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Validating a novel algorithm to identify patients with autoimmune hepatitis in an administrative database.

Therese Bittermann1,2, Nadim Mahmud1,2, James D Lewis1,2

  • 1Department of Medicine, Division of Gastroenterology & Hepatology, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA.

Pharmacoepidemiology and Drug Safety
|May 12, 2021
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Summary

Identifying patients with autoimmune hepatitis (AIH) in health records is challenging. A new algorithm using ICD codes and additional criteria accurately identifies AIH patients in administrative data.

Keywords:
administrative claims dataalgorithmautoimmune hepatitis

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Area of Science:

  • Medical Informatics
  • Hepatology
  • Epidemiology

Background:

  • Population-level studies on autoimmune hepatitis (AIH) treatment are limited.
  • Validated methods for identifying AIH patients in large health databases are lacking.

Purpose of the Study:

  • To assess the accuracy of International Classification of Diseases (ICD) codes for identifying AIH.
  • To develop and validate a novel algorithm for reliable AIH patient identification in health administrative data.

Main Methods:

  • Cross-sectional study of patients with AIH ICD codes (2008-2019).
  • Validation of a base algorithm using Simplified/Revised AIH scores or expert review.
  • Iterative refinement of the algorithm with additional exclusion criteria.

Main Results:

  • The base algorithm achieved a positive predictive value (PPV) of 77.6%.
  • Excluding patients with biliary disease codes improved PPV to 89.7%.
  • Further excluding patients with recent immune checkpoint inhibitor therapy increased PPV to 92.9%.

Conclusions:

  • ICD codes alone are insufficient for reliable AIH patient identification.
  • The developed algorithm incorporating diagnostic and medication criteria demonstrates high performance.