Accuracy of pharmacy and coded-diagnosis information in identifying tuberculosis in patients with rheumatoid arthritis

Abstract

Purpose: Previous studies suggest that disease-modifying anti-rheumatic drugs (DMARDs) increase tuberculosis (TB) risk. The accuracy of pharmacy and coded-diagnosis information to identify persons with TB is unclear.

Methods: Within a cohort of rheumatoid arthritis (RA) patients (2000-2005) enrolled in Tennessee Medicaid, we identified those with potential TB using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD9-CM) diagnosis codes and/or pharmacy claims. Using the Tennessee TB registry as the gold standard for identification of TB, we estimated the sensitivity, specificity, predictive values, and the respective 95% confidence intervals for each TB case-ascertainment strategy.

Results: Ten of 18,094 RA patients had confirmed TB during 61,461 person-years of follow-up (16.3 per 100,000 person-years). The sensitivity and positive predictive value (PPV) and respective 95% confidence intervals were low for confirmed TB based on ICD9-CM codes alone (60.0% (26.2-87.8) and 1.3% (0.5-2.9)), pharmacy data alone (20% (2.5-55.6) and 4.1% (0.5-14.3)), and both (20% (2.5-55.6) and 25.0% (3.2-65.1)).

Conclusions: Algorithms that use administrative data alone to identify TB have a poor PPV that results in a high false positive rate of TB detection.