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The purpose of this paper is to establish the value of clinical genetic diagnostics in the lives of people with an intellectual disability (ID), their families, and their primary and professional caregivers. It has been shown that psychologists are more likely to make use of the opportunities offered by clinical genetic diagnostics if they have seen the psychological benefits in their own practice. Moreover, this paper aims to promote the practice of informing people with ID, their families, and other caregivers regarding the current technological advances in genetic diagnostics, thereby allowing these patients to decide for themselves whether to utilise these opportunities.

The authors report four case studies in which the psychosocial value to each patient is pivotal.

In these four cases, it is clear the medical model can augment the social model by providing an interpretation of its meaningfulness in the lives of the people concerned.

Case studies alone can have limited scientific significance. This approach examining the significance of clinical genetic diagnosis should be studied further in larger groups.

It is hoped that psychologists and other professional caregivers will become enthused about the value of clinical genetic diagnostics and will choose to discuss the option of referral for clinical genetic diagnostics with their patients more often.

People with an ID who are seeking mental health care, and their caregivers, should be given the opportunity to take part in the decision regarding whether to use clinical genetic diagnostics, which may even have a destigmatising effect.

Quality of life may improve for people with an ID seeking mental healthcare and for their caregivers as well by opening up discussion regarding the opportunities presented by clinical genetic diagnostics. The fact that people are able to make their own choices based on their own considerations can have a destigmatising effect.

An important current trend in health care is the move toward personalized medicine. Personalized medicine includes diagnostic and therapeutic interventions, with risk defined through genetics. The key paradigm shift brought about by the advent of personalized medicine is the increased use of in vitro genomic diagnostics. These tests offer the potential of being able to predict which patients are likely to respond to a particular drug, or which patients are likely to develop adverse reactions to a drug. The focus of this paper is the use of genomic diagnostics, and how the increasing development and translation into clinical practice of diagnostic – drug combination products will be adopted into health care delivery. The meaning of value and how to measure it is considered from different perspectives. A novel framework for evaluating the value of genomic diagnostics is proposed. Finally, the implications for regulatory approval and policy are discussed using an illustrative case study.

This chapter explores the rise in genetic approaches to health disparities at the turn of the twenty-first century.

Analysis of public health policies, genome project records, ethnography of project leaders and leading genetic epidemiologists, and news coverage of international projects demonstrates how the study of health disparities and genetic causes of health simultaneously took hold just as the new field of genomics and matters of racial inequality became a global priority for biomedical science and public health.

As the U.S. federal government created policies to implement racial inclusion standards, international genome projects seized the study race, and diseases that exhibit disparities by race. Genomic leaders made health disparities research a central feature of their science. However, recent attempts to move toward analysis of gene-environment interactions in health and disease have proven insufficient in addressing sociological contributors to health disparities. In place of in-depth analyses of environmental causes, pharmacogenomics drugs, diagnostics, and inclusion in sequencing projects have become the frontline solutions to health disparities.

The chapter argues that genetic forms of medicalization and racialization have taken hold over science and public health around the world, thereby engendering a divestment from sociological approaches that do not align with the expansion of genomic science. The chapter thus contributes to critical discussions in the social and health sciences about the fundamental processes of medicalization, racialization, and geneticization in contemporary society.

This chapter proposes an optimized innovative information technology as a means for achieving operational functionalities of real-time portable electronic health records, system interoperability, longitudinal health-risks research cohort and surveillance of adverse events infrastructure, and clinical, genome regions – disease and interventional prevention infrastructure. In application to the Dod-VA (Department of Defense and Veteran's Administration) health information systems, the proposed modernization can be carried out as an “add-on” expansion (estimated at $288 million in constant dollars) or as a “stand-alone” innovative information technology system (estimated at $489.7 million), and either solution will prototype an infrastructure for nation-wide health information systems interoperability, portable real-time electronic health records (EHRs), adverse events surveillance, and interventional prevention based on targeted single nucleotide polymorphisms (SNPs) discovery.

Describes Myriad Genetics and its struggle to develop a genetic testing service while facing challenges from competitors and activist organizations. After Myriad's discovery of the BRCA gene, capable of genetic testing for breast cancer in women, Myriad needed to choose a strategy to provide this service to the public. With several major competitors offering similar services, intense media scrutiny, and a charged activist and political climate, a poor Myriad decision could have major repercussions.

Big Data analysis is one of the key challenges to the provision of health care to emerge in the last few years. This challenge has been spearheaded by the huge interest in the “4Ps” of health care (predictive, preventive, personalized, and participatory). Big Data offers striking development opportunities in health care and life sciences. Healthcare research is already using Big Data to analyze the spatial distribution of diseases such as diabetes mellitus at detailed geographic levels. Big Data is also being used to assess location-specific risk factors based on data of health insurance claims. Other studies in systems medicine utilize bioinformatics approaches to human biology which necessitate Big Data statistical analysis and medical informatics tools. Big Data is also being used to develop electronic algorithms to forecast clinical events in real time, with the intent to improve patient outcomes and thus reduce costs.

