title: Use of administrative claims data for identifying patients with cirrhosis.
abstract: BACKGROUND
  Administrative data are used in clinical research, but the validity of ICD-9 codes to identify cirrhotic patients has not been well established.
  
  
  OBJECTIVE
  To determine the diagnostic accuracy of ICD-9 codes for cirrhosis in clinical practice.
  
  
  METHODS
  We conducted a retrospective cohort study of patients from a safety-net hospital between 2008 and 2011. Patients were initially identified using ICD-9 codes for cirrhosis or a resultant complication. The gold-standard for diagnosis of cirrhosis was histology and/or imaging based on medical record review. Sensitivity, specificity, positive predictive values, and negative predictive values for each ICD-9 code were calculated. Diagnostic accuracy was assessed by the c-statistic using receiver operator characteristic curve analysis.
  
  
  RESULTS
  We identified 2893 patients with an ICD-9 code for cirrhosis, of whom 50.2% had 1 ICD-9 code, 20.3% had 2 different codes, and 29.5% had 3 or more codes. Cirrhosis was confirmed in 44.0% of patients with 1 ICD-9 code, 82.6% with 2 codes, and 95.7% of those with at least 3 codes. Ascites had a significantly lower positive predictive values for cirrhosis than other ICD-9 codes (P<0.001). The optimal combination of ICD-9 codes to identify cirrhotic patients included all codes except that of ascites, with a c-statistic of 0.71 in our derivation cohort. The sensitivity of this combination was confirmed to be 98% in a validation cohort of 285 patients with known cirrhosis.
  
  
  CONCLUSIONS
  Administrative data can identify patients with cirrhosis with high accuracy, although ascites has a significantly lower positive predictive value than other ICD-9 codes.
authors.affiliation: Department of Internal Medicine, UT Southwestern Medical Cente, Dallas, TX 75390-8887, USA.
authors.forename: Mahendra S
authors.initials: MS
authors.lastname: Nehra
authors.forename: Ying
authors.initials: Y
authors.lastname: Ma
authors.forename: Christopher
authors.initials: C
authors.lastname: Clark
authors.forename: Ruben
authors.initials: R
authors.lastname: Amarasingham
authors.forename: Don C
authors.initials: DC
authors.lastname: Rockey
authors.forename: Amit G
authors.initials: AG
authors.lastname: Singal
mesh_terms: D059019:Clinical Coding; D015331:Cohort Studies; D057286:Electronic Health Records; D005260:Female; D006801:Humans; D038801:International Classification of Diseases; D008103:Liver Cirrhosis / Q000175:diagnosis*; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D012372:ROC Curve; D012189:Retrospective Studies; D012680:Sensitivity and Specificity