What role do digital health technologies and health data exchange play in helping the global community in its fight against SARS-CoV-2 and other pressing global health challenges? foraus contributed to this debate by convening experts and the general public to a virtual reflection on the Covid-19 crisis and existing opportunities in the field of digital health through its Think Tank Talk event «Health Data Exchange in Times of Covid-19». The event brought a series of lessons, which we would like to share through this written contribution. Our key take-away: if necessary framework conditions and mechanisms are created, digital health technologies can and will unfold their full potential and play a facilitating role towards the achievement of universal health coverage by 2030.
The potential is immense: Digital and AI-driven technologies not only have the potential to facilitate the achievement of SDG n°3 and WHO flagship initiatives such as the «triple billion targets» in the long term, but also more immediately to fight the spread of Covid-19 through various means. Areas of application for these tools include health education for risk management, tracking & tracing of infected individuals and communities, effective and rapid research for a vaccine or effective treatments and outbreak prediction.
Many challenges remain: Yet there are several challenges that need to be addressed, which are not only of a technological, but also of a legal, political and, probably most importantly, ethical nature. Should health data be considered a global public good and be equitably accessible and if so, how do we achieve this? How can we ensure data safety, security and privacy? What is actually reliable data? While the Think Tank Talk dove into these highly relevant questions, the lack of concrete answers highlighted the need for policy-makers to address these pressing issues so that we are better prepared for the next global health crisis, have the necessary tools and resources to respond rapidly and can more generally address pressing global health challenges.
Global governance is needed: A strong and stable global governance framework, led by common legal instruments such as potential health data regulations, could be a way forward to ensure common understanding and rules in a crowded field bringing together stakeholders with sometimes very distinct interests. Yet, global governance also needs local ownership and perspectives if it is to be effectively implemented. Countries and regions should therefore also show political buy-in for the setup of a level playing field in digital health.
Multi-stakeholder platforms are essential: Multi-stakeholder cooperation and breaking down silos is key to ensure that not only states, but also actors and initiatives within civil society and the private sector are able to contribute to the development and deployment of digital health solutions. Platforms such as the Digital Transformation for UHC 2030 Coalition or datacraft are good examples of what should be further promoted to bring data scientists and healthcare professionals together. Further institutional support is needed for such initiatives.
Field experience from LMICs – hype vs. reality: There are many relevant lessons to learn from low and middle income countries. For instance, the Harvard Global Health Institute’s Data Science & AI Summit for Healthcare (DASH) initiative highlights how the Covid-19 response in LMICS has magnified existing barriers to leveraging digital solutions, while providing opportunity for unprecedented creativity in the space. Mature digital solutions have been readily harnessed – telemedicine exploded, SMS has been deployed for the rapid dissemination of information, and new platforms for real-time reporting of cases have been developed. In many cases, data has become available more quickly for researchers and decision-makers.
Yet when it comes to the use of AI tools in the COVID-response, many barriers have been amplified by the urgency of the situation. For example, training an AI algorithm requires high data volume, which often doesn’t exist and for some tools, the time consuming and expert-driven process of labeling. Recognizing and addressing potential biases in datasets also needs to be prioritized, as an algorithm trained on biased data will further perpetuate it. While AI has enormous potential in addressing unfulfilled health needs in low resource settings, it should be considered amongst an abundance of other digital and non-digital solutions. For the most impact, new solutions should always be developed and deployed in tandem with or led by local experts and stakeholders.
Finally, open access of technologies is important, notably in the context of LMICs. The PASSION project, which focuses more specifically on teledermatology in African countries, shows again the immense potential of digital technologies for LMICS. Yet, datasets from local populations are missing. This makes it more difficult to train algorithms accordingly, although technological solutions can help. A global health data ecosystem, in which health data could be more easily shared and exchanged in a fair and transparent way, would facilitate the development and deployment of such initiatives.
Covid-19 as a catalyst? There are many challenges ahead. While Covid-19 has reinforced some of them, it has also highlighted the potential that lies behind digital health technologies within the general public and amongst decision-makers. Initiatives like the ones we work on at foraus, I-DAIR, the Harvard Global Health Institute, datacraft or through the PASSION project, help to bring together stakeholders from different areas and to foster trust and understanding around digital health and AI. We believe that, if necessary framework conditions and mechanisms are created, digital health technologies can and will unfold their full potential and play a facilitating role towards the achievement of universal health coverage by 2030.