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

Fiorella Pia Salvatore,Alessia Spada,Demetris Vrontis,Francesca Fortunato,Mariantonietta Fiore

doi:10.3390/ijerph18094652

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.

Highlights

The ongoing evolution of demographic dynamics, and the consequent modification of the population’s health needs, with a growing share of elderly patients and those with chronic diseases, requires health systems to be structurally and organizationally redesigned [1].Chronic diseases represent the close time horizon of the world countries, given the constantly increasing trend of risk factors [2]
Data for patients with acute myocardial infarction (AMI), heart failure (HF), and atrial fibrillation (AF) were extracted from electronic medical records included in the hospital discharge registry (HDR)
The HDR is held at the regional epidemiological observatory in the Apulia region, in southern Italy, which has a population of about 4 million (6.67% of the Italian population)

Summary

Introduction

Chronic diseases represent the close time horizon of the world countries, given the constantly increasing trend of risk factors [2]. National health services are currently challenged to research and develop strategies, determinants, and impacts to reduce the predisposition to chronic degenerative diseases and to reduce the burden of the same on public accounts. A careful economic evaluation of the determinants reveals the paramount importance of starting new cost-effective strategies to optimize performance of health expenditure [5]. Governments, academia, and experts in health economics are faced with increased healthcare costs and are searching for tools to reform and to reduce health expenditures [6,7]. Healthcare costs are increasing more and more across all of the world’s

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