The growth of data-collecting goods and services, such as ehealth and mhealth apps, smart watches, mobile fitness and dieting apps, electronic skin and ingestible tech, combined with recent technological developments such as increased capacity of data storage, artificial intelligence and smart algorithms, has spawned a big data revolution that has reshaped how we understand and approach health data. Recently the COVID-19 pandemic has foregrounded a variety of data privacy issues. The collection, storage, sharing and analysis of health- related data raises major legal and ethical questions relating to privacy, data protection, profiling, discrimination, surveillance, personal autonomy and dignity. This book examines health privacy questions in light of the General Data Protection Regulation (GDPR) and the general data privacy legal framework of the European Union (EU). The GDPR is a complex and evolving body of law that aims to deal with several technological and societal health data privacy problems, while safeguarding public health interests and addressing its internal gaps and uncertainties. The book answers a diverse range of questions including: What role can the GDPR play in regulating health surveillance and big (health) data analytics? Can it catch up with internet-age developments? Are the solutions to the challenges posed by big health data to be found in the law? Does the GDPR provide adequate tools and mechanisms to ensure public health objectives and the effective protection of privacy? How does the GDPR deal with data that concern children’s health and academic research? By analysing a number of diverse questions concerning big health data under the GDPR from various perspectives, this book will appeal to those interested in privacy, data protection, big data, health sciences, information technology, the GDPR, EU and human rights law.

This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.

The complexities of implementing the General Data Protection Regulation (GDPR) continue to grow as it progresses through new and ever-changing technologies, business models, codes of conduct, and decisions of the supervisory authorities, and the courts. This eminently practical guide to implementing the GDPR – written in an original, problem-solving style by a highly experienced data protection expert with equal knowledge of both law and technology – provides a step-by-step project management approach to building a GDPR-compliant data protection system, assessing, and documenting the risks and then implementing these changes through processes at the operational level. With detailed attention to case law (Member State, ECJ, and ECHR), especially where affecting high-risk areas that have attracted scrutiny, the guidance proceeds systematically through such topics and issues as the following: required documentation, policies, and procedures; risk assessment tools and analysis frameworks; children’s data; employee and health data; international transfers post-Schrems II; data subject rights including the right of access; data retention and erasure; tracking and surveillance; and effects of technologies such as artificial intelligence, biometrics, and machine learning. With its practical examples derived from the author’s experience in building GDPR-compliant software, as well as its analysis of case law and enforcement priorities, this incomparable guide enables company data protection officers and compliance staff to advise on key issues with full awareness of the legal and reputational risks and how to mitigate them. It is also sure to be of immeasurable value to concerned regulators and policymakers at all government levels. “…it's going to be the go to resource for practitioners.” Tom Gilligan, Data Protection Consultant, September 2021 "I purchased this book recently and I’m very glad I did. It’s the textbook I have been waiting for. As someone relatively new to data protection, I was finding it very difficult to find books on the practical side of data protection. This book is very clearly laid out with practical examples and case law given for each topic, which is immensely helpful. I would recommend it to any data protection practitioners." Jennifer Breslin, LLM CIPP/E, AIPP Member

Part I Setting the scene -- Introduction: Individual rights, the public interest and biobank research 4000 (8) -- Genetic data and privacy protection -- Part II GDPR and European responses -- Biobank governance and the impact of the GDPR on the regulation of biobank research -- Controller' and processor's responsibilities in biobank research under GDPR -- Individual rights in biobank research under GDPR -- Safeguards and derogations relating to processing for archiving purposes in the scientific purposes: Article 89 analysis for biobank research -- A Pan-European analysis of Article 89 implementation and national biobank research regulations -- EEA, Switzerland analysis of GDPR requirements and national biobank research regulations -- Part III National insights in biobank regulatory frameworks -- Selected 10-15 countries for reports: Germany -- Greece -- France -- Finland -- Sweden -- United Kingdom -- Part IV Conclusions -- Reflections on individual rights, the public interest and biobank research, ramifications and ways forward. .

Precision Public Health is a new and rapidly evolving field, that examines the application of new technologies to public health policy and practice. It draws on a broad range of disciplines including genomics, spatial data, data linkage, epidemiology, health informatics, big data, predictive analytics and communications. The hope is that these new technologies will strengthen preventive health, improve access to health care, and reach disadvantaged populations in all areas of the world. But what are the downsides and what are the risks, and how can we ensure the benefits flow to those population groups most in need, rather than simply to those individuals who can afford to pay? This is the first collection of theoretical frameworks, analyses of empirical data, and case studies to be assembled on this topic, published to stimulate debate and promote collaborative work.

