D Goldberg1, Jd Lewis, Sd Halpern, Mark Weiner, Vincent Lo Re. 1. Department of Medicine, Division of Gastroenterology, University of Pennsylvania; Clinical Center for Biostatistics and Epidemiology, University of Pennsylvania.
Abstract
PURPOSE: Use of administrative or population-based databases for post-marketing pharmacoepidemiology research in patients with end-stage liver disease (ESLD) has been limited by the difficulty of accurately identifying such patients. Algorithms to identify patients with ESLD using ICD-9-CM codes have not been developed outside of the Veterans Affairs healthcare setting. METHODS: We queried electronic medical records at two tertiary care hospitals to identify patients with ICD-9-CM codes indicative of ESLD. Coding algorithms were developed to identify patients with confirmed ESLD, and these were tested to determine their positive predictive value (PPV). RESULTS: The presence of one inpatient or outpatient ICD-9-CM code for: (i) cirrhosis; (ii) chronic liver disease, and (iii) a hepatic decompensation event yielded a PPV of 85.2% (167/196; 95% CI: 79.4%-89.9%). The PPV increased to 89.3% (150/168; 95% CI: 83.6%-93.5%) when the algorithm required two or more ICD-9-CM codes for a hepatic decompensation. However, an algorithm requiring only one ICD-9-CM code for (i) cirrhosis and (ii) a hepatic decompensation event, in the absence of a chronic liver disease code, yielded a PPV of 85.7% (30/35; 95% CI: 69.7%-95.2%). CONCLUSIONS: A coding algorithm that includes at least one ICD-9-CM code for cirrhosis plus one ICD-9-CM code for a hepatic decompensation event has a high PPV for identifying patients with ESLD. The inclusion of at least two codes indicative of a hepatic decompensation event increased the PPV. This algorithm can be used in future epidemiologic studies to examine the outcomes of a variety of long-term medical therapies in patients with ESLD.
PURPOSE: Use of administrative or population-based databases for post-marketing pharmacoepidemiology research in patients with end-stage liver disease (ESLD) has been limited by the difficulty of accurately identifying such patients. Algorithms to identify patients with ESLD using ICD-9-CM codes have not been developed outside of the Veterans Affairs healthcare setting. METHODS: We queried electronic medical records at two tertiary care hospitals to identify patients with ICD-9-CM codes indicative of ESLD. Coding algorithms were developed to identify patients with confirmed ESLD, and these were tested to determine their positive predictive value (PPV). RESULTS: The presence of one inpatient or outpatient ICD-9-CM code for: (i) cirrhosis; (ii) chronic liver disease, and (iii) a hepatic decompensation event yielded a PPV of 85.2% (167/196; 95% CI: 79.4%-89.9%). The PPV increased to 89.3% (150/168; 95% CI: 83.6%-93.5%) when the algorithm required two or more ICD-9-CM codes for a hepatic decompensation. However, an algorithm requiring only one ICD-9-CM code for (i) cirrhosis and (ii) a hepatic decompensation event, in the absence of a chronic liver disease code, yielded a PPV of 85.7% (30/35; 95% CI: 69.7%-95.2%). CONCLUSIONS: A coding algorithm that includes at least one ICD-9-CM code for cirrhosis plus one ICD-9-CM code for a hepatic decompensation event has a high PPV for identifying patients with ESLD. The inclusion of at least two codes indicative of a hepatic decompensation event increased the PPV. This algorithm can be used in future epidemiologic studies to examine the outcomes of a variety of long-term medical therapies in patients with ESLD.
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