The parallel-joint scheme, where positivity of either algorithm was considered a positive outcome, yielded a sensitivity and specificity of 0.99 (PI: 0.99, 0.99) and 0.97 (PI: 0.95, 0.99), respectively.

    Conclusions

    Both ICD-9-CM- and CPT-4-based algorithms had high sensitivity to identify cholecystectomy procedures in administrative data when used individually and especially in a parallel-joint approach.

  • Supporting Files:
    No Additional Files