This book provides expert advice on the practical implementation of the European Union’s General Data Protection Regulation (GDPR) and systematically analyses its various provisions. Examples, tables, a checklist etc. showcase the practical consequences of the new legislation. The handbook examines the GDPR’s scope of application, the organizational and material requirements for data protection, the rights of data subjects, the role of the Supervisory Authorities, enforcement and fines under the GDPR, and national particularities. In addition, it supplies a brief outlook on the legal consequences for seminal data processing areas, such as Cloud Computing, Big Data and the Internet of Things.Adopted in 2016, the General Data Protection Regulation will come into force in May 2018. It provides for numerous new and intensified data protection obligations, as well as a significant increase in fines (up to 20 million euros). As a result, not only companies located within the European Union will have to change their approach to data security; due to the GDPR’s broad, transnational scope of application, it will affect numerous companies worldwide.

The growth of data-collecting goods and services, such as ehealth and mhealth apps, smart watches, mobile fitness and dieting apps, electronic skin and ingestible tech, combined with recent technological developments such as increased capacity of data storage, artificial intelligence and smart algorithms, has spawned a big data revolution that has reshaped how we understand and approach health data. Recently the COVID-19 pandemic has foregrounded a variety of data privacy issues. The collection, storage, sharing and analysis of health- related data raises major legal and ethical questions relating to privacy, data protection, profiling, discrimination, surveillance, personal autonomy and dignity. This book examines health privacy questions in light of the General Data Protection Regulation (GDPR) and the general data privacy legal framework of the European Union (EU). The GDPR is a complex and evolving body of law that aims to deal with several technological and societal health data privacy problems, while safeguarding public health interests and addressing its internal gaps and uncertainties. The book answers a diverse range of questions including: What role can the GDPR play in regulating health surveillance and big (health) data analytics? Can it catch up with internet-age developments? Are the solutions to the challenges posed by big health data to be found in the law? Does the GDPR provide adequate tools and mechanisms to ensure public health objectives and the effective protection of privacy? How does the GDPR deal with data that concern children’s health and academic research? By analysing a number of diverse questions concerning big health data under the GDPR from various perspectives, this book will appeal to those interested in privacy, data protection, big data, health sciences, information technology, the GDPR, EU and human rights law.

New health technologies promise great things but they also pose significant challenges for governments, particularly around safety concerns, effectiveness, and value for money. This collection analyses the defining features of the relationship between EU law and new technologies, and the roles of risk, rights, ethics, and markets.

Mobile Health Technologies, also known as mHealth technologies, have emerged, amongst healthcare providers, as the ultimate Technologies-of-Choice for the 21st century in delivering not only transformative change in healthcare delivery, but also critical health information to different communities of practice in integrated healthcare information systems. mHealth technologies nurture seamless platforms and pragmatic tools for managing pertinent health information across the continuum of different healthcare providers. mHealth technologies commonly utilize mobile medical devices, monitoring and wireless devices, and/or telemedicine in healthcare delivery and health research. Today, mHealth technologies provide opportunities to record and monitor conditions of patients with chronic diseases such as asthma, Chronic Obstructive Pulmonary Diseases (COPD) and diabetes mellitus. The intent of this book is to enlighten readers about the theories and applications of mHealth technologies in the healthcare domain.

Updated as of August 2014, this practical book will demonstrate proven methods for anonymizing health data to help your organization share meaningful datasets, without exposing patient identity. Leading experts Khaled El Emam and Luk Arbuckle walk you through a risk-based methodology, using case studies from their efforts to de-identify hundreds of datasets. Clinical data is valuable for research and other types of analytics, but making it anonymous without compromising data quality is tricky. This book demonstrates techniques for handling different data types, based on the authors’ experiences with a maternal-child registry, inpatient discharge abstracts, health insurance claims, electronic medical record databases, and the World Trade Center disaster registry, among others. Understand different methods for working with cross-sectional and longitudinal datasets Assess the risk of adversaries who attempt to re-identify patients in anonymized datasets Reduce the size and complexity of massive datasets without losing key information or jeopardizing privacy Use methods to anonymize unstructured free-form text data Minimize the risks inherent in geospatial data, without omitting critical location-based health information Look at ways to anonymize coding information in health data Learn the challenge of anonymously linking related datasets