Technology And Innovation In HR
Varma, C. Bhaskar
Research Scholar, Jain University, Bangalore
Abstract
In India, the high cost of medical education, particularly for an MBBS degree, poses significant challenges for new doctors, who often find that their qualifications do not justify the Expenses incurred. This financial strain is exacerbated when these highly trained professionals are employed for routine tasks such as insurance treatment and billing verification, roles that are not commercially viable given their level of education and potential. As a cost-effective measure, many insurance companies and third-party administrators (TPAs) opt to employ doctors with BHMS or BMS degrees for these tasks. However, these professionals are often underqualified for the complexities of medical verification, leading to inefficiencies and errors in treatment validation and anomaly detection. The situation also adversely affects programs like the Ex-Servicemen Contributory Health Scheme (ECHS), where the need for accurate and efficient cashless medical services is critical. Delays and inaccuracies in medical verification can complicate the provision of timely healthcare to veterans and their families, underscoring the need for improvement in these processes. This paper proposes the implementation of an Artificial Intelligence (AI) ecosystem designed to function as highly qualified medical agents. This AI system will be capable of independently verifying diagnoses, treatment plans, and medical reports for accuracy while also identifying procedural anomalies. The primary objective is to augment the capabilities of the current workforce, enhancing overall efficiency and effectiveness in medical management. By deploying AI medical agents, the project aims to not only address the gap in qualification and task complexity but also improve the accuracy and reliability of medical administrative processes. This initiative promises to revolutionize the way medical verifications are handled, providing a sustainable, scalable solution to a pressing healthcare management issue in India.
Keywords: Technology, Innovation, financial strain, artificial intelligence, challenges
Impact statement
The current research proposes the implementation of an Artificial Intelligence (AI) ecosystem designed to function as highly qualified medical agents. This AI system will be capable of independently verifying diagnoses, treatment plans, and medical reports for accuracy while also identifying procedural anomalies. With the objective to augment the capabilities of the current workforce, the research focus on enhancing overall efficiency and effectiveness in medical management. By deploying AI medical agents, the project aims to not only address the gap in qualification and task complexity but also improve the accuracy and reliability of medical administrative processes.
About The Author
With over 30 years of professional experience spanning aviation, human resources, and healthcare, C. Bhaskar Varma has built a diverse skill set that allows him to navigate and succeed in complex industries. His began in aviation, where he oversaw operations that demanded precision, safety, and adaptability. This role sharpened his leadership abilities and gave him an in-depth understanding of managing large-scale, high-stakes environments. Transitioning into human resources, He gained valuable experience in people management, recruitment, employee development, and organizational efficiency. He became adept at creating cohesive, high-performing teams and optimizing workflows to meet business objectives. Currently, he apply his skills to the healthcare sector, focusing on hospital insurance services for retired personnel. He is particularly passionate about delivering ethical, affordable medical services to those most in need, ensuring that quality healthcare is accessible and sustainable. A key strength is his ability to set up and launch new ventures or operations, leveraging his experience to establish efficient, effective systems from the ground up. He approach each challenge with a commitment to ethical practices, cost-effectiveness, and long-term success, making a tangible difference in the industries that he serve.
References
Aayog, N. (2018). National strategy for artificial intelligence. https://niti.gov.in/writereaddata/files/document_publication/NationalStrategy-forAI-Discussion-Paper.pdf
Bhattacharya, S., & Hossain, M. M. (2021). The challenges and opportunities of artificial intelligence in healthcare in India. International Journal of Advanced Computer Science and Applications. https://doi.org/10.14569/IJACSA.2021.0120413
National health Profile 2020. https://www.mohfw.gov.in/documents/national-health-profile
Healthcare in India: Current state and key imperatives. (2020). https://home.kpmg/in/en/home/insights/2018/12/healthcare-in-india.html Ministry of Health and Family Welfare, Government of India.
Indian Journal of Medical Ethics. (2017). Medical education in India: Current issues and challenges. Indian Journal of Medical Ethics, 2(1), 10–15. https://ijme.in/articles/medical-education-in-india-current-issues-and-challenges/KPMG. (2018).
12(4), 101-109. (2020). Artificial Intelligence in Healthcare in India: A Review. Purohit, A, & Singh, S. Journal of Medical Systems, 44(11), 1-11, 020-01658-1. https://doi.org/10.1007/s10916
Journal Rajkomar, A., Dean, J., & Kohane, I. (2019). Machine learning in medicine. New England of Medicine, 380(14), 1347–1358. https://doi.org/10.1056/NEJMra1814259. These references provide a comprehensive overview of the challenges and opportunities associated with implementing AI in healthcare in India, the current state of medical education, and the potential impacts on healthcare management and administration
McKinsey, & Company. (2019). Transforming healthcare with AI: The impact on the workforce and organizations. https://www.mckinsey.com/industries/healthcare-systems-and-services/ourinsights/transforming-healthcare-with-ai
World Health Organization. (2019). Artificial intelligence in health: Ethical, legal, and social implications. https://www.who.int/health-topics/artificial-intelligence
Tiwari, A. K. (2024). Relevance of innovations in educational research technology of universities. Edumania-An International Multidisciplinary Journal, 02(01), 235–254. https://doi.org/10.59231/edumania/9029
S, S. (2023). Impact of social media on Youth: Comprehensive Analysis. Shodh Sari-An International Multidisciplinary Journal, 02(04), 286–301. https://doi.org/10.59231/sari7640
Naveen, & Bhatia, A. (2023). Need of Machine Learning to predict Happiness: A Systematic review. Edumania-An International Multidisciplinary Journal, 01(02), 306–335. https://doi.org/10.59231/edumania/8991
Kumar, S., & Simran. (2024). Equity in K-12 STEAM education. Eduphoria, 02(03), 49–55. https://doi.org/10.59231/eduphoria/230412
Kumar, S. (2023). Artificial Intelligence Learning and Creativity. Eduphoria, 01(01), 13–14. https://doi.org/10.59231/eduphoria/230402
Kulkarni, S. R., & Kulkarni, S. S. (2024). Revolutionizing organizations by technological innovations in HR. Shodh Sari-An International Multidisciplinary Journal, 03(01), 03–14. https://doi.org/10.59231/sari7650
Agarwal, R. (2023). Use of technology by higher education students. Shodh Sari-An International Multidisciplinary Journal, 02(04), 152–161. https://doi.org/10.59231/sari7631