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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.

There is considerable heterogeneity between primary care systems that have evolved in individual national cultural environments. Models of Child Health Appraised (MOCHA) studied how the transfer of models or their individual components can be achieved across nations, using examples of combinations of settings, functions, target groups and tracer conditions. There are many factors that determine the feasibility of successful transfer of these from one setting to another, which must be recognised and taken into account. These include the environment of the care system, national policy-making and contextual means of directing population behaviour – in the form of penalties and incentives, which cannot be assessed or expected to work by means of rational actions alone. MOCHA developed a list of criteria to assess transferability, summarised in a population characteristics, intervention content, environment and transfer (PIET-T) process. To explore the process and means of transferability, we obtained consensus statements from the researchers on optimum model scenarios and conducted a survey of stakeholders, professionals and users of children’s primary care services that involved three specific health topics: vaccination coverage in infants, monitoring of a chronic or complex condition and early recognition of mental health problems. The results give insight into features of transferability – such as the availability and the use of guidelines and formal procedures; the barriers and facilitators of implementation and similarities and differences between model practices and the existing model of child primary care in the country. We found that successful transfer of an optimal model is impossible without tailoring the model to a specific country setting. It is vital to be aware of the sensitivity of the population and environmental characteristics of a country before starting to change the system of primary care.

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.

This chapter focuses on ways of giving voice to the survivors of institutional abuse and how their contribution can be capitalised in raising community awareness of this phenomenon. The collection of testimonies demonstrates that institutional abuse is a common and widespread phenomenon that in most cases remains unrevealed throughout the life course. The participatory research process we describe is part of an important social and clinical intervention developed in the framework of two projects. The chapter illustrates outputs and outcomes related to disclosure of institutional abuse and its long-term consequences, as well as the meaning and implications of collective trauma. Results confirm the need to promote the voice of survivors to build a new professional and community culture and sensitisation towards children's right to be heard as an essential instrument to prevent and detect institutional ill treatment. Participatory processes can overcome the resistance of individuals, professional communities and politicians to recognising the phenomenon, emphasising institutional responsibilities and the specific effects of a serious form of maltreatment that requires extraordinary and specific interventions in terms of intensity and flexibility. This chapter describes a fieldwork and research experience made possible thanks to a strong alliance with survivors who engaged in a process of reflection and theoretical elaboration that generated both social and clinical impacts.

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 aims to explore smart facilities services in the context of university campus by aiming to understand how the service development processes can be classified.

The qualitative study is based on literature review about smart facilities services and a case study about developing visualisation, data and smart service in one building in Finnish campus. The case study data were gathered by diverse methods and analysed by content analysis.

Three smart facilities service processes were identified: experience processes for users, data-based service processes and technology processes. All the processes require more than only technocratic approach.

Single case study without longitudinal data gathering is not strong in terms of generalisation.

The process classification can help different stakeholders to identify their role and tasks in smart facilities service development.

The research aims to understand how to develop smart services in addition to more investigated topic what the services include.

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.

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.