Heart failure: a prevalence-based and model-based cost analysis

Abstract

IntroductionHeart failure (HF) imposes a heavy economic burden on patients, their families, and society as a whole. Therefore, it is crucial to quantify the impact and dimensions of the disease in order to prioritize and allocate resources effectively.MethodsThis study utilized a prevalence-based, bottom-up, and incidence-based Markov model to assess the cost of illness. A total of 502 HF patients (classes I–IV) were recruited from Madani Hospital in Tabriz between May and October 2022. Patients were followed up every two months for a minimum of two and a maximum of six months using a person-month measurement approach. The perspective of the study was societal, and both direct and indirect costs were estimated. Indirect costs were calculated using the Human Capital (HC) method. A two-part regression model, consisting of the Generalized Linear Model (GLM) and Probit model, was used to analyze the relationship between HF costs and clinical and demographic variables.ResultsThe total cost per patient in one year was 261,409,854.9 Tomans (21,967.21 PPP). Of this amount, 207,147,805.8 Tomans (17,407.38 PPP) (79%) were indirect costs, while 54,262,049.09 Tomans (4,559.84 PPP) (21%) were direct costs. The mean lifetime cost was 2,173,961,178 Tomans. Premature death accounted for the highest share of lifetime costs (48%), while class III HF had the lowest share (2%). Gender, having basic insurance, and disease class significantly influenced the costs of HF, while comorbidity and age did not have a significant impact. The predicted amount closely matched the observed amount, indicating good predictive power.ConclusionThis study revealed that HF places a significant economic burden on patients in terms of both direct and indirect costs. The substantial contribution of indirect costs, which reflect the impact of the disease on other sectors of the economy, highlights the importance of unpaid work. Given the significant variation in HF costs among assessed variables, social and financial support systems should consider these variations to provide efficient and fair support to HF patients.