Elements of Trust in Digital Health Systems: Scoping Review.

BACKGROUND: Information and communication technologies have long become prominent components of health systems. Rapid advances in digital technologies and data science over the last few years are predicted to have a vast impact on health care services, configuring a paradigm shift into what is now commonly referred to as digital health. Forecasted to curb rising health costs as well as to improve health system efficiency and safety, digital health success heavily relies on trust from professional end users, administrators, and patients. Yet, what counts as the building blocks of trust in digital health systems has so far remained underexplored. OBJECTIVE: The objective of this study was to analyze what relevant stakeholders consider as enablers and impediments of trust in digital health. METHODS: We performed a scoping review to map out trust in digital health. To identify relevant digital health studies, we searched 5 electronic databases. Using keywords and Medical Subject Headings, we targeted all relevant studies and set no boundaries for publication year to allow a broad range of studies to be identified. The studies were screened by 2 reviewers after which a predefined data extraction strategy was employed and relevant themes documented. RESULTS: Overall, 278 qualitative, quantitative, mixed-methods, and intervention studies in English, published between 1998 and 2017 and conducted in 40 countries were included in this review. Patients and health care professionals were the two most prominent stakeholders of trust in digital health; a third-health administrators-was substantially less prominent. Our analysis identified cross-cutting personal, institutional, and technological elements of trust that broadly cluster into 16 enablers (altruism, fair data access, ease of use, self-efficacy, sociodemographic factors, recommendation by other users, usefulness, customizable design features, interoperability, privacy, initial face-to-face contact, guidelines for standardized use, stakeholder engagement, improved communication, decreased workloads, and service provider reputation) and 10 impediments (excessive costs, limited accessibility, sociodemographic factors, fear of data exploitation, insufficient training, defective technology, poor information quality, inadequate publicity, time-consuming, and service provider reputation) to trust in digital health. CONCLUSIONS: Trust in digital health technologies and services depends on the interplay of a complex set of enablers and impediments. This study is a contribution to ongoing efforts to understand what determines trust in digital health according to different stakeholders. Therefore, it offers valuable points of reference for the implementation of innovative digital health services. Building on insights from this study, actionable metrics can be developed to assess the trustworthiness of digital technologies in health care.

Digital health: meeting the ethical and policy challenges.

Digital health encompasses a wide range of novel digital technologies related to health and medicine. Such technologies rely on recent advances in the collection and analysis of ever increasing amounts of data from both patients and healthy citizens. Along with new opportunities, however, come new ethical and policy challenges. These range from the need to adapt current evidence-based standards, to issues of privacy, oversight, accountability and public trust as well as national and international data governance and management. This review illustrates key issues and challenges facing the rapidly unfolding digital health paradigm and reflects on the impact of big data in medical research and clinical practice both internationally and in Switzerland. It concludes by emphasising five conditions that will be crucial to fulfil in order to foster innovation and fair benefit sharing in digital health.

What Is Trust? Ethics and Risk Governance in Precision Medicine and Predictive Analytics.

Trust is a ubiquitous term used in emerging technology (e.g., Big Data, precision medicine), innovation policy, and governance literatures in particular. But what exactly is trust? Even though trust is considered a critical requirement for the successful deployment of precision medicine initiatives, nonetheless, there is a need for further conceptualization with regard to what qualifies as trust, and what factors might establish and sustain trust in precision medicine, predictive analytics, and large-scale biology. These new fields of 21st century medicine and health often deal with the "futures" and hence, trust gains a temporal and ever-present quality for both the present and the futures anticipated by new technologies and predictive analytics. We address these conceptual gaps that have important practical implications in the way we govern risk and unknowns associated with emerging technologies in biology, medicine, and health broadly. We provide an in-depth conceptual analysis and an operative definition of trust dynamics in precision medicine. In addition, we identify three main types of "trust facilitators": (1) technical, (2) ethical, and (3) institutional. This three-dimensional framework on trust is necessary to building and maintaining trust in 21st century knowledge-based innovations that governments and publics invest for progressive societal change, development, and sustainable prosperity. Importantly, we analyze, identify, and deliberate on the dimensions of precision medicine and large-scale biology that have carved out trust as a pertinent tool to its success. Moving forward, we propose a "points to consider" on how best to enhance trust in precision medicine and predictive analytics.