Background/Objectives: Health and social care systems around the globe are currently undergoing 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 contexts. This transformation is strongly supported by technologies such as micro- and nanotechnologies, advanced computing, artificial intelligence, edge computing, etc. Methods: To enable communication and cooperation between actors from different domains using different methodologies, languages, and ontologies based on different education, experiences, etc., we have to understand the transformed health ecosystem and all its components in terms of structure, function and relationships in the necessary detail, ranging from elementary particles up to the universe. In this way, we advance design and management of the complex and highly dynamic ecosystem from data to knowledge level. The challenge is the consistent, correct, and formalized representation of the transformed health ecosystem from the perspectives of all domains involved, representing and managing them based on related ontologies. The resulting business viewpoint of the real-world ecosystem must be interrelated using the ISO/IEC 21838 Top Level Ontologies standard. Thereafter, the outcome can be transformed into implementable solutions using the ISO/IEC 10746 Open Distributed Processing Reference Model. Results: The model and framework for this system-oriented, architecture-centric, ontology-based, policy-driven approach have been developed by the first author and meanwhile standardized as ISO 23903 Interoperability and Integration Reference Architecture. The formal representation of any ecosystem and its development process including examples of practical deployment of the approach, are presented in detail. This includes correct systems and standards integration and interoperability solutions. A special issue newly addressed in the paper is the correct and consistent formal representation Conclusions: of all components in the development process, enabling interoperability between and integration of any existing representational artifacts such as models, work products, as well as used terminologies and ontologies. The provided solution is meanwhile mandatory at ISOTC215, CEN/TC251 and many other standards developing organization in health informatics for all projects covering more than just one domain.
- Klíčová slova
- ecosystems, health and social care transformation, information modelling, knowledge representation and management, language types, ontologies, systems architecture,
- Publikační typ
- časopisecké články MeSH
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. For enabling communication and cooperation between actors from different domains using different methodologies, languages and ontologies based on different education, experiences, etc., we have to understand the transformed health ecosystems and all its components in structure, function and relationships in the necessary detail ranging from elementary particles up to the universe. That way, we advance design and management of the complex and highly dynamic ecosystem from data to knowledge level. The challenge is the consistent, correct and formalized representation of the transformed health ecosystem from the perspectives of all domains involved, representing and managing them based on related ontologies. The resulting business view of the real-world ecosystem must be interrelated using the ISO/IEC 21838 Top Level Ontologies standard. Thereafter, the outcome can be transformed into implementable solutions using the ISO/IEC 10746 Open Distributed Processing Reference Model. Model and framework for this system-oriented, architecture-centric, ontology-based, policy-driven approach have been developed by the first author and meanwhile standardized as ISO 23903 Interoperability and Integration Reference Architecture.
- Klíčová slova
- Ecosystems, Health and social care transformation, Information modelling, Knowledge representation and management, Language types, Ontologies, Systems architecture,
- MeSH
- individualizovaná medicína * MeSH
- lidé MeSH
- umělá inteligence MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
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. To guarantee consistent and conformant processes and outcomes, the specifications and principles must be based on international standards. A core standard for representing transformed health ecosystems and managing the integration and interoperability of systems, components, specifications, and artifacts is ISO 23903:2021, therefore playing a central role in this publication. Consequently, ISO/TC 215 and CEN/TC 251, both representing the international standardization on health informatics, declared the deployment of ISO 23903:2021 mandatory for all their projects and standards addressing more than one domain. The paper summarizes and concludes the first author's leading engagement in the evolution of pHealth in Europe and beyond over the last 15 years, discussing the concepts, principles, and standards for designing, implementing, and managing 5P medicine ecosystems. It not only introduces the theoretical foundations of the approach but also exemplifies its deployment in practical projects and solutions regarding interoperability and integration in multi-domain ecosystems. The presented approach enables comprehensive and consistent integration of and interoperability between domains, systems, related actors, specifications, standards, and solutions. That way, it should help overcome the problems and limitations of data-centric approaches, which still dominate projects and products nowadays, and replace them with knowledge-centric, comprehensive, and consistent ones.
- Klíčová slova
- 5P medicine, ecosystem, integration, interoperability, knowledge management, knowledge representation, modeling, system architecture,
- Publikační typ
- časopisecké články MeSH
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. The challenge is the understanding and the formal as well as consistent representation of the world of sciences and practices, i.e., of multidisciplinary and dynamic systems in variable context. This enables mapping between the different disciplines, methodologies, perspectives, intentions, languages, etc., as philosophy or cognitive sciences do. The approach requires the deployment of advanced technologies including autonomous systems and artificial intelligence. This poses important ethical and governance challenges. This paper describes the aforementioned transformation of health and social care ecosystems as well as the related challenges and solutions, resulting in a sophisticated, formal reference architecture. This reference architecture provides a system-theoretical, architecture-centric, ontology-based, policy-driven model and framework for designing and managing intelligent and ethical ecosystems in general and health ecosystems in particular.
