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In order to assess the state of health of Europe’s children, or to appraise the systems and models of healthcare delivery, data about children are essential, with as much precision and accuracy as possible by small group characteristic. Unfortunately, the experience of the Models of Child Health Appraised (MOCHA) project and its scientists shows that this ideal is seldom met, and thus the accuracy of appraisal or planning work is compromised. In the project, we explored the data collected on children by a number of databases used in Europe and globally, to find that although the four quinquennial age bands are common, it is impossible to represent children aged 0–17 years as a legally defined group in statistical analysis. Adolescents, in particular, are the most invisible age group despite this being a time of life when they are rapidly changing and facing increasing challenges. In terms of measurement and monitoring, there is little progress from work of nearly two decades ago that recommended an information system, and no focus on the creation of a policy and ethical framework to allow collaborative analysis of the rich anonymised databases that hold real-world people-based data. In respect of data systems and surveillance, nearly all systems in European society pay lip service to the importance of children, but do not accommodate them in a practical and statistical sense.

The paper aims to examine some economical, political and health system indicators on the transmission of the COVID-19 transmission within the national system. The main objective is to investigate what are the most effective indicators which have led to the declared numbers by countries.

This study combined multiple sets of data to describe best the economical status of the health system including the government spending on the health system to draw some conclusion regarding the behavior of the pandemic.

Complex emergencies and internal conflicts negatively affected the quality of the reported cases and the size of the pandemic. The health work force was the most determinant factor of the health system. It can sometimes be impossible to understand the epidemic only with epidemiological data or health system one; economical aspects of health system and political situation have to be added to the equation.

The research according to the authors’ knowledge is the most comprehensive comparison so far that investigate the non-covid aspects from a political side in particular in complex emergencies and war situation added health system indicators.

The 30 MOCHA (Models of Child Health Appraised) countries are diverse socially, culturally and economically, and differences exist in their healthcare systems and in the scope and role of primary care. An economic analysis was undertaken that sought to explain differences in child health outcomes between countries. The conceptual framework was that of a production function for health, whereby health outputs (or outcomes) are assumed affected by several ‘inputs’. In the case of health, inputs include personal (genes, health behaviours) and socio-economic (income, living standards) factors and the structure, organisation and workforce of the healthcare system. Random effects regression modelling was used, based on countries as the unit of analysis, with data from 2004 to 2016 from international sources and published categorisations of healthcare system. The chapter describes the data deficiencies and measurement conundrums faced, and how these were addressed. In the absence of consistent indicators of child health outcomes across countries, five mortality measures were used: neonatal, infant, under five years, diabetes (0–19 years) and epilepsy (0–19 years). Factors found associated with reductions in mortality were as follows: gross domestic product per capita growth (neonatal, infant, under five years), higher density of paediatricians (neonatal, infant, under five years), less out-of-pocket expenditure (neonatal, diabetes 0–19), state-based service provision (epilepsy 0–19) and lower proportions of children in the population, a proxy for family size (all outcomes). Findings should be interpreted with caution due to the ecological nature of the analysis and the limitations presented by the data and measures employed.

Under the Directive 2011/24/EU, medical tourism and cross-border health are interrelated terms regarding the freedom to move to get the most accessible medical treatment into EU Member State within the defined procedures for reimbursement. Little known empirically regarding the efficiency of the cross-border health/medical tourism industry. This study aims to measure its efficiency in Europe for the years 2010-2014, by using Data Envelopment Analysis (DEA).

Data obtained from OECD and the European Core Health Indicators (ECHI), which is collecting the data through Eurostat. Eurostat collects data on health-care activities and provides data on hospital discharges, including the hospital discharges of non-residents and these include hospital discharges of in-patients and day care patients. The analysis uses “DEA.P, 2.1 for windows” by Coelli (1996).

The results show that the Members States health systems were very efficient in handling non-residents in-patients; however, when managing day cases/outpatients, the efficiency scores dropped.

The findings would have significant associations affecting intentions to revisit clinics and the destination country. In addition, will be useful to those seeking a better understanding of the cross-border health and medical tourism industry efficiency.

Extending the findings of the European Commission report (2015c) by examining how well medical tourists are informed about the decision they are making, would be of perceived value. These are important indicators at European level by helping each Member State to measure its medical tourism services.

Evaluating primary care for children has not before been undertaken on a national level, and only infrequently on an international level, an adult-focused perspective is the norm. The Models of Child Health Appraised (MOCHA) project explored the evaluation of quality of primary care for children in a nationally comparable way, which recognises the influence of all components of child well-being and well-becoming. Using adult-focused metrics fails to account for children’s physical and psycho-social development at different ages, differences in health and non-health determinants, patterns of disease and risk factors and the stages of the life course. To do this, we attempted to identify comparable measures of child health in the European Union and European Economic Area countries, we aimed to perform a structural equation modelling technique to identify causal effects of certain policies or procedures in children’s primary care and we aimed to identify and interrogate large datasets for key tracer conditions. We found that the creation of comparative data for children and child health services remains a low priority in Europe, and the largely unmet need for indicators covering all the healthcare dimensions hampers development of evidence-based policy. In terms of the MOCHA project objective of appraising models of child primary health care, the results of this specific work show that the means of appraisal of system and service quality are not yet agreed or mature, as well as having inadequate data to fuel them.

