The Representational Challenge for Designing and Managing 5P Medicine Ecosystems.

Health and social care systems around the globe currently undergo a transformation towards personalized, preventive, predictive, participative precision medicine (5PM), considering the individual health status, conditions, genetic and genomic dispositions, etc., in personal, social, occupational, environmental and behavioral context. This transformation is strongly supported by technologies such as micro- and nanotechnologies, advanced computing, artificial intelligence, edge computing, etc.

Principles and Standards for Designing and Managing Integrable and Interoperable Transformed Health Ecosystems.

The advancement of sciences and technologies, economic challenges, increasing expectations, and consumerism result in a radical transformation of health and social care around the globe, characterized by foundational organizational, methodological, and technological paradigm changes. The transformation of the health and social care ecosystems aims at ubiquitously providing personalized, preventive, predictive, participative precision (5P) medicine, considering and understanding the individual's health status in a comprehensive context from the elementary particle up to society. For designing and implementing such advanced ecosystems, an understanding and correct representation of the structure, function, and relations of their components is inevitable, thereby including the perspectives, principles, and methodologies of all included disciplines.

Designing and Managing Advanced, Intelligent and Ethical Health and Social Care Ecosystems.

The ongoing transformation of health systems around the world aims at personalized, preventive, predictive, participative precision medicine, supported by technology. It considers individual health status, conditions, and genetic and genomic dispositions in personal, social, occupational, environmental and behavioral contexts. In this way, it transforms health and social care from art to science by fully understanding the pathology of diseases and turning health and social care from reactive to proactive.

Future pHealth Ecosystem-Holistic View on Privacy and Trust.

Modern pHealth is an emerging approach to collecting and using personal health information (PHI) for personalized healthcare and personalized health management. For its products and services, it deploys advanced technologies such as sensors, actuators, computers, mobile phones, etc. Researchers have shown that today's networked information systems, such as pHealth ecosystems, miss appropriate privacy solutions, and trust is only an illusion.

Privacy and Trust in pHealth - Past, Present and Future.

From beginning to today, pHealth has been a data driven service that collects and uses personal health information (PHI) for personal health services and personalized healthcare. As a result, pHealth services use intensively ICT technology, sensors, computers and mathematical algorithms. In past, pHealth applications were focused to certain health or sickness related problem, but in today they use mobile devices, wireless networks, Web-technology and Cloud platforms.

Standards and Principles to Enable Interoperability and Integration of 5P Medicine Ecosystems.

Health and social care ecosystems are currently a matter of foundational organizational, methodological and technological paradigm changes towards personalized, preventive, predictive, participative precision (5P) medicine. For designing and implementing such advanced ecosystems, an understanding and correct representation of structure, function and relations of their components is inevitable. To guarantee consistent and conformant processes and outcomes, the specifications and principles must be internationally standardized.

Privacy and Trust in eHealth: A Fuzzy Linguistic Solution for Calculating the Merit of Service.

The use of eHealth and healthcare services are becoming increasingly common across networks and ecosystems. Identifying the quality and health impact of these services is a big problem that in many cases it is difficult determine. Health ecosystems are seldom designed with privacy and trust in mind, and the service user has almost no way of knowing how much trust to place in the service provider and other stakeholders using his or her personal health information (PHI).

Transformed Health Ecosystems-Challenges for Security, Privacy, and Trust.

A transformed health ecosystem is a multi-stakeholder coalition that collects, stores, and shares personal health information (PHI) for different purposes, such as for personalized care, prevention, health prediction, precise medicine, personal health management, and public health purposes. Those services are data driven, and a lot of PHI is needed not only from received care and treatments, but also from a person's normal life. Collecting, processing, storing, and sharing of the huge amount of sensitive PHI in the ecosystem cause many security, privacy, and trust challenges to be solved.

Transformation of Health and Social Care Systems-An Interdisciplinary Approach Toward a Foundational Architecture.

