Fair resource allocation: Using welfare-based dominance constraints

COVID-19 and the efficiency of health systems in Europe

“…We summarize, briefly, some results of these studies: by analyzing 34 OECD countries from the perspective of health systems efficiency, using 14 inputs (pharmaceutical consumption, average years of schooling, obesity, tobacco consumption, alcohol consumption, per capita health expenditure, percentage of health care expenditure, physicians, nurses, beds) and 4 outputs (life expectancy, infant mortality, population aged and population aged 65 years and older), it is concluded that there are substantial differences between countries’ health systems and subsystems, which require specific approaches to improve their performance [ 7 ]; applying the analysis to the level of 29 OECD countries, in the period 2000–2010, it is highlighted that a positive influence on the efficiency of health systems is given by education, income, environment, and a negative one by health expenditures, public or private [ 10 ]; at the level of 34 OECD countries, the DEA method is applied to rank the states in terms of the efficiency of health systems and a strong efficiency is obtained in Norway, Sweden, Germany, South Korea, Singapore, Japan, while the other states present lower efficiencies [ 8 ]; studying the health systems for 31 OECD countries taking into account both health system variables (doctors, beds and health expenditure) and external ones (GDP, institutional arrangements, population behavior, socio-economic or environmental determinants), the conclusion was that external factors are the ones that have a greater influence on efficiency than health factors [ 6 ]; including in the study 32 OECD countries, it is highlighted that a number of factors (obesity, smoking, low GDP per capita and education level) negatively influence the efficiency of health systems, while environmental factors have a positive influence [ 11 ]. by developing a theoretical model for establishing resource allocation decisions that affect multiple beneficiaries, it is shown that for maximizing efficiency it is necessary to consider the fairness, and with reference to medical decisions made by the World Health Organization (WHO), they should to be done at a certain aggregate level, rather than separately for each affected individual [ 12 ]. …”

“…by developing a theoretical model for establishing resource allocation decisions that affect multiple beneficiaries, it is shown that for maximizing efficiency it is necessary to consider the fairness, and with reference to medical decisions made by the World Health Organization (WHO), they should to be done at a certain aggregate level, rather than separately for each affected individual [ 12 ].…”

A guide to formulating fairness in an optimization model

“…Various methods are described in Gralla et al ( 2014 ); Carland et al ( 2018 ); Yılmaz and Kabak ( 2020 ), and Hasnain et al ( 2021 ). An alternate approach, proposed by Argyris et al ( 2022 ), does not rely on a single set of weights given in advance. Rather, it requires that the resulting distribution of benefits be at least as fair as a “reference” distribution, perhaps representing a floor on the degree of acceptable fairness.…”

Exploring the nexus of equality and efficiency in healthcare

“…Operations research provides an interesting perspective with useful analytical tools and states that if the efficiency loss is negligible, the DMUs would find it easier to support a solution that ensures fairness. Therefore, in many cases, addressing fairness concerns results in a decrease in efficiency (Karsu and Morton, 2015; Argyris et al , 2022). Thus, the choice between equality and efficiency become inevitable (Reidpath et al , 2012; Sun and Luo, 2017).…”