Purpose
To develop and validate case-finding algorithms for granulomatosis with polyangiitis (Wegener’s, GPA), microscopic polyangiitis (MPA), and eosinophilic granulomatosis with polyangiitis (Churg-Strauss, EGPA).
Methods
250 patients per disease were randomly selected from 2 large healthcare systems using the International Classification of Diseases version 9 (ICD9) codes for GPA/EGPA (446.4) and MPA (446.0). 16 case-finding algorithms were constructed using a combination of ICD9 code, encounter type (inpatient or outpatient), physician specialty, use of immunosuppressive medications, and the anti-neutrophil cytoplasmic antibody (ANCA) type. Algorithms with the highest average positive predictive value (PPV) were validated in a third healthcare system.
Results
An algorithm excluding patients with eosinophilia or asthma and including the encounter type and physician specialty had the highest PPV for GPA (92.4%). An algorithm including patients with eosinophilia and asthma and the physician specialty had the highest PPV for EGPA (100%). An algorithm including patients with one of the following diagnoses: alveolar hemorrhage, interstitial lung disease, glomerulonephritis, acute or chronic kidney disease, the encounter type, physician specialty, and immunosuppressive medications had the highest PPV for MPA (76.2%). When validated in a third healthcare system, these algorithms had high PPV (85.9% for GPA, 85.7% for EGPA, and 61.5% for MPA). Adding the ANCA type increased the PPV to 94.4%, 100%, and 81.2% for GPA, EGPA, and MPA respectively.
Conclusion
Case-finding algorithms accurately identify patients with GPA, EGPA, and MPA in administrative databases. These algorithms can be used to assemble population-based cohorts and facilitate future research in epidemiology, drug safety, and comparative effectiveness.