The prevalence of mental health disorders worldwide poses a significant and pressing concern, affecting the quality of life and life expectancy of a substantial portion of the global population. This research endeavors to investigate the application of Artificial Intelligence (AI) Technologies in addressing the complex challenges within the realm of mental health. It aims to navigate barriers associated with cost-efficiency, accessibility, and product development. The objective of this study is to formulate a strategic framework enabling mental health solution providers to reduce costs while accommodating the diverse needs and preferences of individuals.
Employing a qualitative research design, this study seeks to comprehensively explore the multifaceted dimensions of the research problem. It intends to substantiate the relationship between AI technology and connectivity in the context of mental health through rigorous investigation. Focused group discussions will be conducted to gauge public sentiment and perceptions regarding the utilization of AI technology in mental healthcare. Additionally, an analysis of claims data, if available, will offer insights into various aspects such as the number of claims, patient visits and expenditure from both patients and insurers.
The anticipated outcome of this research is to provide empirical evidence demonstrating the impact of AI integration on mental health solutions. It aims to furnish actionable guidance for businesses within the mental health sector to curtail costs and cater to the diverse needs of individuals. Furthermore, it aspires to yield a nuanced understanding of public attitudes, concerns and willingness to embrace AI-based solutions in mental healthcare.

Authors:
Bhanu Ranjan, SP Jain School of Global Management, Singapore
Rashmi Malpani, SP Jain School of Global Management, Singapore

About the Presenter(s)
Dr Bhanu Ranjan is a University Assistant Professor/Lecturer at S P Jain School of Global Management in Singapore

See this presentation on the full schedule – Thursday Schedule

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