Background: The majority of chronic disease is caused by risk factors which are mostly preventable. Effective interventions to reduce these risks are known and proven to be applicable to a variety of settings. Chronic disease is generally developed long before the fatal outcome, meaning that a lot of people spend a number of years in poor health. Effective prevention measures can prolong lives of individuals and significantly improve their quality of life. However, the methods to measure cost-effectiveness are a subject to much debate. The Economics of Chronic Diseases project aims to establish the best possible methods of measuring cost-effectiveness as well as develop micro-simulation models apt at projecting future burden of chronic diseases, their costs and potential savings after implementation of cost-effective interventions.
Method: This research project will involve eight European countries: Bulgaria, Finland, Greece, Lithuania, The Netherlands, Poland, Portugal and the United Kingdom (UK). A literature review will be conducted to identify scientific articles which critically review the methods of cost-effectiveness. Contact will be made health economists to inform and enrich this review. This evidence will be used as a springboard for discussion at a meeting with key European stakeholders and experts with the aim of reaching a consensus on recommendations for cost-effectiveness methodology. Epidemiological data for coronary heart disease, chronic kidney disease, type 2 diabetes and chronic obstructive pulmonary disease will be collected along with data on time trends in three major risk factors related to these diseases, specifically tobacco consumption, blood pressure and body mass index. Economic and epidemiological micro-simulation models will be developed to asses the future distributions of risks, disease outcomes, healthcare costs and the cost-effectiveness of interventions to reduce the burden of chronic diseases in Europe.
Discussion: This work will help to establish the best methods of measuring cost-effectiveness of health interventions as well as test a variety of scenarios to reduce the risk factors associated with selected chronic diseases. The modelling projections could be used to inform decisions and policies that will implement the best course of action to curb the rising incidence of chronic diseases.