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Analysis Study Research Paper | Information Technology | United States of America | Volume 13 Issue 7, July 2024 | Rating: 2.7 / 10
Predicting Diabetes through Data Analytics Enhancing Early Detection and Intervention
Umamaheswara Reddy Kudumula [6]
Abstract: The United States is grappling with a chronic disease crisis, with 90% of the nation's $4.1 trillion annual healthcare expenditure dedicated to managing chronic and mental health conditions. Diabetes stands out among these chronic diseases, affecting 11.6% of the U. S. population. Nearly 38 million Americans are currently living with diabetes, and an additional 96 million are prediabetic, placing them at high risk for developing type 2 diabetes [1]. This condition leads to severe complications, such as heart disease, blindness, and kidney failure. In 2022, the cost of diagnosed diabetes was nearly $400 billion, encompassing medical expenses and productivity losses. Diabetes is among the top 10 causes of mortality in the U. S., with an average death rate of 31.1 per 100, 000 people. Early detection and prevention are crucial to reducing [2] healthcare costs, improving quality of life, and preventing premature deaths. This white paper explores the potential of predictive data analytics to identify individuals at risk of developing diabetes. By leveraging these insights, healthcare organizations can implement targeted interventions, enhance patient outcomes, improve quality of life, and reduce overall healthcare costs.
Keywords: Chronic Conditions, Diabetes, Prevalence, Data Analytics, Healthcare, Patient Care, Chronic Disease
Edition: Volume 13 Issue 7, July 2024,
Pages: 1214 - 1219