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The papers of this thesis are not available in Munin. Paper 1. Silsand, L., Ellingsen, G. (2014). Generification by Translation: Designing Generic Systems in Context of the Local. Available in: Journal of Association for Information Systems, vol. 15(4): 3. Paper 2. Christensen, B., Silsand, L., Wynn, R. and Ellingsen, G. (2014). The biography of participation. In Proceedings of the 13th Participatory Design Conference, 6-10 Oct. Windhoek, Namibia. ACM Digital Library. Paper 3. Silsand, L. and Ellingsen, G. (2016). Complex Decision-Making in Clinical Practice. In: Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing (CSCW '16). ACM Digital Library. ISBN: 978-1-4503-3592-8. Paper 4: Silsand, L., Ellingsen, G. (2017). Governance of openEHR-based information Infrastructures. (Manuscript). Paper 5. Silsand, L. (2017). The 'Holy Grail' of Interoperability of Health Information Systems: Challenges and Implications. Available in: Stigberg S., Karlsen J., Holone H., Linnes C. (eds) Nordic Contributions in IS Research. SCIS 2017. Lecture Notes in Business Information Processing, vol 294. Springer, Cham. ; This thesis provides empirical insights about socio-technical interdependencies affecting the making and scaling of an Information Infrastructure (II) for healthcare based on the development of large-scale Electronic Patient Records. The Ph.D. study is an interpretive case study, where the empirical data has been collected from 2012 to 2017. In most developed countries, the pressures from politicians and public in general for better IT solutions have grown enormously, not least within Electronic Patient Record (EPR) systems. Considerable attention has been given to the proposition that the exchange of health information is a critical component to reach the triple aim of (1) better patient experiences through quality and satisfaction; (2) better health outcomes of populations; and (3) reduction of per capita cost of health care. A promising strategy for dealing with the challenges of accessibility, efficiency, and effective sharing of clinical information to support the triple aim is an open health-computing platform approach, exemplified by the openEHR approach in the empirical case. An open platform approach for computing EPR systems addresses some vital differences from the traditional proprietary systems. Accordingly, the study has payed attention to the vital difference, and analyze the technology and open platform approach to understand the challenges and implications faced by the empirical process. There are two main messages coming out of this Ph.D. study. First, when choosing an open platform approach to establish a regional or national information infrastructure for healthcare, it is important to define it as a process, not a project. Because limiting the realization of a large-scale open platform based infrastructure to the strict timeline of a project may hamper infrastructure growth. Second, realizing an open platform based information infrastructure requires large structural and organizational changes, addressing the need for integrating policy design with infrastructure design.

Title page -- Preface -- Contents -- Section 1: Advanced Medical Information Society -- The 21s t Century Telemedical Information Society -- Elements of Success in Telemedicine Programs: Advice from Telemedicine Leaders -- Real Applications of Patient-Related Telemedical Services -- Telemedicine: Medicine + Telecommunications -- Polish Reality and Prospects in the Context of Telematic Applications -- Internet and Medical Service Chains -- A Framework for the Security of Telemedical Services -- Virtual Medical Worlds - The Foundation for a Telemedical Information Society -- Establishing a Pilot ITIS - International Telemedical Information Society -- ITIS'98 - Seeds for the New Telemedical Information Society -- Section 2: Compunetics -- High Performance Distributed Computing: An Introduction -- Making Large-scale Telemedicine Work: A Computational Infrastructure for Telemedicine -- Ultrasonic Diffraction Tomography - An Application Connecting High Performance Computing Centers with Clinical Environment -- High Performance Computing and Networking in Medical Imaging Applications -- Tumor Growth Simulation and Visualization: a Review and a Web-based Paradigm -- Simulation and Visualisation in Medical Diagnosis: Perspectives and Computational Requirements -- Section 3: Telemedical Informatics -- Teaching and Learning with Virtual Reality -- Nursing Education for the Telemedical Society -- The Integration of Virtual Reality into a Web-based Telemedical Information Society -- Electronic Biomedical Library Image Service for Europe - Phase II ELISE II -- Intelligent Medical Systems -- Telecollaboration on EEG Data Analysis: a Pilot Experience in Italy -- Computer Aided Medical Diagnosis as a Knowledge Discovery Application -- Section 4: Medical Imaging Technologies -- Medical Image Compression -- Wavelet Based Image Compression for Telemedicine

Healthcare is an information problem needing an information solution using modern information technology. The traditional medical record does not suffice, but the new technologies of internet services do. Existing technologies can be combined for new methods of gathering and analyzing health information, via monitors using sensors and clusters using supercomputers. There is a way of utilizing both the electronic medical record of the past and the personalized genomic medicine of the future. It gathers information from all the sources affecting personal health: from the bodies of individuals to the societies of populations. Healthcare Infrastructure: Health Systems for Individuals and Populations describes the new healthcare infrastructure that will gather these personal health records from every individual and correlate each longitudinal record across whole populations. This book explains the problems of personal medicine and public health, then the solutions possible with information technology. Health determinants for individuals and populations are examined at length, along with present and future technologies to measure these. Computer analysis will produce clusters of persons with similar measurements of health status. The analysis discovers which persons have which outcomes and the management uses this knowledge to provide efficient healthcare. The new healthcare infrastructure will provide information for decision makers to effectively manage provider care and manage patient expectations. Thus, this book will be a key reference for all professionals working within the management of health, from informatician to healthcare executive, health information technologist to computer scientist, and physician to patient.

