JMIR Publications

ABSTRACT

Background:

Digital health technologies (i.e., the integration of digital technology and health information) are aimed at increasing the efficiency of healthcare delivery; they are rapidly adapting to healthcare contexts to provide improved medical services for citizens. Contrary to expectations, however, their rapid adoption appears to have led to health inequities, with differences in health conditions or inequality in the distribution of healthcare resources among different populations.

Objective:

This scoping review aims to identify and describe the health inequities of healthcare services brought about by the adoption of digital health technologies. The factors influencing such inequities, as well as corresponding countermeasures to ensure health equity between different groups of citizens, is also studied.

Methods:

Primary studies and literature, including articles and reviews, published in English between 1990 to 2020, were retrieved using appropriate search strategies across three electronic databases: Clarivate Analytics’ Web of Science, PubMed and Scopus. Data management was performed by two authors using Thomson Endnote by systematically screening and identifying eligible articles for this study. Those articles not fulfilling the eligibility criteria were excluded with justification. Any conflict in opinion was resolved through discussion with the corresponding author. Qualitative descriptive synthesis was performed to reach the outcomes of this scoping review.

Results:

In total, 2,325 studies were collected during the search process, from which 41 papers were identified for further analysis. The quantity of literature increased until 2016, with a peak being reached in 2020. The United States, the United Kingdom, and Norway ranked as the top three countries for publication output. Health inequities caused by the adoption of digital health technologies in healthcare services can be reflected in two dimensions, viz. the inability of citizens to obtain technology (e.g., no access to technology), and the different disease outcomes found among citizens under technical intervention measures (e.g., disease mortality). The factors which influenced inequities included age, race, region, economy, and education level, together with health conditions and eHealth literacy. Finally, government agencies and medical institutions (e.g., establish national health insurance), digital health technology providers (e.g., design high-quality tools), and healthcare service receivers (e.g., develop skills to access digital technologies) can all take actions to alleviate inequities in future, and examples of such actions are given in parentheses above.

Conclusions:

The application of digital health technology in healthcare services has brought inequities to some extent. However, existing research has certain flaws in its content. Findings provide a comprehensive starting point for future research allowing for further investigation into how digital health technologies may influence the unequal distribution of healthcare services. The interaction between individual subjective factors, as well as social support and influencing factors, should be included in future studies. In particular, access to and availability of digital health technologies for socially disadvantaged groups should be of paramount importance.