Validation of three coding algorithms to identify patients with end-stage liver disease in an administrative database
D. Goldberg, Hospital of the University of Pennsylvania, 3400 Spruce Street, 9 Penn Tower, Philadelphia, PA. E-mail: email@example.com
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.
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).
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%).
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. Copyright © 2012 John Wiley & Sons, Ltd.