The rapid expansion of Electronic Health Records has accelerated the integration of Big Data Analytics (BDA) and Artificial Intelligence into healthcare systems, transforming clinical decision-making and personalised medicine. However, increasing reliance on advanced analytics introduces substantial challenges related to governance, cybersecurity, ethical accountability, and workforce preparedness. This rapid review, guided by PRISMA and structured using the PICOSS framework, synthesises peer-reviewed literature published between 2013 and 2023 to examine the benefits, tools, and challenges associated with BDA in healthcare. Of the 2,969 retrieved studies, 35 met the inclusion criteria. Findings indicate that BDA enhances predictive capabilities (31%), personalised healthcare delivery (31%), and operational cost efficiency (11%). Persistent barriers include data governance and quality management concerns (48%), cybersecurity risks (40%), and ethical challenges such as algorithmic bias and limited transparency (26%). Advanced tools, including machine learning, deep learning, and federated learning, are central to implementation but require specialised competencies. The review identifies a critical gap in healthcare education regarding AI literacy, ethical algorithm governance, and interdisciplinary training. These findings underscore the need to embed data governance, cybersecurity awareness, and ethical AI frameworks into higher education curricula to prepare professionals for responsible, sustainable data-driven healthcare practice.

Authors:
Muhammad Sultan, Medical University of Bahrain, Bahrain

About the Presenter(s)
Muhammad Sultan is a Data and AI specialist at School of Nursing & Midwifery, Royal College of Surgeons in Ireland – Bahrain, with research interests in AI integration, workforce preparedness, and educational transformation in data-driven healthcare.

Connect on Linkedin
https://www.linkedin.com/in/s-muhammad/

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