Objective: For realizing pervasive and ubiquitous health and social care services in a safe and high quality as well as efficient and effective way, health and social care systems have to meet new organizational, methodological, and technological paradigms. The resulting ecosystems are highly complex, highly distributed, and highly dynamic, following inter-organizational and even international approaches. Even though based on international, but domain-specific models and standards, achieving interoperability between such systems integrating multiple domains managed by multiple disciplines and their individually skilled actors is cumbersome.

How a Service User Knows the Level of Privacy and to Whom Trust in pHealth Systems?

pHealth is a data (personal health information) driven approach that use communication networks and platforms as technical base. Often it' services take place in distributed multi-stakeholder environment. Typical pHealth services for the user are personalized information and recommendations how to manage specific health problems and how to behave healthy (prevention).

Autonomous Systems and Artificial Intelligence - Hype or Prerequisite for P5 Medicine?

For meeting the challenge of aging, multi-diseased societies, cost containment, workforce development and consumerism by improved care quality and patient safety as well as more effective and efficient care processes, health and social care systems around the globe undergo an organizational, methodological and technological transformation towards personalized, preventive, predictive, participative precision medicine (P5 medicine). This paper addresses chances, challenges and risks of specific disruptive methodologies and technologies for the transformation of health and social care systems, especially focusing on the deployment of intelligent and autonomous systems.

Privacy Is Dead - Solutions for Privacy-Enabled Collections and Use of Personal Health Information in Digital Era.

Today's digital information systems and applications collect every day a huge amount of personal health information (PHI) from sensor and surveillance systems, and every time we use personal computers or mobile phones. Collected data is processed in clouds, platforms and ecosystems by digital algorithms and machine learning. Pervasive technology, insufficient and ineffective privacy legislation, strong ICT industry and low political will to protect data subject's privacy have together made it almost impossible for a user to know what PHI is collected, how it is used and to whom it is disclosed.

Why Interoperability at Data Level Is Not Sufficient for Enabling pHealth?

Multidisciplinary and highly dynamic pHealth ecosystems according to the 5P Medicine paradigm require careful consideration of systems integration and interoperability within the domains knowledge space. The paper addresses the different aspects or levels of knowledge representation (KR) and management (KM) from cognitive theories (theories of knowledge) and modeling processes through notation up to processing, tooling and implementation. Thereby, it discusses language and grammar challenges and constraints, but also development process aspects and solutions, so demonstrating the limitation of data level considerations.

Autonomous Systems and Artificial Intelligence in Healthcare Transformation to 5P Medicine - Ethical Challenges.

The paper introduces a structured approach to transforming healthcare towards personalized, preventive, predictive, participative precision (P5) medicine and the related organizational, methodological and technological requirements. Thereby, the deployment of autonomous systems and artificial intelligence is inevitably. The paper discusses opportunities and challenges of those technologies from a humanistic and ethical perspective.

Health Information Systems in the Digital Health Ecosystem-Problems and Solutions for Ethics, Trust and Privacy.

Digital health information systems (DHIS) are increasingly members of ecosystems, collecting, using and sharing a huge amount of personal health information (PHI), frequently without control and authorization through the data subject. From the data subject's perspective, there is frequently no guarantee and therefore no trust that PHI is processed ethically in Digital Health Ecosystems. This results in new ethical, privacy and trust challenges to be solved.

How Does GDPR Support Healthcare Transformation to 5P Medicine?

Health systems advance towards personalized, preventive, predictive, participative precision (5P) medicine, considering the individual's health status, contexts and conditions. This results in fully distributed, highly dynamic, highly complex business systems and processes with multiple, comprehensively cooperating actors from different specialty and policy domains, using their specific methodologies, terminologies, ontologies, knowledge and skills. Rules and regulations governing the business process as well as the organizational, legal and individual conditions, thereby controlling the behavior of the system, are called policies.

