Medical Costs of Patients with Type 2 Diabetes in a Single Payer System: A Classification and Regression Tree Analysis

Abstract

Background and Objectives: Many studies and systematic reviews have estimated the healthcare costs of diabetes using a cost-of-illness approach. However, in the studies based on this approach patients’ heterogeneity is rarely taken into account. The aim of this study was to stratify patients with type 2 diabetes into homogeneous cost groups based on demographic and clinical characteristics. Methods: We conducted a retrospective cost-of-illness study by linking individual data on health services utilization retrieved from the administrative databases of Emilia-Romagna Region (Italy). Direct medical costs (either all-cause or diabetes-related) were calculated from the perspective of the regional health service, using tariffs for hospitalizations and outpatient services and the unit costs of prescriptions for drugs. The determinants of costs identified in a generalized linear regression model were used to characterize subgroups of patients with homogeneous costs in a classification and regression tree analysis. Results: The study population consisted of a cohort of 101,334 patients with type 2 diabetes, followed up for 1 year, with a mean age of 70.9 years. Age, gender, complications, comorbidities and living area accounted significantly for cost variability. The classification tree identified ten patient subgroups with different costs, ranging from a median of €483 to €39,578. The two subgroups with highest costs comprised dialysis patients, and the largest subgroup (57.9%) comprised patients aged ≥ 65 years without renal, cardiovascular and cerebrovascular complications. Conclusions: Classification of patients into homogeneous cost subgroups can be used to improve the management of, and budget allocation for, patients with type 2 diabetes.