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Using social choice theory and acceptability analysis to measure the value of health systems
The Future Health Index (FHI) is developed by the Royal Philips to help determine the readiness of countries to address global health challenges and build sustainable, fit-for-purpose national health systems. The FHI 2018 presents the Value Measure to measure the value of 16 health systems, which is...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7332049/ https://www.ncbi.nlm.nih.gov/pubmed/32614864 http://dx.doi.org/10.1371/journal.pone.0235531 |
Sumario: | The Future Health Index (FHI) is developed by the Royal Philips to help determine the readiness of countries to address global health challenges and build sustainable, fit-for-purpose national health systems. The FHI 2018 presents the Value Measure to measure the value of 16 health systems, which is formulated by taking the arithmetic average of Access, Satisfaction and Efficiency. However, this scheme is not the Pareto optimal and loses association with weights. For these reasons, this paper proposes to apply the social choice theory and Stochastic Multicriteria Acceptability Analysis for group decision making (SMAA-2) to measure the value of health systems, by means of re-constructing the Value Measure. Specifically, we begin with considering all possible individual preferences among Access, Satisfaction and Efficiency, which is mathematically represented by ranked weights of them; the pessimistic and optimistic outcomes under certain individual preference are derived in a closed-form manner, according to which an interval decision matrix is then formulated; the SMAA-2 is then lastly applied to compute the holistic acceptability index, which is considered as a revised Value Measure. An empirical study using the data of 16 health systems is conducted to show the effectiveness and superiority of our method. It is demonstrated that our method always outperforms the Value Measure, by means of comparing the Spearman’s rank correlation coefficients. |
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