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Identification of Health Expenditures Determinants: A Model to Manage the Economic Burden of Cardiovascular Disease

Fiorella Pia Salvatore, Alessia Spada, Francesca Fortunato, Demetris Vrontis and Mariantonietta Fiore ()
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Fiorella Pia Salvatore: Department of Economics, University of Foggia, 71121 Foggia, Italy
Alessia Spada: Department of Economics, University of Foggia, 71121 Foggia, Italy
Francesca Fortunato: Sector of Hygiene, Department of Medical and Surgical Sciences, University of Foggia, 71121 Foggia, Italy
Demetris Vrontis: School of Business, University of Nicosia, Nicosia 1700, Cyprus

IJERPH, 2021, vol. 18, issue 9, 1-15

Abstract: The purpose of this paper is to investigate the determinants influencing the costs of cardiovascular disease in the regional health service in Italy’s Apulia region from 2014 to 2016. Data for patients with acute myocardial infarction (AMI), heart failure (HF), and atrial fibrillation (AF) were collected from the hospital discharge registry. Generalized linear models (GLM), and generalized linear mixed models (GLMM) were used to identify the role of random effects in improving the model performance. The study was based on socio-demographic variables and disease-specific variables (diagnosis-related group, hospitalization type, hospital stay, surgery, and economic burden of the hospital discharge form). Firstly, both models indicated an increase in health costs in 2016, and lower spending values for women ( p < 0.001) were shown. GLMM indicates a significant increase in health expenditure with increasing age ( p < 0.001). Day-hospital has the lowest cost, surgery increases the cost, and AMI is the most expensive pathology, contrary to AF ( p < 0.001). Secondly, AIC and BIC assume the lowest values for the GLMM model, indicating the random effects’ relevance in improving the model performance. This study is the first that considers real data to estimate the economic burden of CVD from the regional health service’s perspective. It appears significant for its ability to provide a large set of estimates of the economic burden of CVD, providing information to managers for health management and planning.

Keywords: health costs; healthcare management; gender medicine; GLM model; GLMM; data oriented (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
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