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Background: Inflammatory bowel diseases (IBDs), Crohn's disease (CD) and ulcerative colitis (UC), are chronic diseases that have been increasingly treated with biological drugs in recent years. Newly developed coding algorithms for IBD identification using claims databases are needed to improve post-marketing surveillance of biological drugs. Objective: To test algorithms to identify CD and UC, as indication for use of biological drugs approved for IBD treatment, using a claims database. Methods: Data were extracted from the Caserta Local Health Unit database between 2015 and 2018. CD/UC diagnoses reported by specialists in electronic therapeutic plans (ETPs) were considered as gold standard. Five algorithms were developed based on ICD-9-CM codes as primary cause of hospital admissions, exemption from healthcare service co-payment codes and drugs dispensing with only indication for CD/UC. The accuracy was assessed by sensitivity (Se), specificity (Sp), positive (PPV) and negative predicted values (NPV) along with computation of the Youden Index and F-score. Results: In the study period, 1205 subjects received at least one biological drug dispensing approved for IBD and 134 (11.1%) received ≥ 1 ETP with IBD as use indication. Patients with CD and CU were 83 (61.9%) and 51 (38.1%), respectively. Sensitivity of the different algorithms ranged from 71.1% (95% CI: 60.1– 80.5) to 98.8 (95% CI: 93.5– 100.0) for CD and from 64.7% (95% CI: 50.1– 77.6) to 94.1 (95% CI: 83.8– 98.8) for UC, while specificity was always higher than 91%. The best CD algorithm was "Algorithm 3", based on hospital CD diagnosis code OR CD exemption code OR [IBD exemption code AND dispensing of non-biological drugs with only CD indication] (Se: 98.8%; Sp: 97.2%; PPV: 84.5%, NPV: 99.8%), achieving the highest diagnostic accuracy (Youden Index=0.960). The best UC algorithm was "Algorithm 3", based on specific hospital UC diagnosis code OR UC exemption code OR [IBD exemption code AND golimumab dispensing] OR dispensing of non-biological drugs with only UC indication (Se: 94.1%; Sp: 91.6%; PPV: 50.0%; NPV: 99.4%), and achieving the highest diagnostic accuracy (Youden Index=0.857). Conclusion: In a population-based claims database, newly coding algorithms including diagnostic and exemption codes plus specific drug dispensing yielded highly accurate identification of CD and UC as distinct indication for biological drug use. [ABSTRACT FROM AUTHOR]