Hospital Cost of Inflammatory Bowel Disease and Its Determinants in a Multicenter Study From Iran

Background: In the current era of monitoring healthcare costs for patients with inflammatory bowel disease (IBD), there has been a shift in the pattern of such costs. In this cross-sectional study conducted in three hospitals in Iran from 2015 to 2021, we aimed to assess the in-hospital costs of IBD and identify predictors of higher total hospital costs in hospitalized patients with IBD. Methods: This cross-sectional study was conducted at three hospitals in Iran. For the purpose of this study, we collected demographic and clinical information, as well as cost data for patients with IBD. Two non-parametric statistical procedures, classification and regression trees (CARTs) and quantile regression forests (QRFs), were employed to identify the main factors related to hospital costs of IBD, which served as the dependent variable in our analysis. Results: During 7 years, 930 admissions occurred in these three hospitals. 22.3% of patients (138 of 619) were readmitted, and 306 (49.4%) were male. The mean age of the patients was 33 (SD=18.9) years. A total of 454 patients (73.3%) had ulcerative colitis (UC), and 165 patients (26.7%) had Crohn’s disease (CD). Hotelling and medication costs accounted for the largest share of the total hospital costs, with percentages of 30.61% and 23.40%, respectively. Length of stay (LOS) was found to be the most important variable related to hospital costs of IBD in both QRF and CART models, followed by age and year of hospital admission in QRF. Additionally, in the CART model, hospital type and year of hospital admission were also significant predictors of hospital costs for patients with IBD. Conclusion: The present study showed that LOS, age, year of admission, and the hospital where the patient is admitted are all important factors that determine hospital costs for patients with IBD. Patients admitted for 20.5 days or longer had the highest hospital costs. These findings can be used as thresholds for future DRG policies.