A global review of opportunities, best practices, emerging trends & pitfalls in application of Artificial Intelligence-Machine Learning technologies in the area of healthcare financing for UHC and their relevance to the Pradhan Mantri Jan Arogya Yojana in India.
People in low-and middle-income countries (LMICs) generally rely on out-of-pocket spending for their medical expenses (Reshmi et al.,2021). This can result in significant financial shocks, particularly for poor and other vulnerable families. Health insurance is one of the interventions that has been suggested by expert committees as one of the ways to achieve Universal Health Coverage (UHC) to mitigate high secondary and tertiary care expenses for people, particularly the poor and vulnerable (Planning Commission, 2011).
In 2019, the Government of India launched an ambitious health-care scheme called “Ayushman Bharat”, which comprised as a social health insurance scheme aiming to bring more than 107 million of the most vulnerable families in the country under the ambit of health insurance, covering a range of tertiary and secondary care.
This study is a global review concerning the potential applications of Artificial Intelligence and Machine Learning in healthcare financing (particularly in health insurance), with a focus on publicly funded systems. the objective is to assess the benefits and challenges of AI and ML for the effective functioning of such systems towards sustainability, with the backdrop of PMJAY scheme in India. With large amounts of relevant data generated in India under the scheme, informed decision-making can be promoted and strengthened by implementing the use of AI and ML in key strategic areas.