- Klíčová slova
- architecture, ecosystems, health transformation, knowledge representation and management,
- Publikační typ
- časopisecké články MeSH
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. Summarizing the first author's Keynotes over the last 15 years of pHealth conferences, the paper discusses concepts, standards and principles of 5P medicine ecosystems including their design and implementation. Furthermore, a guidance to find and to deploy corresponding international standards in practical projects is provided.
- Klíčová slova
- 5P medicine, System architecture, ecosystem, integration, interoperability, knowledge management, knowledge representation, modeling,
- MeSH
- ekosystém * MeSH
- individualizovaná medicína * MeSH
- Publikační typ
- časopisecké články MeSH
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. In future, pHealth uses information systems that are highly distributed, dynamic, increasingly autonomous, multi-stakeholder data driven eco-system having ability to monitor anywhere person's regular life, movements and health related behaviours. Because privacy and trust are pre-requirements for successful pHealth, this development raises huge privacy and trust challenges to be solved. Researchers have shown that current privacy approaches and solutions used in pHealth do not offer acceptable level of privacy, and trust is only an illusion. This indicates, that today's privacy models and technology shall not be moved to the future pHealth. The authors have analysed interesting new privacy and trust ideas published in journals, and found that they seem to be effective but offer only a partial solution. To solve this weakness, the authors used a holistic system view to aspects impacting privacy and trust in pHealth, and created a template that can be used in planning and development future pHealth services. The authors also propose a tentative solution for future trustworthy pHealth. It combines privacy as personal property and trust as legal binding fiducial duty approaches, and uses a Blockchain-based smart contract solution to store person's privacy and trust requirements and service providers' promises.
- Klíčová slova
- Fiducial Duty, Privacy, Privacy law, Smart Contract, System view, Trust,
- MeSH
- důvěra MeSH
- lidé MeSH
- počítače do ruky MeSH
- počítače MeSH
- soukromí * MeSH
- zdravotní záznamy osobní * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
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. The authors have studied those challenges from different perspectives using existing literature and found that current security and privacy solutions are insufficient, and for the user it is difficult to know whom to trust, and how much. Furthermore, in today's widely used privacy approaches, such as privacy as choice or control and belief or perception based trust does not work in digital health ecosystems. The authors state that it is necessary to redefine the way privacy and trust are understood in health, to develop new legislation to support new privacy and approaches, and to force the stakeholders of the health ecosystem to make their privacy and trust practices and features of their information systems available. The authors have also studied some candidate solutions for security, privacy, and trust to be used in future health ecosystems.
- Klíčová slova
- ecosystem, personal health information, privacy, security, trust,
- Publikační typ
- časopisecké články MeSH
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. METHODS: Using the abstract presentation of any system by the universal type theory as well as universal logics and combining the resulting Barendregt Cube with parameters and the engineering approach of cognitive theories, systems theory, and good modeling best practices, this study argues for a generic reference architecture model moderating between the different perspectives and disciplines involved provide on that system. To represent architectural elements consistently, an aligned system of ontologies is used. RESULTS: The system-oriented, architecture-centric, and ontology-based generic reference model allows for re-engineering the existing and emerging knowledge representations, models, and standards, also considering the real-world business processes and the related development process of supporting IT systems for the sake of comprehensive systems integration and interoperability. The solution enables the analysis, design, and implementation of dynamic, interoperable multi-domain systems without requesting continuous revision of existing specifications.
- Klíčová slova
- 5P medicine, architecture, ecosystem, health transformation, integration, interoperability, knowledge representation and management, modeling,
- Publikační typ
- časopisecké články MeSH
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). The rapid development of micro- and nano-sensor technology and signal processing makes it possible for pHealth service provider to collect wide spectrum of personal health related information from vital signs to emotions and health behaviors. This development raises big privacy and trust challenges especially because in pHealth similarly to eCommerce and Internet shopping it is commonly expected that the user automatically trust in service provider and used information systems. Unfortunately, this is a wrong assumption because in pHealth's digital environment it almost impossible for the service user to know to whom to trust, and what the actual level of information privacy is. Therefore, the service user needs tools to evaluate privacy and trust of the service provider and information system used. In this paper, the authors propose a solution for privacy and trust as results of their antecedents, and for the use of computational privacy and trust. To answer the question, which antecedents to use, two literature reviews are performed and 27 privacy and 58 trust attributes suitable for pHealth are found. A proposal how to select a subset of antecedents for real life use is also provided.
- Klíčová slova
- antecedents, eCommerce, pHealth, privacy, trust,
- MeSH
- chorobopisy - počítačové systémy MeSH
- důvěra MeSH
- soukromí * MeSH
- zdravotní záznamy osobní * MeSH
- Publikační typ
- časopisecké články MeSH
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.
- Klíčová slova
- Artificial intelligence, Autonomous systems, Ethics, Healthcare transformation, Knowledge management, Knowledge representation, Learning, pHealth,
- MeSH
- individualizovaná medicína * MeSH
- lidé MeSH
- umělá inteligence * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
