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.

The telemedicine community readiness model-successful telemedicine implementation and scale-up.

To successfully scale-up telemedicine initiatives (TIs), communities play a crucial role. To empower communities fulfilling this role and increase end users' acceptance of TIs, support tools (from now on entitled artifacts) are needed that include specific measures to implement and scale up telemedicine. Addressing this need, the article introduces the Telemedicine Community Readiness Model (TCRM). The TCRM is designed to help decision-makers in communities to create a favorable environment that facilitates the implementation and scale-up of TIs. The TCRM is a practical tool to assess communities' readiness to implement TIs and identify aspects to improve this readiness. The development process follows a design-science procedure, which integrates literature reviews and semi-structured expert interviews to justify and evaluate design decisions and the final design. For researchers, the paper provides insights into factors that influence telemedicine implementation and scale-up (descriptive role of knowledge) on the community level. For practitioners, it provides a meaningful tool to support the implementation and scale-up of TIs (prescriptive role of knowledge). This should help to realize the potential of telemedicine solutions to increase access to healthcare services and their quality.

Sauerbruch, STARPAHC, and SARS: Historical Perspectives on Readiness and Barriers in Telemedicine.

Aim: Telemedicine is a promising solution to extend traditional health care services. Even though mainly discussed during the past two decades, its roots go back into the past century and even further, considering the use of bonfires to warn other villages of diseases. Insights from historical cases can therefore be useful for the ongoing discussion regarding the successful implementation of telemedicine. Subject and Methods: We analyzed three historical telemedicine cases (varying regarding time and place) and extracted their success factors and barriers as well as assessed their maturity by using the Telemedicine Community Readiness Model (TCRM). Evidence-based categories of success factors and barriers as well as the TCRM's dimensions were used as deductive categories to analyze the study material's content. Results: The analysis showed that the readiness for telemedicine is higher when the technology is the only option to access health care services. In all three cases, core readiness played a central role. However, the health sector, existing technology, and finance were barriers present at all times, while during pandemics, some barriers are only temporarily removed, for example, by putting legal issues on hold. The analyzed cases were all on lower levels of maturity as they mainly represent pilot tests or exceptional circumstances. Conclusion: Results indicate the important core functions in telemedicine initiatives as well as the diversity of their circumstances. Insights from such historical meta-perspectives can, for example, help to strengthen the sustainability of the increased use of telemedicine during the COVID-19 pandemic and scale up current telemedicine projects.

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.