Digital pHealth - Problems and Solutions for Ethics, Trust and Privacy.

The penetration of digital platforms and ecosystem based business-model together with the use algorithm and machine leaning are changing the environment where pHealth takes place. Traditional pHealth is changing to Digital pHealth. This development brings new ethical, privacy and trust problems which have to solve to make Digital pHealth successful.

Healthcare Transformation Towards Personalized Medicine - Chances and Challenges.

The paper introduces a structured approach to transforming healthcare towards personalized, preventive, predictive, participative precision (P5) medicine. It highlights the promising methodological paradigm changes, accompanied by related organizational and technological ones. In the latter context, the deployment of artificial intelligence and autonomous systems is crucial beside miniaturization and mobility.

A Model for Calculated Privacy and Trust in pHealth Ecosystems.

A pHealth ecosystem is a community of service users and providers. It is also a dynamic socio-technical system. One of its main goals is to help users to maintain their personal health status.

Modeling the Personal Health Ecosystem.

Complex ecosystems like the pHealth one combine different domains represented by a huge variety of different actors (human beings, organizations, devices, applications, components) belonging to different policy domains, coming from different disciplines, deploying different methodologies, terminologies, and ontologies, offering different levels of knowledge, skills, and experiences, acting in different scenarios and accommodating different business cases to meet the intended business objectives. For correctly modeling such systems, a system-oriented, architecture-centric, ontology-based, policy-driven approach is inevitable, thereby following established Good Modeling Best Practices. However, most of the existing standards, specifications and tools for describing, representing, implementing and managing health (information) systems reflect the advancement of information and communication technology (ICT) represented by different evolutionary levels of data modeling.

Ethics Certification of Health Information Professionals.

Objectives:  To provide a model for ensuring the ethical acceptability of the provisions that characterize the interjurisdictional use of eHealth, telemedicine, and associated modalities of health care deliveiy that are currently in place.

Methods:  Following the approach initiated in their Global Protection of Health Data project within the Security in Health Information Systems (SiHIS) working group of the International Medical Informatics Association (IMIA), the authors analyze and evaluate relevant privacy and security approaches that are intended to stem the erosion of patients' trustworthiness in the handling of their sensitive information by health care and informatics professionals in the international context.

Results:  The authors found that while the majority of guidelines and ethical codes essentially focus on the role and functioning of the institutions that use EHRs and information technologies, little if any attention has been paid to the qualifications of the health informatics professionals (HIPs) who actualize and operate information systems to deal with or address relevant ethical issues.

Data Modeling Challenges of Advanced Interoperability.

Progressive health paradigms, involving many different disciplines and combining multiple policy domains, requires advanced interoperability solutions. This results in special challenges for modeling health systems. The paper discusses classification systems for data models and enterprise business architectures and compares them with the ISO Reference Architecture.

Trust Model for Protection of Personal Health Data in a Global Environment.

Successful health care, eHealth, digital health, and personal health systems increasingly take place in cross-jurisdictional, dynamic and risk-encumbered information space. They require rich amount of personal health information (PHI). Trust is and will be the cornerstone and prerequisite for successful health services.

Trust - Essential Requirement and Basis for pHealth Services.

Trust is a social code and glue between persons and organizations in any business domain including health. pHealth is a complex concept that is built around health service providers, individuals and artefacts such as sensors, mobile devices, networks, computers, and software applications. It has many stakeholders such as organizations, persons, patients, customers, and tele-operators.

Requirements and Solutions for Personalized Health Systems.

Organizational, methodological and technological paradigm changes enable a precise, personalized, predictive, preventive and participative approach to health and social services supported by multiple actors from different domains at diverse level of knowledge and skills. Interoperability has to advance beyond Information and Communication Technologies (ICT) concerns, including the real world business domains and their processes, but also the individual context of all actors involved. The paper introduces and compares personalized health definitions, summarizes requirements and principles for pHealth systems, and considers intelligent interoperability.