A Systematic Review of Blockchain and Metaheuristic Algorithms for Secure and Scalable Healthcare Systems

Karam Hatem Alkhater^1,2,*, Mohana Shanmugam³, Pritheega Magalingam⁴

¹Department of Computer Engineering Techniques, College of Technical Engineering, University of Al Maarif, Al Anbar, 31001, Iraq

²Department of Information & Communication Technology, College of Graduate Studies, Universiti Tenaga Nasional, Selangor, Malaysia

³Department of Informatics, College of Computing and Informatics, Universiti Tenaga Nasional, Selangor, Malaysia

⁴Faculty of Artificial Intelligence, Universiti Teknologi Malaysia (UTM), Kuala Lumpur, Malaysia

Emails: KaramKhater.92@gmail.com; mohana@uniten.edu.my; mpritheega.kl@utm.my

Abstract

The integration of blockchain technology and metaheuristic optimization has transformed healthcare systems by improving security, scalability, and data interoperability. Blockchain ensures decentralization, immutability, and privacy, making it a viable solution for electronic medical records (EMRs) and secure healthcare data management. Meanwhile, metaheuristic algorithms optimize blockchain networks by enhancing transaction efficiency, consensus mechanisms, and real-time medical data processing. This paper systematically reviews recent advancements in blockchain and metaheuristics for healthcare applications. We discuss existing privacy-preserving models, AI-driven optimization techniques, and hybrid consensus mechanisms, addressing their strengths and limitations. Through a structured methodology, we analyze research trends, security challenges, and computational bottlenecks. This study encompassed 300 research articles from nine global databases. Then, inclusion and exclusion criteria were applied, leading to the exclusion of 144 studies and the retention of 156 studies. Subsequently, quality assessments were conducted, resulting in the final inclusion of only 8 studies for data extraction. A three-phase methodology was followed: planning, conducting, and reporting. The studies covered the period from January 2020 to January 2025, and 10 evaluation questions were used to assess the quality of the studies. Our findings reveal that while blockchain enhances data security and interoperability, metaheuristic-driven AI further optimizes system efficiency. However, challenges such as scalability constraints, energy consumption, regulatory compliance, and AI-based cyber threats remain significant. Future research should focus on developing lightweight blockchain architectures, quantum- resistant cryptographic models, and federated AI-enhanced security frameworks to address these issues. By leveraging advanced blockchain and AI-driven metaheuristics, healthcare systems can achieve greater resilience, efficiency, and adaptive security.

Keywords: Blockchain; Metaheuristics; Healthcare Security; Optimization; AI-driven Security; Electronic Medical Records (EMRs); Data Privacy; Consensus Mechanisms