Blockchain has been hailed as the most disruptive technology of the next decade. One of the areas of immediate application is healthcare, where different types of blockchain applications could help streamline data sharing, protect patient privacy, and assist in the monitoring of drug shipments. This Article explores the first steps taken by healthcare companies in the United States to incorporate blockchain solutions into their business models. It then contrasts them to ongoing experiments in the European Union, with a focus on Sweden's adoption of CareChain (a national, interoperable blockchain health data platform) and Estonia's digitization of 95% of the country's health data.

Healthcare innovation is impeded by high costs, the need for diverse skillsets, and complex regulatory processes. The COVID-19 pandemic exposed critical gaps in the current framework, especially those lying at the boundary between cutting-edge academic research and industry-scale manufacturing and production. While many resource-rich geographies were equipped with the required expertise to solve challenges posed by the pandemic, mechanisms to unite the appropriate institutions and scale up, fund, and mobilize solutions at a time-scale relevant to the emergency were lacking. We characterize the orthogonal spatial and temporal axes that dictate innovation. Improving on their limitations, we propose a "pre-emptive innovation infrastructure" incorporating in-house hospital innovation teams, consortia-based assembly of expertise, and novel funding mechanisms to combat future emergencies. By leveraging the strengths of academic, medical, government, and industrial institutions, this framework could improve ongoing innovation and supercharge the infrastructure for healthcare emergencies.

Healthcare innovation is impeded by high costs, the need for diverse skillsets, and complex regulatory processes. The COVID-19 pandemic exposed critical gaps in the current framework, especially those lying at the boundary between cutting-edge academic research and industry-scale manufacturing and production. While many resource-rich geographies were equipped with the required expertise to solve challenges posed by the pandemic, mechanisms to unite the appropriate institutions and scale up, fund, and mobilize solutions at a time-scale relevant to the emergency were lacking. We characterize the orthogonal spatial and temporal axes that dictate innovation. Improving on their limitations, we propose a "pre-emptive innovation infrastructure" incorporating in-house hospital innovation teams, consortia-based assembly of expertise, and novel funding mechanisms to combat future emergencies. By leveraging the strengths of academic, medical, government, and industrial institutions, this framework could improve ongoing innovation and supercharge the infrastructure for healthcare emergencies.

The book Intelligent Healthcare: Infrastructure, Algorithms, and Management© cover a wide range of research topics on innovative intelligent healthcare solutions and advancements with the latest research developments. Data analytics are relevant for healthcare to meet many technical challenges and issues that need to be addressed to realize this potential. The advanced healthcare systems have to be upgraded with new capabilities such as data analytics, machine learning, intelligent decision making, and more professional services. The Internet of Things helps to design and develop intelligent healthcare solutions assisted by security, data analytics, and machine learning. This book will provide federated learning, Data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart healthcare. This book aims to attract works on multidisciplinary research spanning across computer science and engineering, environmental studies, services, urban planning and development, Healthcare, social sciences, and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative learning and computing solutions and big medical data-powered applications to cope with the real-world challenges for building smart healthcare sectors. Main Features: Ø Immersive technologies in healthcare Ø Internet of medical things Ø Federated learning algorithms Ø Explainable AI in Pervasive Healthcare Ø New management principles using biomedical data Ø Secured healthcare management systems This book aims to set up a better understanding of data scientists, researchers, and technologists under innovative digital health. The reader can find out existing research challenges, current market trends, and low-cost technologies to smoothly address the digital health issue

Recently there has been increased focus on the need to modernize the healthcare information infrastructure in the United States.1–4 The U.S. healthcare industry is by far the largest in the world in both absolute dollars and in percentage of GDP (more than $1.5 trillion, or 15 percent of GDP). It is also fragmented and complex. These difficulties, coupled with an antiquated infrastructure for the collection of and access to medical data, lead to enormous inefficiencies and sources of error. Consumer, regulatory, and governmental pressure drive a growing consensus that the time has come to modernize the U.S. healthcare information infrastructure (HII). While such transformation may be disruptive in the short term, it will, in the future, significantly improve the quality, expediency, efficiency, and successful delivery of healthcare while decreasing costs to patients and payers and improving the overall experiences of consumers and providers. The launch of a national health infrastructure initiative in the United States in May 2004-with the goal of providing an electronic health record for every American within the next decade-will eventually transform the healthcare industry in general, just as information technology (IT) has transformed other industries in the past. The key to this successful outcome will be based on the way we apply IT to healthcare data and the services delivered through IT. This must be accomplished in a way that protects individuals and allows competition but gives caregivers reliable and efficient access to the data required to treat patients and to improve the practice of medical science.

In Norway, the focus on interoperability and communication across healthcare practices has increased the need to connect ICT portfolios at different levels of healthcare, into large-scale information infrastructures (II). Governing healthcare practices is exceptionally complex, due to the diverging goals and policies of the heterogeneous actors involved. Establish well-functioning ICT governance organizations to handle these large infrastructures is therefore important. Using information infrastructure theory, and governance literature from the IS field, this paper contributes with empirical insight to the longitudinal and political process of establishing ICT governance in a healthcare context, reporting from one of Norway's largest health ICT projects, situated in the North Norway Regional Health Authority in 2012–2016. Our focus was on the following research questions: How does organizational politics shape the process of establishing an ICT governance organization in a heterogeneous healthcare environment, and what does it take to establish such ICT governance organization?