Transforming Healthcare through Big Data Analytics: A Systematic Review of Emerging Trends, Challenges, and Opportunities

Abstract

Big Data Analytics (BDA) is a giant lever that moves the whole healthcare system towards better and cheaper care by enabling accurate insights, improving patient outcomes, and lowering operational costs. The present research paper locates the new developments, the difficulties, and possible solutions concerning BDA implementation in the healthcare sector. Indeed, one of the major instrumentalities of predictive algorithms is reduction in the hospital readmissions rates, moreover, they can be of great help in the improvement of situations with chronic diseases such as heart failure and diabetes. Also, the utilization of genomic data in personalized medicine may become the production of the most advanced treatment methods for cancer area where targeted therapies are reportedly prolong patients' lives. However, the world still has to face issues of data privacy, security, and interoperability along with these advancements. Leading-edge solutions such as strong encryption, blockchain, and strict enforcement of external regulations like HIPAA conspiracies appear to be the answer to the most difficult problems. Case studies have shown that data analytics can be a powerful instrument for the integration of electronic health records (EHRs) and quality improvement, thus resulting in effective clinical decision- making. The obstacles for the use of analytical tools are coming from humans and technology; the need for training programs and the establishment of a data-driven culture remain unchanged. Besides, the synergy of AI, blockchain, and edge computing is a significant factor that healthcare analytics' efficiency, security, and scalability are enhanced. This article ends up arguing that by overcoming these obstacles we will be the beneficiaries of a healthcare system with personalization, safety, and efficiency.