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Review Papers | Health Sciences | United States of America | Volume 13 Issue 11, November 2024 | Popularity: 3.7 / 10

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Machine Learning and the Future of Medicare: Predicting Health Trends in an Aging Society

Ginoop Chennekkattu Markose

Abstract: There is a rapidly growing elderly population that calls for significant pressure on health systems such as Medicare, which caters to the elderly population in millions. This is because as people age and their life spans expand, they are most likely to suffer from chronic diseases, including heart diseases, diabetes, and Alzheimer?s diseases, hence requiring more medical attention and services and high costs. General healthcare approaches, treatment plans, and different measures to deal with the challenges mentioned above have been observed to be inoperative in caring for the increasing elderly patient population. For this reason, Machine Learning (ML) brings a revolutionary solution by leveraging vast amounts of health - related data to make future health forecasts, develop individual treatment programs, and, most significantly, cut expenses. Because of the ability of algorithms to find correlations in patient information about the patient, ML is capable of early diagnosis of diseases patients who are likely to be hospitalized and anticipate possible precautions. For this reason, this article looks at some significant ML approaches, like decision trees, random forests, and neural networks, which have been successfully employed in healthcare prediction. Using factors such as demographic, clinical, and historical data, these models are predictive in that they can predict the health outcomes of Medicare to enhance the management of its resources better and afford more preventive measures. For instance, the readmission of patients to hospitals can be predicted by an ML model, which can help healthcare providers use preventive measures to ensure savings on unnecessary costs. Given the results of this research, it could be stated that the application of ML in the proper way can help not only predict changes in the health of elderly people but also provide an individual approach to providing necessary treatment that would result in the improvement of patient?s conditions and, therefore, stability of Medicare. Because of this, it can be considered a modern approach in healthcare management, especially when looking into the increasing elderly population.

Keywords: Machine Learning (ML), Medicare, Predictive Analytics, Aging, Health

Edition: Volume 13 Issue 11, November 2024

Pages: 58 - 66

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