LAUSR

BACKGROUND To facilitate inflammatory bowel disease (IBD) research in the United States, we developed and validated claims-based definitions to identify incident and prevalent IBD diagnoses using administrative healthcare claims data among multiple payers. METHODS We used data from Medicare, Medicaid, and the HealthCore Integrated Research Database (Anthem commercial and Medicare Advantage claims). The gold standard for validation was review of medical records. We evaluated 1 incidence and 4 prevalence algorithms based on a combination of International Classification of Diseases codes, National Drug Codes, and Current Procedural Terminology codes. The claims-based incident diagnosis date needed to be within ±90 days of that recorded in the medical record to be valid. RESULTS We reviewed 111 charts of patients with a potentially incident diagnosis. The positive predictive value (PPV) of the claims algorithm was 91% (95% confidence interval [CI], 81%-97%). We reviewed 332 charts to validate prevalent case definition algorithms. The PPV was 94% (95% CI, 86%-98%) for ≥2 IBD diagnoses and presence of prescriptions for IBD medications, 92% (95% CI, 85%-97%) for ≥2 diagnoses without any medications, 78% (95% CI, 67%-87%) for a single diagnosis and presence of an IBD medication, and 35% (95% CI, 25%-46%) for 1 physician diagnosis and no IBD medications. CONCLUSIONS Through a combination of diagnosis, procedural, and medication codes in insurance claims data, we were able to identify incident and prevalent IBD cases with high accuracy. These algorithms can be useful for the ascertainment of IBD cases in future studies.