Validating new coding algorithms to improve identification of alcohol-associated and nonalcohol-associated cirrhosis hospitalizations in administrative databases

Author:

Swain Liam A.1,Godley Jenny12,Brahmania Mayur3,Abraldes Juan G.4,Tang Karen L.15,Flemming Jennifer6,Shaheen Abdel Aziz13ORCID

Affiliation:

1. Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada

2. Department of Sociology, University of Calgary, Calgary, Alberta, Canada

3. Department of Medicine, Division of Gastroenterology and Hepatology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada

4. Liver Unit, Department of Medicine, Division of Gastroenterology, University of Alberta, Edmonton, Alberta, Canada

5. Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada

6. Department of Medicine and Public Health Sciences, Queen’s University, Kingston, Ontario, Canada

Abstract

Background: Alcohol (AC) and nonalcohol-associated cirrhosis (NAC) epidemiology studies are limited by available case definitions. We compared the diagnostic accuracy of previous and newly developed case definitions to identify AC and NAC hospitalizations. Methods: We randomly selected 700 hospitalizations from the 2008 to 2022 Canadian Discharge Abstract Database with alcohol-associated and cirrhosis-related International Classification of Diseases 10th revision codes. We compared standard approaches for AC (ie, AC code alone and alcohol use disorder and nonspecific cirrhosis codes together) and NAC (ie, NAC codes alone) case identification to newly developed approaches that combine standard approaches with new code combinations. Using electronic medical record review as the reference standard, we calculated case definition positive and negative predictive values, sensitivity, specificity, and AUROC. Results: Electronic medical records were available for 671 admissions; 252 had confirmed AC and 195 NAC. Compared to previous AC definitions, the newly developed algorithm selecting for the AC code, alcohol-associated hepatic failure code, or alcohol use disorder code with a decompensated cirrhosis-related condition or NAC code provided the best overall positive predictive value (91%, 95% CI: 87–95), negative predictive value (89%, CI: 86–92), sensitivity (81%, CI: 76–86), specificity (96%, CI: 93–97), and AUROC (0.88, CI: 0.85–0.91). Comparing all evaluated NAC definitions, high sensitivity (92%, CI: 87–95), specificity (82%, CI: 79–86), negative predictive value (96%, CI: 94–98), AUROC (0.87, CI: 0.84–0.90), but relatively low positive predictive value (68%, CI: 62–74) were obtained by excluding alcohol use disorder codes and using either a NAC code in any diagnostic position or a primary diagnostic code for HCC, unspecified/chronic hepatic failure, esophageal varices without bleeding, or hepatorenal syndrome. Conclusions: New case definitions show enhanced accuracy for identifying hospitalizations for AC and NAC compared to previously used approaches.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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