ReviewBioengineering (Basel, Switzerland)2026
Digital Twins for Hospital and Healthcare Operations: A Systematic Review of Resource Allocation, Infection Control, and Workflow Optimization.
Review in Bioengineering (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The incorporation of Digital Twins (DT) into the healthcare industry marks a revolution in terms of adopting a more proactive and personalized approach towards patient care. The increasing complexity of technological tools employed within the healthcare environment leads to assessing the potential impacts of these digital models in collaboration with AI and IoT for increased efficiency and improved results. In this context, this study offers a systematic review of existing research regarding DTs in the field of healthcare, with specific consideration of hospital applications. An extensive literature search was performed within the Scopus database for peer-reviewed publications during the period from 2021 to 2026. Following a demanding screening process, 70 relevant articles were found that fulfilled the selection criteria. The review shows an emerging trend towards the application of AI-based Digital Twins in the real-time monitoring, predictive maintenance of medical devices, and planning surgeries. The paper analyses several key characteristics of healthcare DTs, including their design and architecture, and the benefits they generate. It also presents the challenges related to data integration and ethics surrounding virtual health models and recommendations for future research. In conclusion, this review demonstrates the revolutionary role of AI- and IoT-enabled Digital Twins in the transformation of hospitals' infrastructures. This paper summarizes the latest developments and gaps in this field and offers a starting point for further research in this area.
Indexed as
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.