Economic Evaluation of an Integrated Health and Social Care Program for Heart Failure Through 2 Different Modeling Techniques. (29th November 2018)

• Record Type: Journal Article
• Authors: Larrañaga, Igor; Stafylas, Panos; Fullaondo, Ane; Apuzzo, Gian Matteo; Mar, Javier
• Is Part Of: Health services research and managerial epidemiology. Volume 5(2018)
• Publication Date: 2018-11-29
• Subjects: heart failure -- SmartCare -- integrated health care -- Markov -- discrete event simulation; Medical care -- Periodicals; Health services administration -- Periodicals; Epidemiology -- Periodicals; 362.1
• DOI: 10.1177/2333392818795795
• Languages: English
• ISSNs: 2333-3928

Abstract

Introduction: An integrated health and social care program for patients with heart failure (HF) was implemented at the Friuli-Venezia Giulia deployment site as part of the SmartCare European project. The objective of this study was to validate 2 different decision modeling techniques used to perform the economic evaluation. Methods: Data were collected during the SmartCare project which enrolled 108 patients with HF and followed for more than 6 months. The techniques used were Markov and discrete event simulation models. In both cases, a cost-effectiveness analysis and a budget impact analysis were carried out. The former was used to assign priority to the intervention and the latter to assess its sustainability. Analyses were conducted from the perspective of the Regional Health Authority. Results: Results were similar with both types of model. Cost-effectiveness analysis found no significant differences in quality of life, but the intervention generated significant cost savings, becoming the dominant option. Data extrapolation showed no benefits in terms of mortality or hospital admissions, but budget impact analysis also predicted annual savings, as a significant number of in-hospital days were avoided. In budget analysis, both models predicted early, increasing and cumulative annual savings. Discussion: The integrated program was dominant as it provided better outcomes and lower total costs, and thus, decision-makers should prioritize it. Besides, the work demonstrates the capacity of decision modeling to become a complementary tool in managing integrated health and social care models.