Work

Digital twins in hospital operations management: a structured review and quantitative content analysis of decision support, workflow engineering and resource allocation

Year: 2026

Type: article

Abstract: INTRODUCTION: Digital twin (DT) technology is increasingly used to support data-driven hospital operations, but evidence remains fragmented across workflows, technological infrastructures, levels of decision support, implementation stages, and methodological quality. OBJECTIVE: This study aimed to synthesise DT applications in hospital operations management and to develop a structured framework linking data infrastructure, workflow modelling, decision support, resource allocation, implementation, and operational resilience. METHODS: A structured review and quantitative content analysis was conducted across PubMed, Scopus, and Web of Science on 23-24 March 2026. Of 521 records identified, 456 remained after duplicate removal and 20 studies met the eligibility criteria following title/abstract and full-text screening. Studies were independently classified by two reviewers according to application domain, technological infrastructure, decision-support maturity, operational outcomes, and implementation stage, and were formally appraised for methodological and reporting quality using design-appropriate QuADS and JBI tools. RESULTS: Twenty studies were included. Among the 13 studies demonstrating operational decision-support capability, 2 (15.4 %) were descriptive, 3 (23.1 %) predictive, 5 (38.5 %) prescriptive, and 3 (23.1 %) adaptive. Implementation remained limited: 6 studies (30 %) were contextual/conceptual, 8 (40 %) simulation or proof-of-concept, 4 (20 %) hospital-context validation or pilot studies, and only 2 (10 %) demonstrated operational implementation. Among the 17 studies assessed with QuADS, the final consensus median score was 36/39 (IQR 31-38; range 21-38). CONCLUSIONS: DTs are emerging as hospital information-system infrastructures for analytics-enabled, workflow-integrated, and human-supervised decision support. However, technical decision-support sophistication does not necessarily indicate real-world implementation or stronger evidence. Wider adoption requires interoperable data systems, workflow integration, governance, organisational readiness, and rigorous evaluation in operational hospital settings.

Source: International Journal of Medical Informatics

DOI: 10.1016/j.ijmedinf.2026.106768

Authors: İbrahim Halil Kayral, Seda Taşır

Institutions: Izmir University, Ankara University

Language: English

Topic: Healthcare Operations and Scheduling Optimization

Subfield: Emergency Medical Services

Field: Health Professions

Domain: Health Sciences

SDGs: Good health and well-being, Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $3,150