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

Background: 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.

Methods: 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.

Results: 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%).

Conclusions: 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.