Scale-up of Digital Innovations in Health Care: Expert Commentary on Enablers and Barriers.

Health care delivery is undergoing a rapid change from traditional processes toward the use of digital health interventions and personalized medicine. This movement has been accelerated by the COVID-19 crisis as a response to the need to guarantee access to health care services while reducing the risk of contagion. Digital health scale-up is now also vital to achieve population-wide impact: it will only accomplish sustainable effects if and when deployed into regular health care delivery services. The question of how sustainable digital health scale-up can be successfully achieved has, however, not yet been sufficiently resolved. This paper identifies and discusses enablers and barriers for scaling up digital health innovations. The results discussed in this paper were gathered by scientists and representatives of public bodies as well as patient organizations at an international workshop on scaling up digital health innovations. Results are explored in the context of prior research and implications for future work in achieving large-scale implementations that will benefit the population as a whole.

Evaluation is Key: Providing Appropriate Evaluation Measures for Participatory and User-Centred Design Processes of Healthcare IT.

INTRODUCTION: The increasing availability of healthcare IT has the potential to improve the integration of health services. Existing projects developing healthcare IT mostly disregard the potential and importance of incorporating user feedback and proper evaluation measures to gain user feedback throughout the development process. We therefore provide methodological guidance for evaluation in a stepwise user-centred design process. METHODS: Based on a literature review we propose adequate methods for data collection in each phase of participatory and user-centred healthcare IT development. In order to provide an orientation within the plethora of development processes used in practice, we consolidate a generic blueprint process from the literature review. The applicability of our methodological guidance is shown in three diverse use cases from the field of integrated care. RESULTS: From 14 literature items, we identified common evaluation methods including, among others, interviews, focus groups, and surveys. These methods can be associated to six typical development phases that could be derived from research: State of the Art Research, Requirement Analysis, Conceptual Prototype, Preliminary Prototype, Full Prototype, Full Application. The use cases demonstrate the value of qualitative methods and mixed methods designs. DISCUSSION: Our methodological guidance has proven applicable for designing healthcare IT solutions from scratch - both for patient and professional settings - and to develop a platform for combining existing component-based solutions. In integrated care settings, where a wide range of stakeholders with multiple needs exist, we thus provide methodological guidance on how to involve users in the development process. CONCLUSION: Our stepwise methodological guidance helps to design and properly evaluate healthcare IT solutions, which meet the user needs and requirements, for integrated care settings.

Automated Engineering for Health Smart Homes: Find a Way in the Jungle of Assistance Systems.

Health Smart Homes are a promising part of digital personalized health care. However, engineering of the underlying residential assistance systems is a complex process that needs to be supported by computer-based design tools. This paper presents a formal definition for the engineering task and proposes a methodology for model-driven design process automation, that is implemented in a web-based pilot application. Using this approach for design support, the challenge to efficiently compose personalized assistance systems for patients can be coped with in the future, which reduces a major barrier for smart home assistance applications.

Defining and Delimitating Telemedicine and Related Terms - An Ontology-Based Classification.

The way health care is delivered changes continuously and is increasingly supported by digital technologies, such as telemedicine. Many terms in that context exist, which are not defined consistently and therefore used ambiguously. This makes it difficult to assess the evidence base. Ontologies bring structure and clarity to the discourse around telemedicine and related terms. We use this tool to provide definitions of relevant terms and show their interrelations. The results provided will be applied to different case studies to show their applicability. We aim to provide a more evidence-based understanding of relevant terms in digital health.

Identifying Obstacles and Research Gaps of Telemedicine Projects: Approach for a State-of-the-Art Analysis.

This paper presents an approach for an evaluation of finished telemedicine projects using qualitative methods. Telemedicine applications are said to improve the performance of health care systems. While there are countless telemedicine projects, the vast majority never makes the threshold from testing to implementation and diffusion. Projects were collected from German project databases in the area of telemedicine following systematically developed criteria. In a testing phase, ten projects were subject to a qualitative content analysis to identify limitations, need for further research, and lessons learned. Using Mayring's method of inductive category development, six categories of possible future research were derived. Thus, the proposed method is an important contribution to diffusion and translation research regarding telemedicine, as it is applicable to a systematic research of databases.