Yet, this Big Data era also poses critically difficult ethical challenges, since it is breaking down the traditional divisions between what belongs to public and private domains in health care and health research. Big Data in health care raises complex ethical concerns due to use of huge datasets obtained from different sources for varying reasons. The clinical translation of this Big Data is thus resulting in key ethical and epistemological challenges for those who use these data to generate new knowledge and the clinicians who eventually apply it to improve patient care.

Underlying this challenge is the fact that patient consent often cannot be collected for the use of individuals’ personal data which then forms part of this Big Data. There is also the added dichotomy of healthcare providers which use such Big Data in attempts to reduce healthcare costs, and the negative impact this may have on the individual with respect to privacy issues and potential discrimination.

Big Data thus challenges societal norms of privacy and consent. Many questions are being raised on how these huge masses of data can be managed into valuable information and meaningful knowledge, while still maintaining ethical norms. Maintaining ethical integrity may lack behind in such a fast-changing sphere of knowledge. There is also an urgent need for international cooperation and standards when considering the ethical implications of the use of Big Data-intensive information.

This chapter will consider some of the main ethical aspects of this fast-developing field in the provision of health care, health research, and public health. It will use examples to concretize the discussion, such as the ethical aspects of the applications of Big Data obtained from clinical trials, and the use of Big Data obtained from the increasing popularity of health mobile apps and social media sites.

Child welfare services (CWSs) globally continue to absorb high rates of children living with or suspected of fetal alcohol spectrum disorder (FASD). Such high prevalence rates render CWS with major ethical and moral dilemmas of meeting complex needs. Currently, many jurisdictions are challenged by diagnostic capacity and cost implications of formal FASD diagnosis. This paper aims to recommend a screening protocol to address management gap between FASD initial presentation and formal diagnosis.

This is a follow-up paper from a grounded-theory study of a sample (N = 18) of child welfare social workers (CWSWs), allied health professionals and foster parents. A stepwise protocol was developed through systematical interpretation of the final data.

The application of a five-step screening protocol would greatly support CWSW in meeting the needs of children with suspected FASD. This CWSWs-led assessment model incorporates a clinical evaluation to exclude neurodevelopmental conditions caused by known genetic disorders, followed by behavioral and neurocognitive psychosocial assessments.

This study had several limitations. Firstly, as a specific social work-based sample, it is not necessarily representative of the wider population of social workers globally due to different cultural responses to FASD in CWSs. The transferability of findings will have to be considered due to cultural variations concerning FASD.

By offering a management and nonlabeling approach, this five-step screening protocol offers a delineated pathway for CWSW and addresses the major professional frustrations while seeking to plan safe care for a child suspected of having FASD.

The research offers a pragmatic low-cost to society to alleviate the mounting social and monetary implications of FASD. A large percentage of children impacted by prenatal alcohol exposure do not qualify under formal clinical diagnostic guidelines. Leaving these children without intervention is problematic. The recommendation of this study addresses this critical gap in services. The primary aim is to alleviate the burden on this cohort of vulnerable children by offering nonlabeling neurodevelopmental screening.

The direct implications of FASD and how it impacts CWS are well documented. However, few studies focus on the critical interface of FASD and the role of CWSW responsible for planning their safe care. This paper offers a novel pragmatic and functional multistep protocol to aid CWSW in this complex area of practice.

In February this year the sequence of the human genome was published, opening a new chapter in medicine. Soon genetic testing will be at the heart of diagnosis, epidemiology, drug development and even regenerative medicine. Before we are born there will be new opportunities to remedy genetic defects, and afterwards to make almost lifelong prognoses. The debate will intensify on the use of human embryos in medical research, while the prospect of human cloning will fascinate some scientists and horrify others. Europe needs to be in the vanguard of this new industrial revolution, but a host of ethical concerns must first be addressed – because genomics is as much about privacy as Petri dishes.

Depressive disorders are a focus of growing social and economic concern. While antidepressant medications are widely accepted, they are ineffective for nearly 40% of users, and cause numerous adverse drug reactions. The pharmacogenomics of depression attempts to better understand the role of genetic variation in antidepressant metabolism in the hope of improving drug efficacy and tolerability. However, the development and delivery of genome‐based antidepressants face many hurdles. In this paper we provide an overview of the potential impact of the pharmacogenomics of depression on public mental health care by focusing on the social and ethical issues at stake. These include questions about genetic testing, informed consent, drug access, and market fragmentation. We end the paper with a brief discussion of the wider context and how the pharmacogenomics of depression relates to broader trends in psychiatry and biomedicine.

India's diagnostics business valued at USD 10 billion was growing at 20% annually. Several players with different business models competed. Dr. Lal PathLabs, the world's largest histopathology centre led with a menu of 3,500 tests, 1,600 collection centres and 7,000 pick-up points. Its Initial Public Offer had been oversubscribed 33.41 times and the team at Dr. Lal PathLabs was excited about expanding its international footprint. Two overseas companies were incorporated in Netherlands and Nepal. Yet, there were enormous unmet needs in India alongside potential for public-private partnerships. Trade-offs over portfolio choice and regional versus international footprint needed thinking through.