Utilizing Data Analytics to Predict Chronic Condition: A Focus on Diabetes
Abstract: The United States of America has a crisis of chronic disease. 90% of the nation's 4.1 trillion dollars in annual health care expenditure goes towards chronic and mental health condition management [1] [2]. Diabetes has the highest prevalence among chronic conditions in the [3] healthcare industry, impacting 11.6% of the U. S. population [4]. Nearly 38 million Americans have Diabetes, and another 96 million have prediabetes condition, which puts them at risk of developing type 2 diabetes. Diabetes causes severe complications like heart disease, blindness, or kidney failure. In 2022, the estimated cost of diagnosed Diabetes was nearly $400 billion in medical costs and productivity loss [4]. Diabetes is one of the Top 10 conditions resulting in mortality, with an average death of 31.1 per 100, 000 [6]. Early detection and prevention of Diabetes are required to reduce healthcare costs, improve the Quality of life, and prevent early deaths. This white paper explores the opportunity of using predictive data analytics to predict if a person is likely to develop Diabetes. This data helps Healthcare Organizations develop strategies to target interventions, enhance patient outcomes, improve Quality of life, and reduce healthcare costs.
Keywords: Chronic Conditions, Diabetes, Prevalence, Data Analytics, Healthcare, Patient Care, Chronic Disease
How to Cite?: Bharath Srinivasaiah, "Utilizing Data Analytics to Predict Chronic Condition: A Focus on Diabetes", Volume 13 Issue 2, February 2024, International Journal of Science and Research (IJSR), Pages: 354-360, https://www.ijsr.net/getabstract.php?paperid=SR24202231430, DOI: https://dx.doi.org/10.21275/SR24202231430