The Application of Big Data Analytics in Predictive Medicine and Its Influence on Early Disease Detection and Preventive Healthcare Strategies

Abstract

The rapid growth of Big Data analytics has significantly transformed predictive medicine, enabling early disease detection and the development of effective preventive healthcare strategies. This study investigates the impact of Big Data technologies on clinical prediction accuracy, patient outcomes, and healthcare efficiency. A convergent mixed-methods approach was employed, combining quantitative data from 170 healthcare professionals with qualitative insights from case studies and expert interviews. The findings demonstrate that Big Data analytics significantly enhances early diagnosis rates, improves risk prediction models, and supports proactive healthcare interventions. However, challenges such as data integration complexity, privacy concerns, and algorithmic bias remain significant barriers. The study concludes with strategic recommendations for optimizing the use of Big Data in predictive medicine.