The coronavirus disease 2019 (COVID-19) pandemic has accumulated a mounting death toll and ravaged economies. Even with the presence of cutting-edge expertise and technologies, the virus has slipped through the cracks in our international defense and surveillance systems. It has exploited rifts in our social fabric while revealing perceptual fallacies arising from misinformation, in what the World Health Organization (WHO) has dubbed the COVID-19 “infodemic”. Many industries have been disrupted, and healthcare is no exception.

The high risk of viral transmission within healthcare settings has called for extensive re-organisation. This extends from the flow of human traffic within physical premises, to modifying clinical protocols based on patients’ clinical needs. The use of telemedicine became essential in many clinical settings, with non-urgent appointments either being rescheduled or shifted online. Also, physical touch points at healthcare front-lines had to be minimized as far as possible. Making matters worse, pockets of COVID-19 outbreaks led to an ever-shifting macrosystemic operating environment (i.e. re-lockdowns, revising of protocols, and redistribution of trained manpower). 

 In our recent systematic scoping review, published studies of digital health solutions from artificial intelligence (AI) to the internet of things (IoT) that were deployed globally in the first 6 months of COVID-19 are presented. Overarching trends and gaps in the evaluation of digital solutions for public health responses are identified, in relation to various technology domains (TDs) and relevant public health priorities set out by WHO. This highlighted the catalytic role of COVID-19 on digital health adoption, and provides a rapid reference for those seeking relevant digital health solutions based on a given public health goal, or academics looking to fill gaps in the literature with relevant research.

We found a maturing pool of evidence for telehealth supporting the clinical utility of virtual clinical services. Additionally, there was a substantial number of studies evaluating big data and artificial intelligence (AI) applications, although their methodological weaknesses limit their generalisability. In contrast, limited studies investigated other TDs such as the internet of things, digital platforms for communication (DC), digital solutions for data management (DM), and digital structural screening (DS). Interestingly, despite the small absolute number of studies investigating DCs, there was a relatively large proportion using pragmatic and prospective study designs, reflecting the prominence of DCs among COVID-19 responses and the interest in real-world investigations to evaluate their applications.

 It is clear that more robust evaluation of digital health applications, particularly for “hype” technologies such as AI, are needed to inform safe and effective implementation in clinical care. In fact, digital health solutions have not always been prominently applied in healthcare. Many were instead relegated or confined to pilots in the past, struggling to obtain a foothold among the multitude of competing priorities for healthcare administration. This is exemplified by the many descriptive reports exploring hybrid digital models of care piloted in the past, that have not been widely implemented until the current pandemic. These range from home-based monitoring to safely differ unnecessary follow-up appointments in patients with stable clinical condition, to stacked “pyramid” digital clinical services synergizing technology and providers to ensure patients receive the right care at the right time.

One silver lining was that the pandemic has aligned the priorities of stakeholders at every level in healthcare, presenting a huge impetus for adoption of digital health in various clinical contexts. However, fully realizing these benefits long-term will require addressing barriers to adoption through participatory research involving stakeholders including members of public. Also, addressing the unmet need for pragmatic evaluation of digital health solutions will go a long way to facilitate widespread adoption.

 Aside from the lack of robust validation for several digital health technology domains, major gaps in the literature were identified for certain public health applications of them. Particularly, there are limited scientific assessments of digital health solutions being applied at points of entry or for population surveillance. These require more research in addressing barriers to adoption such as privacy concerns and patient/provider acceptance through greater involvement of stakeholders for sustained adoption beyond COVID-19.

As we embark on 2021, the pandemic continues to present new challenges as we scramble to disseminate potential vaccine candidates. We also know that we cannot afford to let our guard down now, with many countries having learnt painful lessons from resurgences resulting in loss of lives and economic impact of re-lockdowns. Therefore, COVID-19 has highlighted the importance of capacity building by investing in digital infrastructure and managerial competencies for digital health. Our experience during COVID-19 has clearly launched the era of digital health within healthcare, but continued development and validation of these tools is critical to effectively capture their value within the health system, particularly when operational priorities revert after the pandemic.

Contributed by Rachel Marjorie Tseng and Dr. Dinesh Visva Gunasekeran.

Correspondence to mdcdvg@nus.edu.sg