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Purpose – This chapter reports on experts’ perspectives on health information technology (HIT) and how it may be used to improve health care quality and to lower health care costs.

Design/methodology/approach – Two roundtables were convened that focused on how to best use HIT to improve the quality of health care while ensuring it is accessible and affordable. Participants drew upon lessons learned in the Netherlands, the United States, and other countries.

Findings – The first roundtable focused on the use of (1) electronic health records (EHRs) by health care providers, (2) cloud computing for EHRs and health portals for consumers, and (3) data registries and networks for public health surveillance. The second roundtable highlighted (1) the rapid growth of personalized medicine, (2) the corresponding growth and sophistication of bioinformatics and analytics, (3) the increasing presence of mobile HIT, and (4) the disruptive changes in the institutional structures of biomedical research and development.

Practical implications – Governmental sponsorship of small pilot projects to solve practicable health system problems would encourage HIT innovation among key stakeholders. However, large-scale HIT solutions – developed through small pilot projects – should be pursued through public–private partnerships. At the same time, governments should speed up legislative and regulatory procedures to encourage adoption of cost-effective HIT innovations.

Social implications – Mobile HIT and social media are capable of fostering disease prevention and encouraging personal responsibility for improving or stabilizing chronic diseases.

Originality/value – Both health services researchers and policy makers should find this chapter of value since it highlights trends in HIT and addresses how health care quality may be improved while costs are contained.

This research explores the subjective health experiences of women incarcerated in a provincial detention center in Ottawa, Canada.

Narrative interviews conducted with 16 previously incarcerated women were analyzed to explore how health issues shaped their experiences in detention.

Women identified a set of practices and conditions that negatively impacted health, including the denial of medication, medical treatment, and healthcare, limited prenatal healthcare, and damaged health caused by poor living conditions.

Findings suggest that structural health problems emerge in penal environments where healthcare is provided by the same agency responsible for incarceration. The incompatibility between the mandates of incarceration and healthcare suggests that responsibility for institutional healthcare should be transferred to provincial healthcare bodies.

This research responds to the lack of research on carceral health experiences within both penal scholarship and medical sociology, particularly in relation to women and those confined in jails.

This book chapter focuses on firstly social innovation and tools used to address the social needs and foster social innovation initiatives. Looking at the world economic forum and how it supports the social innovations, currency swings, low paying jobs growing rapidly, rapid change and growth as a result of high volatility and high returns, respectively. Secondly looking at the emerging market brought about by the social innovations and how they interconnect. Leading innovation emerging market has three main industries semiconductors, fin-tech, and electric cars. It also looks at the significance of technology in the development of business emerging markets, the role of technology in the emerging market and activities over the decades. Small firms in emerging areas face three major challenges which technology might help overcome. The challenges are trust, sustainability, and network. The role of technology replacing analog chip used for power supply, sensors, wideband signal make up the large semiconductors in the United States replaced with digital chip such as logical operations, data storage, computer information management all this have given birth to artificial intelligence, autonomous machines, self-driving cars, supply-chain management, cloud computing, and software-as-a-service (SaaS) applications are all made possible by digital chips. These are also used for e-commerce, mobile payment, fine-tech, 5G telecom, health-care advancement, remote learning, online entertainment, and cloud computing. Technical advancements that has sparked a revolution that would be especially advantageous for emerging market and small-cap enterprises are the causes of these benefits of how it has affected countries such as Europe, the United States, China, and India to mention a few.

The health consequences of child labor may take time to manifest themselves. This study examines whether children who began working at a young age experience increased incidence of illness or physical disability as adults. When child labor and schooling are treated as chosen without consideration of unobserved abilities or health endowments, child labor appears to have small adverse effects on a wide variety of health measures. Some adverse health consequences such as heart disease or hypertension seem unlikely to be caused by child labor. However, when we allow unobserved health and ability endowments to alter the age of labor market entry and years of schooling completed, the joint effects of child labor and schooling on health become larger while the less plausible health consequences lose significance. Results imply that delaying entry into child labor while increasing time in school significantly lowers the probability of early onset of physical ailments such as back problems, arthritis, or reduced strength or stamina. However, our methods are not able to distinguish between the health impacts of child labor from the impacts of reduced time in school.

