Aim A comprehensive approach to health highlights its close relationship with the social and economic conditions, physical environment and individual lifestyles. However, this relationship is not exempt from methodological problems that may bias the establishment of direct effects between the variables studied. Thus, further research is necessary to investigate the role of socioeconomic variables, their composition and distribution according to health status, particularly on non-communicable diseases. Subjects and methods To shed light on this field, here a systematic review is performed using PubMed, the Cochrane Library and Web of Science. A 7-year retrospective horizon was considered until 21 July 2017. Results Twenty-six papers were obtained from the database search. Additionally, results from “hand searching” were also included, where a wider horizon was considered. Five of the 26 studies analyzed used aggregated data compared to 21 using individual data. Eleven considered income as a study variable, while 17 analyzed the effect of income inequality on health status (2 of the studies considered both the absolute level and distribution of income). The most used indicator of inequality in the literature was the Gini index. Conclusion Although different types of analysis produce very different results concerning the role of health determinants, the general conclusion is that income distribution is related to health where it represents a measure of the differences in social class in the society. The effect of income inequality is to increase the gap between social classes or to widen differences in status.

Companies in general and family businesses in particular engage in local collaborations in rather diverse areas through their corporate social responsibility activities. The COVID-19 pandemic has made these contributions to community improvement more apparent, suggesting a paradigm shift. This conceptual paper proposes a reflection about the evolution of the corporate social responsibility activities linked to family businesses in emergencies and from the socioemotional wealth perspective. The contribution of this paper is twofold. Firstly, it provides an in-depth reflection on the evolution of philanthropy, posing the following questions: are we witnessing a reinvention of corporate social responsibility within the framework of family businesses because of the global pandemic; does this new trend deserve support, given the fundamental role that family businesses have played in this situation; and if so, what should such support consist of, and what is the optimal channel for articulating it? Secondly, the paper proposes a theoretical framework from the socioemotional wealth perspective to advance research about corporate social responsibility carried out by family businesses. Business families are more likely to implement strategies that promote ethical behavior and CSR activities in their companies. The pandemic situation has created new possibilities for developing CSR.

Introduction: In recent years, several hospitals have incorporated MRI equipment managed directly by their cardiology departments. The aim of our work is to determine the total cost per test of both CT and MRI in the setting of a Cardiology Department of a tertiary hospital. Materials and Methods: The process followed for estimating the costs of CT and MRI tests consists of three phases: (1) Identification of the phases of the testing process; (2) Identification of the resources consumed in carrying out the tests; (3) Quantification and assessment of inputs. Results: MRI involves higher personnel (EUR 66.03 vs. EUR 49.17) and equipment (EUR 89.98 vs. EUR 33.73) costs, while CT consumes higher expenditures in consumables (EUR 93.28 vs. EUR 22.95) and overheads (EUR 1.64 vs. EUR 1.55). The total cost of performing each test is higher in MRI (EUR 180.60 vs. EUR 177.73). Conclusions: We can conclude that the unit cost of each CT and MRI performed in that unit are EUR 177.73 and EUR 180.60, respectively, attributable to consumables in the case of CT and to amortization of equipment and staff time in the case of MRI.

The future burden of non-communicable diseases (NCDs) depends on numerous factors such as population ageing, evolution of societal trends, behavioural and physiological risk factors of individuals (e.g. smoking, alcohol use, obesity, physical inactivity, and hypertension). This study aims to assess the burden of NCDs in Europe by 2050 under alternative scenarios. This study combines qualitative and quantitative forecasting techniques to examine how population health in Europe may evolve from 2015 to 2050, taking into account future societal trends. Four scenarios were developed (one business-as-usual scenario, two response scenarios and one pessimistic scenario) and assessed against ‘best’ and ‘worst’-case scenarios. This study provides quantitative estimates of both diseases and mortality outcomes, using a microsimulation model incorporating international survey data. Each scenario is associated with a different risk factor prevalence rate across Europe during the period 2015–2050. The prevalence and incidence of NCDs consistently increase during the analysed time period, mainly driven by population ageing. In more optimistic scenarios, diseases will appear in later ages, while in the pessimistic scenarios, NCDs will impair working-age people. Life expectancy is expected to grow in all scenarios, but with differences by up to 4 years across scenarios and population groups. Premature mortality from NCDs will be reduced in more optimistic scenarios but stagnate in the worst-case scenario. Population ageing will have a greater impact on the spread of NCDs by 2050 compared to risk factors. Nevertheless, risk factors, which are influenced by living environments, are an important factor for determining future life expectancy in Europe.

Background: Telemedicine has been incorporated into daily clinical practice. The purpose of this paper is to evaluate the economic impact of electronic consultation as a means of referring patients between Primary Care (PC) services and the referral Cardiology Service (CS) of a tertiary hospital, in particular, the cost of reduced air pollution. Methods: The direct and indirect costs associated with all the interconsultations between PC and a CS of a tertiary hospital were analyzed under a universal single act model versus a prior e-consultation model that selected patients who would later attend the single-act consultation. The cost of pollution from private motor vehicle travel by road has been analyzed with a Cobb–Douglas cost function. Results: The total cost per patient, including the costs associated with death, represented a saving in the model with e-consultation of 25.6%. The economic value for the reduction of contamination would be EUR 12.86 per patient. Conclusions: The introduction of e-consultation in the outpatient management of patients referred from PC to a CS, helps to reduce direct and indirect costs for the patient and the Health Care System. The cost of pollution associated with the trips explains the total cost to a greater extent, except for the first face-to-face consultation.

Objective: This article examines what the adoption and use of advanced medical technologies – computed tomography (CT) and magnetic resonance imaging (MRI) – by public hospitals depend on and to what extent. Methods: From a sample of panel data for all public hospitals in the health service of Galicia (a subregion of the Galicia-North of Portugal Euroregion) for the 2010–2017 period, we grouped explanatory variables into inputs (resources), outputs (activities) and socio-demographic variables. Factor analysis was used to reduce as much as possible the number of analysed variables, discriminant analysis to examine the technologies adoption decision, and multiple regression analysis to investigate their use. Results: Factor analysis identified motivators on adoption and use of CT and MRI medical technologies as follows: hospital inputs/outputs (Factor 1); radiology studies and adoption of CT by public hospitals (Factor 2); research/teaching role and big-ticket diagnostic and therapeutic (lithotripsy) technologies (Factor 3); number of transplants (Factor 4); cancer diagnosis/treatment (Factor 5); and catchment area geographical dispersion (Factor 6). Cronbach’s alpha of 0.881 indicated an acceptable degree of reliability of the factor variables. Regarding adoption of these technologies, Factor 1 is the most influential, explaining 37% of the variance and showing adequate global internal consistency, whereas Factor 2 is limited to 13% of the variance. In the discriminant analysis, values for Box’s M test and canonical correlations such as Wilks’s lambda for the two technologies underpin the reliability and predictive capacity of the discriminant equations. Finally, and according to the regression analysis, the factor with the greatest influence on CT and MRI use is Factor 2, followed by Factors 1 and 3 in the case of CT use, and Factors 3 and 5 in the case of MRI use. Conclusion: CT and MRI adoption by public hospitals is mainly determined by hospital inputs and outputs. However, the use of both medical technologies is mainly influenced by conventional radiology studies and CT adoption. These results suggest that both choices – adoption and use of advanced medical technology – may be separate decisions as they are taken possibly by different people (the former by managers and policymakers and the latter by physicians).