Validation of a coding algorithm to identify patients with hepatocellular carcinoma in an administrative database

• Published in: Pharmacoepidemiology and drug safety Vol. 22; no. 1; pp. 103 - 107
• Main Authors: Goldberg, David S., Lewis, James D., Halpern, Scott D., Weiner, Mark G., Re III, Vincent Lo
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 01.01.2013; Wiley Subscription Services, Inc
• Subjects: Algorithms; Cancer therapies; Carcinoma, Hepatocellular - classification; Carcinoma, Hepatocellular - diagnosis; Carcinoma, Hepatocellular - epidemiology; Chemotherapy; Chronic Disease; chronic liver disease; cirrhosis; Cross-Sectional Studies; Databases, Factual; Electronic Health Records - statistics & numerical data; Epidemiology; hepatocellular carcinoma; Hospitals; Humans; ICD-9-CM code; International Classification of Diseases; Liver cancer; Liver Cirrhosis - classification; Liver Cirrhosis - diagnosis; Liver Cirrhosis - epidemiology; Liver Diseases - classification; Liver Diseases - diagnosis; Liver Diseases - epidemiology; Liver Neoplasms - classification; Liver Neoplasms - diagnosis; Liver Neoplasms - epidemiology; Male; Medical coding; Middle Aged; pharmacoepidemiology; Predictive Value of Tests; validation
• ISSN: 1053-8569; 1099-1557; 1099-1557
• DOI: 10.1002/pds.3367

ABSTRACT Purpose International Classification of Disease, Ninth Revision, Clinical Modification (ICD‐9‐CM)‐based algorithms to identify patients with hepatocellular carcinoma (HCC) have not been developed outside of the Veterans Affairs healthcare setting. The development and validation of such algorithms are necessary for the conduct of population‐based studies evaluating the epidemiology and comparative effectiveness and safety of therapies for HCC. Methods We queried electronic medical records at two tertiary care hospitals to identify patients with two ICD‐9‐CM diagnosis codes for a chronic liver disease and/or cirrhosis plus two ICD‐9‐CM codes for HCC. We determined the positive predictive value (PPV) of this algorithm by comparing it to diagnoses of HCC confirmed by expert medical record review. Results Among 101 patients meeting the algorithm, 88 (PPV: 87.1%; 95% CI: 79.0–93.0%) had confirmed HCC. The algorithm's sensitivity was 91.7% among patients with confirmed HCC, and its specificity was 98.7% among chronic liver disease patients without HCC. Excluding patients who received systemic chemotherapy in the 12 months prior to or 6 months after the initial ICD‐9‐CM code in the algorithm, the PPV increased to 91.6% (87/95; 95% CI: 84.1–96.3%). Conclusions The presence of at least two ICD‐9‐CM codes for a chronic liver disease and/or cirrhosis plus two ICD‐9‐CM codes for HCC has a high PPV for identifying HCC cases. This simple, claims‐based algorithm can be used in future epidemiologic studies to examine risk factors for HCC and evaluate outcomes and adverse events of medical therapies prescribed for HCC patients. Copyright © 2012 John Wiley & Sons, Ltd.