With the advent of Big Data, the ability to store and use the unprecedented amount of clinical information is now feasible via Electronic Health Records (EHRs). The massive collection of clinical data by health care systems and treatment canters can be productively used to perform predictive analytics on treatment plans to improve patient health outcomes. These massive data sets have stimulated opportunities to adapt computational algorithms to track and identify target areas for quality improvement in health care.

According to a report from Association of American Medical Colleges, there will be an alarming gap between demand and supply of health care work force in near future. The projections show that, by 2032 there is will be a shortfall of between 46,900 and 121,900 physicians in US (AAMC, 2019). Therefore, early prediction of health care risks is a demanding requirement to improve health care quality and reduce health care costs. Predictive analytics uses historical data and algorithms based on either statistics or machine learning to develop predictive models that capture important trends. These models have the ability to predict the likelihood of the future events. Predictive models developed using supervised machine learning approaches are commonly applied for various health care problems such as disease diagnosis, treatment selection, and treatment personalization.

This chapter provides an overview of various machine learning and statistical techniques for developing predictive models. Case examples from the extant literature are provided to illustrate the role of predictive modeling in health care research. Together with adaptation of these predictive modeling techniques with Big Data analytics underscores the need for standardization and transparency while recognizing the opportunities and challenges ahead.

Risk governance is being successfully inserted into scientific and political agendas as a way to understand and address complex problems, such as health problems that have both social and ecological dimensions. However, to date, the debate on risk governance has remained rather conceptual. This chapter addresses these lacunae through describing research that was conducted on the Flemish environmental health governance arrangement and draws on this empirical case study to suggest ways that risk governance can be put into practice.

The case study analysis was conducted through a mixed methods study that combined document analysis and data gathered through 22 in-depth interviews with environmental and health scientists as well as policymakers.

This research shows that the Flemish environmental health risk governance arrangement has succeeded in increasing the exchange of information between: (1) governments at a variety of levels; (2) scientists, policymakers and the general public and (3) environmental and public health civil servants. The analysis also provides insights into some shortcomings and makes recommendations for ameliorating this arrangement: (1) the integration of environmental health objectives into all relevant policy domains, (2) the need for additional research into environmental health indicators and (3) the facilitation of the co-production of knowledge and multi-actor governance.

Empirical contributions and analysis about risk governance and policy formation processes are not often conducted. The added value of this Flemish case study is that it presents an example of good practice from which lessons for future risk governance arrangements can be drawn.

Purpose – The purpose of this article is to investigate one core research question: How can health information technology (HIT) be assessed in a national health care system context?

Design/methodology – We examine this question by taking a systematic approach within a national care system, in which the purpose of HIT is to contribute to a common national health care system's goal: to promote population health in an efficient way. Based on this approach we first develop a framework and our criteria of assessment, and then using Taiwan as a case study, demonstrate how one can apply this framework to assess a national system's HIT. The five criteria we developed are how well does the HIT (1) provide accessible and accurate public health and health care information to the population; (2) collect and provide population health and health care data for government and researchers to analyze population health and processes and outcomes of health care services; (3) provide accessible and timely information that helps to improve provision of cost-effective health care at an institutional level and promotes system-wide efficiency; (4) minimize transaction and administrative costs of the health care system; and (5) establish channels for population participation in governance while also protecting individual privacy.

Findings – The results indicate that Taiwan has high levels of achievement in two criteria while falling short in the other three. Major lessons we learned from this study are that HIT exists to serve a health care system, and the national health care system context dictates how one assesses its HIT.

Originality/value – There is a large body of literature published on the implementation of HIT and its impact on the quality and cost of health care delivery. The vast majority of the literature, however, is focused on a micro institutional level such as a hospital or a bit higher up, on an HMO or health insurance firm. Few have gone further to evaluate the implementation of HIT and its impact on a national health care system. The lack of such research motivated this study. The major contributions of this study are (i) to develop a framework that follows systems thinking principles and (ii) propose a process through which a nation can identify its objectives for HIT and systematically assess its national HIT system. Using Taiwan's national health care system as a case study, this paper demonstrated how it can be done.