Solving the Modeling Dilemma as a Foundation for Interoperability

Introduction: 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. Methods: The paper discusses classification systems for data models and enterprise business architectures and compares them with the ISO Reference Architecture. Results and Conclusions: Existing definitions, specifications and standards for data models enabling interoperability are analyzed, and their limitations are evaluated. Amendments to correctly use those models and to better meet the aforementioned challenges are offered

Challenges and Solutions for Designing and Managing pHealth Ecosystems

For improving quality and safety of healthcare as well as efficiency and efficacy of care processes, health systems turn toward personalized, preventive, predictive, participative precision medicine. The related pHealth ecosystem combines different domains represented by a huge variety of different human and non-human actors belonging to different policy domains, coming from different disciplines. Those actors deploy 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. Core challenge is the formal representation and management of multiple domains' knowledge. For correctly modeling such systems and their behavior, a system-oriented, architecture-centric, ontology-based, policy-driven approach is inevitable, thereby following established Good Modeling Best Practices. The ISO Interoperability Reference Architecture model and framework offers such approach. The paper describes and classifies the ongoing paradigm changes. It presents requirements and solutions for designing and implementing advanced pHealth ecosystems, thereby correctly adopting and integrating existing pHealth interoperability standards, specifications and projects

Interoperable EHR Systems – Challenges, Standards and Solutions

Background: Electronic Health Record Systems (EHRS) and Personal Health Record Systems (PHRS) are core components of infrastructure needed to run any health system. Objectives: As health systems undergo paradigm changes, EHRS and PHRS have to advance as well to meet the related interoperability challenges. Methods: The paper discusses EHR types, implementations and standards, starting with different requirements specifications, systems and systems architectures, standards and solutions. Results: Existing standards and specifications are compared with changing requirements, presenting weaknesses and defining the advancement of EHRS, architectures and related services, embedded in advanced infrastructure systems. Conclusion: Future EHR systems are components in a layered architecture with open interfaces. The need of verifying data models at business domains level is specifically highlighted. Such approach is enabled by the ISO Interoperability Reference Architecture of a systemoriented, architecture-centric, ontology-based, policy- driven approach, meeting good modeling best practices

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. 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.Peer reviewe

Knowledge Representation and Management Enabling Intelligent Interoperability – Principles and Standards

Based on the paradigm changes for health, health services and underlying technologies as well as the need for at best comprehensive and increasingly automated interoperability, the paper addresses the challenge of knowledge representation and management for medical decision support. After introducing related definitions, a system-theoretical, architecture-centric approach to decision support systems (DSSs) and appropriate ways for representing them using systems of ontologies is given. Finally, existing and emerging knowledge representation and management standards are presented. The paper focuses on the knowledge representation and management part of DSSs, excluding the reasoning part from consideration