title: Coding algorithms for identifying patients with cirrhosis and hepatitis B or C virus using administrative data.
abstract: OBJECTIVE
  Despite the use of administrative data to perform epidemiological and cost-effectiveness research on patients with hepatitis B or C virus (HBV, HCV), there are no data outside of the Veterans Health Administration validating whether International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) codes can accurately identify cirrhotic patients with HBV or HCV. The validation of such algorithms is necessary for future epidemiological studies.
  
  
  METHODS
  We evaluated the positive predictive value (PPV) of ICD-9-CM codes for identifying chronic HBV or HCV among cirrhotic patients within the University of Pennsylvania Health System, a large network that includes a tertiary care referral center, a community-based hospital, and multiple outpatient practices across southeastern Pennsylvania and southern New Jersey. We reviewed a random sample of 200 cirrhotic patients with ICD-9-CM codes for HCV and 150 cirrhotic patients with ICD-9-CM codes for HBV.
  
  
  RESULTS
  The PPV of 1 inpatient or 2 outpatient HCV codes was 88.0% (168/191, 95% CI: 82.5-92.2%), while the PPV of 1 inpatient or 2 outpatient HBV codes was 81.3% (113/139, 95% CI: 73.8-87.4%). Several variations of the primary coding algorithm were evaluated to determine if different combinations of inpatient and/or outpatient ICD-9-CM codes could increase the PPV of the coding algorithm.
  
  
  CONCLUSIONS
  ICD-9-CM codes can identify chronic HBV or HCV in cirrhotic patients with a high PPV and can be used in future epidemiologic studies to examine disease burden and the proper allocation of resources.
authors.affiliation: Department of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
authors.forename: Bolin
authors.initials: B
authors.lastname: Niu
authors.forename: Kimberly A
authors.initials: KA
authors.lastname: Forde
authors.forename: David S
authors.initials: DS
authors.lastname: Goldberg
mesh_terms: D000465:Algorithms; D059019:Clinical Coding / Q000592:standards* / Q000706:statistics & numerical data; D016208:Databases, Factual / Q000592:standards / Q000706:statistics & numerical data; D005260:Female; D006308:Health Systems Plans / Q000592:standards / Q000706:statistics & numerical data; D006509:Hepatitis B / Q000175:diagnosis / Q000453:epidemiology*; D006526:Hepatitis C / Q000175:diagnosis / Q000453:epidemiology*; D006801:Humans; D038801:International Classification of Diseases / Q000592:standards* / Q000706:statistics & numerical data; D008103:Liver Cirrhosis / Q000175:diagnosis / Q000453:epidemiology*; D008297:Male; D008875:Middle Aged; D012189:Retrospective Studies
keywords: administrative data; hepatitis B virus; hepatitis C virus; pharmacoepidemiology; validation