Inequities in Health Care Services Caused by the Adoption of Digital Health Technologies: Scoping Review

Abstract

Background Digital health technologies (ie, the integration of digital technology and health information) aim to increase the efficiency of health care delivery; they are rapidly adapting to health care contexts to provide improved medical services for citizens. However, contrary to expectations, their rapid adoption appears to have led to health inequities, with differences in health conditions or inequality in the distribution of health care resources among different populations. Objective This scoping review aims to identify and describe the inequities of health care services brought about by the adoption of digital health technologies. The factors influencing such inequities, as well as the corresponding countermeasures to ensure health equity among different groups of citizens, were also studied. Methods Primary studies and literature, including articles and reviews, published in English between 1990 and 2020 were retrieved using appropriate search strategies across the following three electronic databases: Clarivate Analytics’ Web of Science, PubMed, and Scopus. Data management was performed by two authors (RY and WZ) using Thomson Endnote (Clarivate Analytics, Inc), by systematically screening and identifying eligible articles for this study. Any conflicts of opinion were resolved through discussions with the corresponding author. A qualitative descriptive synthesis was performed to determine the outcomes of this scoping review. Results A total of 2325 studies were collected during the search process, of which 41 (1.76%) papers were identified for further analysis. The quantity of literature increased until 2016, with a peak in 2020. The United States, the United Kingdom, and Norway ranked among the top 3 countries for publication output. Health inequities caused by the adoption of digital health technologies in health care services can be reflected in the following two dimensions: the inability of citizens to obtain and adopt technology and the different disease outcomes found among citizens under technical intervention measures. The factors that influenced inequities included age, race, region, economy, and education level, together with health conditions and eHealth literacy. Finally, action can be taken to alleviate inequities in the future by government agencies and medical institutions (eg, establishing national health insurance), digital health technology providers (eg, designing high-quality tools), and health care service recipients (eg, developing skills to access digital technologies). Conclusions The application of digital health technologies in health care services has caused inequities to some extent. However, existing research has certain limitations. The findings provide a comprehensive starting point for future research, allowing for further investigation into how digital health technologies may influence the unequal distribution of health care services. The interaction between individual subjective factors as well as social support and influencing factors should be included in future studies. Specifically, access to and availability of digital health technologies for socially disadvantaged groups should be of paramount importance.

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