Predictors of flare-related inpatient or emergency department stay in systemic lupus erythematosus: A real-world analysis of Medicaid claims in the United States.

Abstract

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease characterized by multisystem inflammation. Medical management of SLE is based on reducing inflammation and tissue damage in the affected organs; however, medications used to treat SLE have been found to contribute to additional organ damage. Therefore, finding new ways to predict and prevent flares that require an inpatient (IP) stay or emergency department (ED) visit is critical for reducing the clinical and economic burden in patients with SLE. To identify risk factors of SLE flares requiring an IP/ED visit among a Medicaid-insured population with SLE. This retrospective study included patients from the Merative MarketScan Medicaid database (2013-2019). To capture patients at all stages of their SLE journey, all SLE claims for a patient were captured, and the index date was randomly selected among those claims that were at least 12 months after the first evidence of SLE. Patients were required to be continuously enrolled 1-year pre-index (year 1) and post-index (year 2). Demographics, clinical characteristics, and health care use and costs were measured in year 1, and flares requiring an IP/ED visit were identified in year 2 using the Garris algorithm. Multivariable logistic regression and classification and regression tree (CART) modeling were used to identify year 1 predictors and combination of factors, respectively, associated with flares-related IP/ED visits. Of the 8,083 patients included in the study, 37.6% of patients (n = 3,039) had a flare. Logistic regression identified ED visits in year 1 as one of the strongest predictors of flares-related IP/ED visits in year 2 (odds ratio = 2.19 [95% CI = 1.93-2.49]). SLE treatment progression to biologics (0.54 [0.42-0.70]) was the strongest predictor of decreased odds. Other strong predictors included other neurological disorders (1.63 [1.43-1.87]), Black race (1.49 [1.32-1.68]), chronic kidney disease/renal failure (1.35 [1.10-1.66]), and opioid use (1.30 [1.17-1.45]). CART modeling identified patients with an ED visit, an IP admission, and a diagnosis of Elixhauser Comorbidity Index-defined other neurological disorders in year 1 as having the highest probability of a flare-related IP/ED visit in year 2 (probability = 0.708), whereas patients without an ED visit had the lowest probability (probability = 0.185). Patients with the highest risk of a flare that required an IP/ED visit were those with a prior ED visit, IP admission, and other neurological disorders. Modeling also identified patients with prior opioid use, Black patients, and patients without SLE medications as subgroups with a high risk of a flare requiring an IP/ED visit.