📄 Abstract
The healthcare sector is undergoing rapid transformation with the integration of advanced technologies, particularly Artificial Intelligence (AI), to improve operational efficiency and quality management. This study focuses on analyzing how AI-based systems contribute to enhancing hospital performance at MGM Healthcare. The research examines key operational areas such as patient flow, resource utilization, workflow coordination, and service delivery, along with the role of quality management practices in ensuring better patient outcomes. The study adopts a structured research methodology using both primary and secondary data. Statistical tools such as percentage analysis, ANOVA, and Chi-square tests are applied to evaluate relationships between operational efficiency, service quality, and patient satisfaction. The findings reveal that AI technologies, including Hospital Information Systems (HIS), Electronic Medical Records (EMR), and telemedicine, significantly improve decision-making, reduce waiting time, and enhance overall service quality. The results also indicate that effective quality management practices, supported by trained staff and proper coordination, lead to higher patient satisfaction. However, challenges such as system adaptation and workload management still need attention. The study concludes that the integration of AI with efficient management practices plays a crucial role in achieving sustainable healthcare performance and improving patient care.
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📚 How to Cite:
Kannan A, Dr Delecta Jenifer R , AI-BASED OPERATIONAL EFFICIENCY AND QUALITY MANAGEMENT AT MGM HEALTHCARE , Volume 11 , Issue 4, April 2026, EPRA International Journal of Research & Development (IJRD) ,