Leapfrogging the primary care gap: How artificial intelligence can be used as a tool for universal health coverage in low- resource setting

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Tommy Hana

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Abstract

In 1946, the World Health Organization (WHO) declared that the enjoyment of the highest attainable standard of physical and mental health is one of the fundamental rights of every human being.1 Over 70 years have passed and 194 member states have adopted the principles of this constitution, yet over half of the world’s population still do not have full coverage of essential health services, including primary care.2 In accordance with the 2030 Sustainable Development Goals (SDGs), all WHO member states have agreed to achieve universal health coverage (UHC) by 2030.3 Since the adoption of the SDGs, both governments and grass-roots organizations have created, piloted, and/or scaled a plethora of unique programs and strategies to increase access to essential health services. Many of these programs have been enabled using Artificial Intelligence (AI) technologies. The basis of AI technology is mimicry of the human thought process. Like the human brain, AI can perform tasks or reasoning processes to solve problems. Modern, narrow AI methods, powered by machine learning, enable computers to learn how to perform specific tasks and conduct constrained reasoning processes from large sets of data without being explicitly programmed how to do so.4 This discussion focuses on the various uses of AI technologies as they apply to primary care, with a focus on low-resource settings.