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Abstract

This review explores the impact of health analytics on reducing healthcare costs, with a particular focus on aging populations. The integration of data-driven approaches in healthcare has proven effective in optimizing resource allocation, improving care coordination, and enhancing patient outcomes. Predictive analytics plays a critical role in early diagnosis and the management of chronic diseases, leading to cost reductions by preventing hospital readmissions and emergency care. Furthermore, personalized medicine, telehealth, and remote monitoring have contributed to more efficient healthcare delivery by minimizing unnecessary treatments and in-person visits. The review highlights how these innovations not only address the growing healthcare demands of elderly populations but also support long-term sustainability by lowering operational and administrative expenses. Recommendations are provided for policymakers and healthcare providers on how to effectively leverage health analytics to further reduce costs and improve care quality in the future.
Keywords:  Health Analytics, Cost Reduction, Aging Populations, Predictive Analytics, Personalized Medicine, Telehealth.