Equity is an issue that pervades all aspects of primary care provision for children and as such is a recurring theme in the Models of Child Health Appraised project. All European Union member states agree to address inequalities in health outcomes and include policies to address the gradient of health across society and target particularly vulnerable population groups. The project sought to understand the contribution of primary care services to reducing inequity in health outcomes for children. We focused on some key features of inequity as they affect children, such as the importance of good health services in early childhood, and the effects of inequity on children, such as the higher health needs of underprivileged groups, but their generally lower access to health services. This indicates that health services have an important role in buffering the effects of social determinants of health by providing effective treatment that can improve the health and quality of life for children with chronic disorders. We identified common risk factors for inequity, such as gender, family situation, socio-economic status (SES), migrant or minority status and regional differences in healthcare provision, and attempted to measure inequity of service provision. We did this by analysing routine data of universal primary care procedures, such as vaccination, age at diagnosis of autism or emergency hospital admission for conditions that can be generally treated in primary care, against variables of inequity, such as indicators of SES, migrant/ethnicity or urban/rural residency. In addition, we focused on the experiences of child population groups particularly at risk of inequity of primary care provision: migrant children and children in the state care system.

This paper explores the relationship between health promotion and active aging among seniors in Malaysia. The specific objectives were to (1) identify the contributing factors for seniors undergoing full medical check-up and (2) to explore the association between selected active aging factors and health promotion behavior and beliefs.

The study used data from 662 seniors from three different states in Peninsular Malaysia. Logistic regression was used to identify significant determinants of full medical check-up, and chi-square statistics were used to explore the association of active aging and selected health promotion behavior and beliefs. Healthy aging was characterized by being employed or traveling outdoors for leisure.

Household income was found to be a significant barrier to seniors undergoing a full medical check-up. Overall, active seniors were more likely to have positive self-rated health, positive health responsibility and health promotion beliefs but were less likely to undergo a full medical check-up.

Given that cost of a medical check-up could be a barrier for seniors, authorities could consider subsidizing medical check-ups to promote early detection of disease. There is also a need for continuous effort to educate seniors on health risk factors and the importance of taking fuller responsibility for their own health.

This study examined the relationship between active aging and health promotion together, as both components are essential in enhancing the mental and physical well-being of seniors.

This study aims to develop a reliable and valid German/Deutsch version of the management standards indicator tool (MSIT-D) to broaden the pool of instruments available to practitioners and to support international collaborations regarding this workplace management issue.

The MSIT-D was translated from English to German, then its psychometric properties examined using data from British employees (n = 321) and German employees (n = 358). Confirmatory factor analyses (CFAs) were used to evaluate the internal structure and measurement invariance, and Cronbach’s alpha was used to assess internal consistency. Comparisons were made with the German language risk assessment tool Fragebogen zur Gefährdungsbeurteilung psychischer Belastungen (FGBU) to examine concurrent and incremental validity. Criterion validity was checked using established measures of work-related health.

The MSIT-D has an equivalent seven-factor structure (demands, control, managerial support, peer support, relationships, role and change) as the original; the analyses confirmed configural and metric measurement invariance with the original scale. The internal consistency of the scales ranged from 0.82 to 0.91. Regarding criterion validity, the MSIT-D was positively correlated with emotional exhaustion and psychosomatic complaints and negatively correlated with work engagement and workability. The analyses yielded meaningful correlations between the MSIT-D dimensions and the FGBU.

This is the first study to develop a German version of the MSIT and confirm metric measurement invariance. This will allow a comparison of MSIT scores with related constructs between German- and English-speaking samples. As a reliable and valid instrument for assessing work-related stressors, the outcome of this study presents opportunities for developing a unified surveillance system for work-related stress at the European level.

This paper aims to evaluate the technical efficiency of the health-care systems in 21 selected middle-income countries during the period (2000–2017) and determine the source of inefficiency whether it is transient (short run) or persistent (long run).

The study uses the stochastic frontier analysis technique through employing the generalized true random effects model which overcomes the drawbacks of the previously introduced stochastic frontier models and allows for the separation between unobserved heterogeneity, persistent inefficiency and transient inefficiency.

Persistent efficiency is lower than the transient efficiency; hence, there are more efficiency gains that can be made by the selected countries by adopting long-term policies that aim at reforming the structure of the health-care system in the less efficient countries such as South Africa and Russia. The most efficient countries are Vietnam, Mexico and China which adopted a social health insurance that covers almost the whole population with the aim of increasing access to health-care services. Also, decentralization in health-care has assisted in adopting health-care policies that are suitable for both the rural and urban areas based on their specific conditions and health-care needs. A key success in the implementation of the adopted long-term policies by those countries is the continuous monitoring and evaluation of their outcomes and comparing them with the predefined targets and conducting any necessary modifications to ensure their movement in the right path to achieve their goals.

Although several studies have evaluated the technical efficiency both across and within countries using non-parametric (data envelopment analysis) and parametric (stochastic frontier analysis) approaches, to the best of the authors’ knowledge, this is the first attempt to evaluate the technical efficiency of selected middle-income countries during the period (2000–2017) using the generalized true random effects stochastic frontier analysis model.

The Models of Child Health Appraised (MOCHA) project identified the different models of primary care that exist for children, examined the particular attributes that might be different from those directed at adults and considered how these models might be appraised. The project took the multiple and interrelated dimensions of primary care and simplified them into a conceptual framework for appraisal. A general description of the models in existence in all 30 countries of the EU and EEA countries, focusing on lead practitioner, financial and regulatory and service provision classifications, was created. We then used the WHO ‘building blocks’ for high-performing health systems as a starting point for identifying a good system for children. The building blocks encompass safe and good quality services from an educated and empowered workforce, providing good data systems, access to all necessary medical products, prevention and treatments, and a service that is adequately financed and well led. An extensive search of the literature failed to identify a suitable appraisal framework for MOCHA, because none of the frameworks focused on child primary care in its own right. This led the research team to devise an alternative conceptualisation, at the heart of which is the core theme of child centricity and ecology, and the need to focus on delivery to the child through the life course. The MOCHA model also focuses on the primary care team and the societal and environmental context of the primary care system.