The Role of Artificial Intelligence in Health Information Systems: Transforming Healthcare Efficiency and Decision-Making
List of Authors
Abdul Haadi Baharin, Noraisah Kamarudin, Norsuhana Idris, Saiful Nizam Nordin
Keyword
Artificial Intelligence, Health Information Systems, Predictive Analytics, Clinical Decision Support, Digital Transformation
Abstract
Artificial Intelligence (AI) has become a key factor in digital transformation in healthcare, especially when included in Health Information Systems (HIS). AI techniques now go beyond just acting as automated processing tools. They increasingly assist with data-driven clinical reasoning, improve operations, and create personalized patient experiences. This study provides a systematic literature review (SLR) to explore how machine learning, predictive analytics, natural language processing (NLP), clinical decision support systems (CDSS), and robotic process automation (RPA) are integrated into HIS. Searches were carried out in Scopus, ScienceDirect, and IEEE Xplore for peer-reviewed studies published between 2020 and 2025, following the PRISMA protocol. Forty-seven articles met the eligibility criteria and were analyzed to identify areas of implementation, benefits, challenges, and governance implications. The results show clear evidence that AI-enabled HIS improves diagnostic accuracy, streamlines administrative workflows, enhances population health monitoring, and supports predictive decision-making. However, issues related to interoperability, algorithmic bias, explainability, workforce readiness, and cybersecurity still exist, particularly in developing health ecosystems. The review concludes that sustainable implementation of AI-based HIS needs clear model governance, secure data structures, and compliance with privacy laws like Malaysia’s PDPA 2010, backed by national digital strategies such as the MyDIGITAL Blueprint.