1- Management Development & Resource Deputy, Gonabad University of Medical Sciences, Gonabad, Iran
Department of Health Information Technology, School of Paramedical and Rehabilitation, Mashhad University of Medical Sciences, Mashhad, Iran
2- Student research committee, Mashhad University of medical sciences, Mashhad, Iran
Department of Epidemiology, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran
3- Department of Health Information Technology, School of Paramedical and Rehabilitation, Mashhad University of Med-ical Sciences, Mashhad, Iran , merajim1@mums.ac.ir
Abstract: (28 Views)
Background: Driven by the advancements in artificial intelligence, the Internet of Things, and big data technologies, smart hospitals have emerged as an effective framework for improving service quality, patient safety, and resource efficiency. This study aimed to identify, extract, and classify indicators for assessing hospitals’ readiness for smart transformation.
Materials and Methods: This scoping review was conducted in accordance with the PRISMA‑ScR guidelines. The Web of Science, PubMed, Scopus, IranDoc, MagIran, and SID databases were searched without date restrictions up to May 18, 2024. In addition, documents from the World Health Organization (WHO), the Pan American Health Organization (PAHO), and the European Union Agency for Cybersecurity (ENISA) were reviewed. Data were extracted using a standardized form and analyzed through qualitative content analysis.
Results: Out of 2,120 retrieved records, five studies met the final inclusion criteria and were included in the analysis. A total of 108 smart hospital readiness assessment indicators were identified and categorized into three main domains:Infrastructure and Energy Management (44 indicators), Safety and Risk Management (18 indicators), Information and Communications Technology (46 indicators).
Conclusion: The findings indicate that assessing hospitals’ readiness for smart transformation requires simultaneous consideration of technical infrastructure, safety, and information technology capabilities. The extracted framework can serve as a foundation for designing localized assessment tools and planning hospital digital transformation. Study limitations include the limited number of eligible studies and the heterogeneity of the reported frameworks.
Original:
Review |
Subject:
Healthcare management Received: 2025/11/12 | Accepted: 2026/09/15 | Published: 2026/10/21
Send email to the article author