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A Validated Algorithm to Identify Hepatic Decompensation in the Veterans Health Administration Electronic Health

Lamia Y Haque1,2, Janet P Tate2,3, Michael Chew1,2

  • 1Section of Digestive Diseases, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.

Pharmacoepidemiology and Drug Safety
|October 30, 2024
PubMed
Summary
This summary is machine-generated.

A new algorithm using International Classification of Diseases, 10th revision (ICD-10) codes accurately identifies hepatic decompensation in electronic health records. This method is crucial for research in chronic liver disease patients.

Keywords:
epidemiological methodshepatic decompensationliver cirrhosisvalidation

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Area of Science:

  • Hepatology
  • Pharmacoepidemiology
  • Health Informatics

Background:

  • Accurate identification of hepatic decompensation is critical for pharmacoepidemiologic studies in chronic liver disease.
  • Existing methods may lack precision in identifying this key clinical event.

Purpose of the Study:

  • To develop and validate an algorithm for identifying hepatic decompensation using International Classification of Diseases, 10th revision (ICD-10) codes.
  • To assess the positive predictive value (PPV) of this algorithm in a real-world healthcare setting.

Main Methods:

  • An algorithm was created using ICD-10 codes for hepatic decompensation (≥1 inpatient or ≥2 outpatient codes).
  • Data were sourced from the Veterans Health Administration between October 2015 and July 2019.
  • Hepatologist review of medical records confirmed cases, and the PPV of the algorithm was calculated.

Main Results:

  • The algorithm identified confirmed hepatic decompensation in 149 out of 185 records, yielding a PPV of 81% (95% CI, 70%-90%).
  • Ascites was the most frequent diagnosis associated with hepatic decompensation.
  • Cirrhosis diagnosis codes were present in only 56% of confirmed hepatic decompensation cases.

Conclusions:

  • An ICD-10-based coding algorithm demonstrates a high positive predictive value for identifying hepatic decompensation.
  • This validated algorithm can reliably support pharmacoepidemiologic research in patients with chronic liver disease within the Veterans Health Administration.