Validation of claims-based algorithms for psoriatic arthritis

Abstract

Purpose An increasing number of new medications are being developed and approved for psoriatic arthritis (PsA). To generate real-world evidence on comparative safety and effectiveness of these drugs, a claims-based algorithm that can accurately identify PsA is greatly needed. Methods To identify patients with PsA, we developed seven claims-based algorithms based on a combination of diagnosis codes and medication dispensing using the claims data from Medicare parts A/B/D linked to electronic medical records (2012-2014). Two physicians independently conducted a chart review using the treating physician's diagnosis of PsA as the gold standard. We calculated the positive predictive value (PPV) and 95% confidence intervals of each algorithm. Results Of the total 2157 records identified by the seven algorithms, 45% of the records had relevant clinical data to determine the presence of PsA. The PPV of the algorithms ranged from 75.2% (algorithm 1: >= 2 diagnosis codes for PsA and >= 1 diagnosis code for psoriasis) to 88.6% (algorithm 7: >= 2 diagnosis codes for PsA with >= 1 code by rheumatologist and >= 1 dispensing for PsA medication). Having >= 2 diagnosis codes and >= 1 dispensing for PsA medications (algorithm 6) also had PPV of 82.4%. Conclusions All seven claims-based algorithms demonstrated a moderately high PPV of 75% to 89% in identifying PsA. The use of >= 2 diagnosis codes plus >= 1 prescription claim for PsA appears to be a valid and efficient tool in identifying PsA patients in the claims data, while broader algorithms based on diagnoses without a prescription claim also have reasonably good PPVs.