From Patterns to Policy: A Scoping Review Based on Bibliometric Analysis (ScoRBA) of Intelligent and Secure Smart Hospital Ecosystems

2026-03-31

AI Summary

This study addresses the fragmented state of research on intelligence and security in smart hospitals, which has lacked a systematic review and actionable policy guidance. Integrating the PAGER framework with a bibliometric approach (ScoRBA), the authors analyze 891 Scopus-indexed journal articles using co-occurrence analysis, network visualization, overlay analysis, and Enhanced Strategic Diagrams (ESD). They identify three core research clusters—artificial intelligence, privacy preservation, and cloud-edge architectures—and reveal critical gaps, particularly in interoperability and cross-layer integration. The work highlights emerging directions such as explainable AI and federated learning, and proposes an evidence-based policy pathway tailored for developing countries, centered on synergistic governance, scalable infrastructure, and secure data ecosystems.

Technology Category

• Philosophy and Ethics of AI: Privacy & Security
• Intelligent Robots: Other Foundations and Applications
• Cognitive Modeling & Cognitive Systems: Agent Architectures

Application Category

• Security and Privacy: Data transparency and provenance
• Systems and Infrastructure for Web, Mobile and WoT: Web applications in cross-disciplinary domains and verticals such as mixed reality, smart cities, and digital health
• Semantics and Knowledge: Provenance, trust, security and privacy, and ethical issues in managing semantic data

Abstract

This study examines the evolution of Intelligent and Secure Smart Hospital Ecosystems using a Scoping Review with Bibliometric Analysis (ScoRBA) to map research patterns, identify gaps, and derive policy implications. Analyzing 891 journal articles from Scopus (2006-2025) through co-occurrence analysis, network visualization, overlay analysis, and the Enhanced Strategic Diagram (ESD), the study applies the PAGER framework to link Patterns, Advances, Gaps, Research directions, and Evidence-based policy implications. Findings reveal three interrelated clusters: AI-driven intelligent healthcare systems, decentralized privacy-preserving digital health ecosystems, and scalable cloud-edge infrastructures, showing a convergence toward integrated ecosystem architectures where intelligence, trust, and infrastructure reinforce each other. Despite progress in AI, blockchain, and cloud computing, gaps remain in interoperability, real-world implementation, governance, and cross-layer integration. Emerging themes such as explainable AI, federated learning, and privacy mechanisms highlight areas needing further research. Policy-relevant recommendations focus on coordinated governance, scalable infrastructure, and secure data ecosystems, particularly for developing country contexts. The study bridges bibliometric evidence with actionable policies, supporting informed decision-making in smart hospital development.

Problem

• Smart Hospital Ecosystems
• Interoperability
• Governance
• Implementation Gap
• Cross-layer Integration

Innovation

• ScoRBA
• PAGER framework
• bibliometric analysis
• smart hospital ecosystems
• federated learning