-By I-DAIR, an IHF partner

India Health Fund (IHF) is proud to partner with the International Digital Health & AI Research Collaborative (I-DAIR), an initiative to co-create a neutral platform enabling global research collaborations on digital health and AI for health. By convening stakeholders, I-DAIR aims to develop global public goods solving health issues and improving health systems through the inclusive, impactful and responsible deployment of data and AI for health. AI has the potential to improve the healthcare delivery and services by helping governments extend coverage for universal healthcare, especially in a country like India that has significant gaps in healthcare delivery and services. Here are 5 ways in which, with the help of AI-based tools, healthcare services can be extended to underserved populations, improve public health monitoring, and enable healthcare providers to better attend to patient care. 1. Sharing knowledge tools that can identify gaps in research and investments, and develop realistic recommendations for national strategies On November 24, 2021, I-DAIR celebrated the release of the tool and report from its first PathFinders project: the Global Research Map (GRM) of Digital Health and AI. I-DAIR’s Digital Health and AI Global Research Map is an interactive tool designed to provide awareness of the global, regional and national landscapes of digital health and AI research and innovation. Its objectives are to enhance visibility and understanding of current research and investment trends, identify gaps, and foster multistakeholder collaboration on AI and digital health to achieve Universal Health Coverage (UHC) and the Sustainable Development Goal 3 (SDG.3) Using the GRM, users can not only visualise general trends in digital health research and innovation, but also get a deeper dive into regional and national dynamics at play. One of the key findings relates to the unequal distribution of patents: while high income countries (HICs) and low and middle income countries (LMICs) have a similar overall level of patents, there is a strong concentration within those groups. China holds 76% of patents from LMICs and more than 47% of patents filed worldwide. Comparatively the total number of patents filed in the Africa and MENA regions represent about 1% of global patents. Similarly amongst HICs, the USA dominate the patent world, with 24.74% of the global total, while Western, Northern and Southern Europe represent altogether 2.46% of worldwide patents. The GRM is henceforth a practical tool providing the ability to highlight the disparities and inequity in knowledge creation and implementation within the digital health sphere. In turn, this newly raised awareness grants an opportunity to identify gaps in research and investments and develop realistic recommendations to close them. Updated and enriched editions of the GRM will be released annually, along with special versions focusing on specific health topics. As an example, a Map dedicated to Mental Health research is currently being developed. For more information about the GRM and its 2021 report, click here. 2. Shifting the paradigm to community-centered healthcare approach AI solutions constitute an opportunity for improving patient-centric healthcare outcomes. Harnessing the power of digitalization and AI can render the continuum of care more accurate, personalized, accessible, and effective. For example, AI assisted diagnostics and treatment can support physicians’ decisions and provide recommendations backed up by large amounts of healthcare data, improving the accuracy and pace of diagnosis and ultimately saving lives. Currently, the classical model for last mile healthcare and promotion relies on a dedicated workforce to whom primary investigations, health advice and health data collection responsibility are delegated. I-DAIR aims to shift the paradigm towards a community-centered health care approach where a distributed infrastructure, combined with locally available clinical and medical knowledge, provides a continuum of care from promotion, prevention, early diagnosis to treatment. To implement this logic, I-DAIR is co-designing, with the Government of Punjab and Nagaland, an “Open Health” scheme – resulting from an assessment of the current factors hampering the care continuum and integrating existing community health worker and physician workflows, while considering interoperability with eSanjeevani and other government platforms. 3. Embracing new models of inter-sectoral and cross-border collaboration Given globalization and ongoing changes in biodiversity and climate, emerging infectious diseases (EIDs) will remain one of the greatest threats to humanity. The scale and impact of COVID-19 have highlighted inadequacies in our collective capacity to detect and respond in a timely and decisive manner to pandemics. This challenge is as much political as it is about science. The global community needs to come together to embrace new models of inter-sectoral and cross-border collaboration, bringing in academia, the private sector and civil society as partners with governments. Per these conclusions, I-DAIR is elaborating with its partners the idea of a science-based, data-driven, neutral, and trusted collective capacity to improve the quality of local and national responses throughout the continuum of pandemic phases: a global pandemic preparedness and response scheme. A Pandemic Scientific Group, consisting of scientific experts from 14 countries, 17 organizations and 7 disciplines, has recently been conveyed to develop a roadmap for future R&D efforts and guide development of an investment case for the full development of the scheme. 4. Exploring new governance models for AI and Data for health The Covid-19 pandemic created a momentum which increased AI developments, resulting in innovations fostered by a massive flow of investments and a strong political commitment at the global level. However, despite this surge, AI have not constituted a determining factor in the fight against Covid-19, with limited reliable and successful applications¹. Nevertheless, Covid-19 changed the telemedicine landscape and shifted stakeholders’ perceptions of and priorities for virtual care more broadly. Given the trajectory of adoption rates and rapid expansion of use cases, digital tools supported by AI could have the potential to drastically reduce health costs, improve patient outcomes, and expand access to care over the next decade. However, the long-term future of the AI for the health domain will depend on stakeholders’ ability to address key challenges, including privacy concerns, patients’ underlying sense of mistrust, lack of quality and interoperable health data and the overall digital divide, to name a few.  It is then crucial for the future of AI to promote shared quality standards and ethics within the digital health space. Quality data could be collected through increased cooperation in research to promote the free flow of complete data sets, international standards of quality and interoperability, as well as fight against the hindering of health data to move toward a paradigm that would promote it as global public good. In that respect, I-DAIR is currently elaborating a new governance model for AI and data for health that would be tiered, multi-stakeholder and distributed to tackle misuse, missed use, as well as missing data (‘3 M’s). 5. Bridging the health gap and the digital divide to promote inclusive, diverse, and equitable healthcare According to the World Health Organization, at least half of the world’s population lack access to essential health services. More than 800 million people bear the burden of spending at least 10% of their household income on healthcare, with out-of-pocket expenses driving almost 100 million people into poverty each year. At the current pace, up to one third of the world’s population will remain underserved by 2030². The digital transformation of current health systems has the ability to bridge the health gap and the digital divide to achieve universal health coverage. AI has the potential to achieve data-driven clinical health solutions to foster informed, objective and patient-centered care and, thus, participate to dismiss unconscious prejudices influencing healthcare decisions, providing that bias has first been removed from the dataset. That is why transdisciplinary, multistakeholder and global north-south research collaboration is so decisive to promote inclusive, diverse, and equitable healthcare for clinical researchers, practitioners and patients around the world. To know more about I-DAIR and its work please visit https://www.i-dair.org/ and to not miss any updates about our work and events, follow us on Twitter and LinkedIn. Reference:

1. https://www.technologyreview.com/2021/07/30/1030329/machine-learning-ai-failed-covid-hospital-diagnosis-pandemic/
2. https://www.who.int/health-topics/universal-health-coverage#tab=tab_1