BACKGROUND & AIMS:
A subset of patients with inflammatory bowel diseases (IBD) have continuously active inflammation, leading to a high number of complications and high direct health care costs (diagnostic tests, medications, and surgeries) and indirect costs (reduced employment and productivity and fewer opportunities for activities). Identifying these high-risk patients and providing effective interventions could produce better outcomes and reduce costs. We used prior year data to create IBD risk models to predict IBD-related hospitalizations, emergency department visits, and high treatment charges (>$30,000/year) in the subsequent year.
We performed a retrospective study of medical records from all patients with IBD treated at the University of Michigan Hospital from fiscal years 2013-2015. We selected clinical variables from the prior year and tested their abilities to predict 3 adverse outcomes (IBD-related hospitalizations, emergency department visits, and treatment charges >$30,000/year) in the subsequent year. Individual patients were only included once in the data set. We created a multivariate model that was based on a 70% randomly selected cohort (1005 patients) and validated the model on the other 30% (425 patients). Logistic regression was used for bivariate and multivariate analyses.
Factors that predicted high-cost outcomes included the presence of psychiatric illness, use of corticosteroids, use of narcotics, low levels of hemoglobin, and high numbers of IBD-related hospitalizations. In the validation cohort, the model predicted IBD-related hospitalizations, emergency department visits, and high charges in the following year with receiver operating characteristic curve values of 0.751, 0.738, and 0.744, respectively.
We identified 5 factors that can effectively identify patients with IBD at high risk for hospitalization, emergency department visits, and high treatment charges in the next year. These patients should be closely monitored and aggressively managed.