Validation of coding algorithms for the identification of patients hospitalized for alcoholic hepatitis using administrative data

Jack XQ Pang, Erin Ross, Meredith A. Borman, Scott Zimmer, Gilaad G. Kaplan, Steven J. Heitman, Mark G. Swain, Kelly W. Burak, Hude Quan, Robert P. Myers

Epidemiologic studies of alcoholic hepatitis (AH) have been hindered by the lack of a validated International Classification of Disease (ICD) coding algorithm for use with administrative data. Our objective was to validate coding algorithms for AH using a hospitalization database. The Hospital Discharge Abstract Database (DAD) was used to identify consecutive adults (≥18 years) hospitalized in the Calgary region with a diagnosis code for AH (ICD-10, K70.1) between 01/2008 and 08/2012. Medical records were reviewed to confirm the diagnosis of AH, defined as a history of heavy alcohol consumption, elevated AST and/or ALT (<300 U/L), serum bilirubin >34 μmol/L, and elevated INR. Subgroup analyses were performed according to the diagnosis field in which the code was recorded (primary vs. secondary) and AH severity. Algorithms that incorporated ICD-10 codes for cirrhosis and its complications were also examined. Of 228 potential AH cases, 122 patients had confirmed AH, corresponding to a positive predictive value (PPV) of 54 % (95 % CI 47-60 %). PPV improved when AH was the primary versus a secondary diagnosis (67 % vs. 21 %; P < 0.001). Algorithms that included diagnosis codes for ascites (PPV 75 %; 95 % CI 63-86 %), cirrhosis (PPV 60 %; 47-73 %), and gastrointestinal hemorrhage (PPV 62 %; 51-73 %) had improved performance, however, the prevalence of these diagnoses in confirmed AH cases was low (29-39 %). In conclusion the low PPV of the diagnosis code for AH suggests that caution is necessary if this hospitalization database is used in large-scale epidemiologic studies of this condition.