Volume 6 Issue 3 @ 2020 IJIRCT | ISSN: 2454-5988 IJIRCT2412087 International Journal of Innovative Research and Creative Technology (www.ijirct.org) 1 Big Data to Better Care: The Role of AI in Predictive Modelling for Healthcare Management Arunkumar Paramasivan Application Development Advisor Cigna Healthcare Abstract Artificial intelligence (AI) is transforming healthcare management by enabling predictive modelling that leverages vast datasets for proactive and informed decision-making. This article explores the role of AI-driven predictive analytics in enhancing healthcare outcomes, operational efficiency, and patient care personalization. By analyzing comprehensive data sources, from electronic health records to real-time patient monitoring, AI models can accurately forecast health trends, identify individuals at risk of disease, and recommend optimized treatment plans. The ability to anticipate health events enables healthcare providers to shift from reactive to proactive care, which helps to reduce hospital admissions, manage chronic conditions more effectively, and improve overall population health. Furthermore, predictive modelling assists healthcare systems in anticipating resource demands, thereby streamlining allocation and reducing operational costs. The study underscores the value of AI in managing healthcare resources efficiently, especially under constraints, and provides insights into how predictive modelling supports policy-making, reduces clinical workload, and enhances decision- making capabilities. The article presents case studies illustrating the real-world impact of predictive AI applications across various healthcare sectors. Ethical considerations surrounding data privacy and model transparency are also addressed to ensure AI-driven solutions uphold patient trust and regulatory standards.AI continues to evolve, it will unlock new potentials for data-driven healthcare strategies, ultimately paving the way for a more adaptive and resilient healthcare infrastructure capable of delivering high-quality, cost-effective, and personalized care. Keywords: Big Data, Artificial Intelligence, Predictive Modelling, Healthcare Management, Resource Allocation, Data-Driven Decision-Making, Health Trend Forecasting, Personalized Medicine, Chronic Disease Management, Operational Efficiency, Cost Reduction, Real-Time Monitoring, Ethical Considerations I. INTRODUCTION In recent years, the convergence of artificial intelligence (AI) and big data has brought transformative changes to healthcare management, fundamentally reshaping how healthcare providers anticipate, diagnose, and treat medical conditions. Through predictive modeling, AI can analyze enormous, diverse datasets—from electronic health records (EHRs) to wearable device data, imaging records, and population health statistics—identifying meaningful patterns that human analysis might overlook. By enabling data-driven insights into health trends, AI-powered predictive models help healthcare professionals forecast the likelihood of specific health outcomes, proactively identify patients at risk of complications, and streamline treatment planning. This shift to predictive analytics is more than a technological evolution; it represents a proactive approach to patient care that has the potential to improve outcomes, lower costs, and allocate resources more efficiently across healthcare systems. Predictive modeling in healthcare has been shown to support early diagnosis of chronic conditions, enhance preventive care strategies, and optimize