Development and Validation of an Inflammatory Bowel Disease Severity Index Using US Administrative Claims Data: A Retrospective Cohort Study

Abstract

Background: Clinical indices to characterize the severity of inflammatory bowel disease (IBD) are widely used in clinical trials and real-world practice. However, there are few validated instruments for assessing IBD severity in administrative claims-based studies. Methods: Patients (18-89 years) diagnosed with ulcerative colitis (UC) or Crohn's disease (CD) and receiving ≥1 prescription claim for IBD therapy were identified using administrative claims data from the Optum Clinformatics, IMS PharMetrics, and Truven MarketScan databases (January 1, 2013-September 30, 2017). Regression modeling identified independent predictors of IBD-related hospitalization (inpatient stay or emergency department visit resulting in hospitalization), which were used to develop IBD severity indices. The index was validated against all-cause hospitalization and total cost and IBD-related hospitalization and total cost. Results: There were 51,767 patients diagnosed with UC (n = 30,993) or CD (n = 20,774) who were initiated treatment with IBD therapy. Independent predictors of IBD-related hospitalization were Charlson Comorbidity Index score >1, anemia, weight loss, intravenous corticosteroid use, prior gastrointestinal-related emergency department visit and hospitalization, and unspecified disease location or more extensive disease. Female sex, renal comorbidities, intestinal fistula, and stricture were additional risk factors for patients with CD, whereas age <40 years was a UC-specific risk factor. Median IBD severity scores were 8 and 13 for UC and CD, respectively, from possible total scores of 51 and 37. Inflammatory bowel disease severity score correlated with significantly higher all-cause hospitalization and cost, all-cause total cost, IBD-related hospitalization cost, and total cost. Conclusions: These validated UC and CD severity indices can be used to predict IBD-related outcomes using administrative claims databases.