The economic impact of multimorbidity in Italy:evaluation of direct costs and scenario analysis ofpatients with type 2 diabetes, heart failure, andchronic kidney disease using real-world data

ABSTRACT
Objectives: This study aimed to evaluate the healthcare costs associated with managing type 2 diabetes (T2D),
chronic kidney disease (CKD), and heart failure (HF) in Italy. Specifically, the research investigated the economic
impact on the Italian National Health System due to the increased clinical complexity and multimorbidity among
patients with these conditions.
Methods: A predictive model was developed to estimate the costs of managing patients with T2D, CKD, and HF,
either as standalone diseases or in combination. Epidemiological data were derived from real-world data, analyzing
a sample corresponding to approximately 10% of the Italian population. The model stratified patients into
seven groups based on disease combinations and estimated direct healthcare costs, resulting from hospitalizations,
medications, and outpatient services. Scenario analyses were performed to forecast costs based on the
expected progression of single diseases to multimorbid conditions.
Results: The analysis estimated a total annual healthcare expenditure of approximately €18.7 billion for the 5.77
million Italian patients with at least one of these diseases. Patients with T2D, CKD, and HF had an average yearly
cost of €2,002, €4,322, and €5,061, respectively, with multimorbid patients incurring significantly higher costs.
Scenario analyses predicted a potential increase in total healthcare expenditures to €19.5 billion, with an additional
burden of €775 million.
Conclusions: The findings underscore the substantial economic burden of T2D, CKD, and HF, exacerbated by
multimorbidity. The results highlight the need for early diagnosis, targeted prevention, and optimized treatment
strategies to mitigate rising healthcare costs and improve patients’ outcomes.
Keywords: Chronic kidney disease, Healthcare costs, Heart failure, Multimorbidity, Scenario analysis, Type 2
diabetes