WORLD JOURNAL OF ADVANCE
HEALTHCARE RESEARCH

*Folasade Agbolade, Chioma Obi, Kehinde Falayi, Oriolowo Temitope and Ayodeji Falayi

ABSTRACT

Chronic diseases are responsible for the majority of disability and mortality worldwide. These encompass cancer, diabetes, and cardiovascular disease. Unhealthy lifestyles and an aging population are key factors that contribute to the growing burden of chronic disease. The crucial factor in improving health outcomes for these individuals is the implementation of preventive treatment and the proactive management of disorders. However, standard reactive approaches do not detect risks at an early stage. This study proposes the utilization of big data analytics, insights, and predictive modeling to actualize tailored and precise care, with the aim of assisting patients and doctors in proactively managing chronic diseases. Advanced analytics may integrate diverse digital data sets, including genetics, social determinants of health, claims, medical records, and wearables, to detect risks, predict adverse outcomes, and deliver personalized therapies. By utilizing data-driven precision care with education and support programs, patients suffering from chronic diseases can achieve significant enhancements in preventative care, disease management, health outcomes, and overall quality of life, all while reducing healthcare costs. This article explores the diverse role of prediction models and intelligent alerts in the field of preventive medicine, applications of big data analytics in chronic disease management, examines key technologies and solutions, identifies limitations and challenges, and provides recommendations to fully leverage the potential of big data-driven care. An optimal learning health system for the proactive and personalized management of chronic diseases can be achieved through meticulous design and the ethical utilization of advanced analytics on a wide range of data.