Introduction: The introduction of digitization of healthcare data has posed both challenges and opportunities within the industry. Big Data Analytics (BDA) has emerged as a powerful tool, facilitating data-driven decision-making and revolutionizing patient care.
Purpose: The research aimed to analyze diverse perspectives on big data in healthcare, assess BDA's application in the sector, examine contexts, synthesize findings, and propose an implementation roadmap and future research directions.
Methodology: Using an SLR protocol by Nazir et al. (2019), sources like Google Scholar, IEEE, ScienceDirect, Springer, and Elsevier were searched with 18 queries. Inclusion criteria yielded 37 articles, with five more added through citation searches, totaling 42.
Results: The study uncovers diverse healthcare viewpoints on big data's transformative potential, precision medicine, resource optimization, and challenges like security and interoperability. BDA empowers clinical choices, early disease detection, and personalized medicine. Future areas include ethics, interpretable AI, real-time BDA, multi-omics integration, AI-driven drug discovery, mental health, resource constraints, health disparities, secure data sharing, and human-AI collaboration.
Conclusion: This study illuminates Big Data Analytics' transformative potential in healthcare, revealing diverse applications and emphasizing ethical complexities. Integrated data analysis is advocated for patient-centric services.
Recommendation: Balancing BDA's power with privacy, guidelines, and regulations is vital. Implementing the Nigerian healthcare roadmap can optimize outcomes, address challenges, and enhance efficiency. Future research should focus on ethics, interpretable AI, real-time BDA, and mental health integration.
This work is licensed under a Creative Commons Attribution 4.0 International License.
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