AI-Driven Insights into the Socio-Economic Impact and Effectiveness of Chief Minister's Health Insurance Scheme in Krishnagiri District

Abstract

This study investigates the socioeconomic impact and effectiveness of the Chief Minister’s Health Insurance Scheme (CMHIS) in Krishnagiri District,
with a focus on the beneficiaries' background, including factors such as age, gender, income, family status, household structure, and occupation. The research aims
to understand the demographic characteristics of individuals affected by various health challenges, both natural and artificial, and explores the additional burdens
they face due to rising healthcare costs and the inaccessibility of remote clinics. The analysis employs AI-driven methodologies to gain deeper insights into the
pattern of utilization and the relative effectiveness of the health insurance scheme in addressing the needs of economically disadvantaged populations. Findings
indicate that the scheme has significantly alleviated the financial burdens of many families, but challenges remain in reaching those most in need. The study reveals
that while the scheme has provided essential healthcare support, there is a critical need for targeted interventions to ensure timely access, particularly for individuals
living below the poverty line. Additionally, the study suggests that leveraging AI-based data analytics can aid in more precise identification of vulnerable
communities, improving the timely distribution of healthcare benefits. The research concludes with policy recommendations for the government and healthcare
authorities, emphasizing the importance of optimizing resource allocation, ensuring equitable access to healthcare services, and enhancing the delivery of insurance
benefits to low-income households. Furthermore, it stresses the need for a more data-driven approach to identify beneficiaries and deliver assistance at the most
appropriate time and location, ensuring greater health equity in Krishnagiri District.