ReviewEuropean journal of public health2025
Could digital twins be the next revolution in healthcare?
Review in European journal of public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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
7 citing papers in PubMed.
- A Lean-based Digital Twin model for planning and governance in secondary and tertiary hospital networks.BMC health services research · 2026Article
- Healthcare Digital Twins Across Scales: A Narrative Review and Five-Level Conceptual Framework.Healthcare (Basel, Switzerland) · 2026Review
- Analysis of digital twin applications in nursing practice and education: a scoping review.Journal of educational evaluation for health professions · 2026Article
- Trust By Design: Enabling Responsible Precision Health Through Blockchain-Powered Digital Twins And Trusted AI.Blockchain in healthcare today · 2025Article
- TWINVAX: conceptual model of a digital twin for immunisation services in primary health care.Frontiers in public health · 2025Article
- Simulating the blood transfusion system in Kenya: Modelling methods and exploratory analyses.PLOS global public health · 2025Article
- Simulation-based assessment of digital twin systems for immunisation.Frontiers in digital health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A Digital Twin (DT) can be understood as a representation of a real asset, a virtual replica of a physical object, process, or even a system. They have been used in managing healthcare facilities, streamlining care processes, personalizing treatments, and enhancing patient recovery. The potential impact of this tool on our society and its well-being is quite significant. A quick review of the literature was carried out using the terms ('Digital Twins') and ('Digital Health'), and (Health Care) with a time interval of up to 5 years (2018-23). Using the PRISMA Method, the search was conducted in six academic databases: IEEE Xplore, Dimensions, Scopus, Web of Science, PubMed, and ACM. After applying the search strings and the exclusion criteria, a total of 13 publications were identified and listed to constitute and support the discussion of this article. The selected studies were categorized into 2 groups according to their application in healthcare: A group of clinical applications, subdivided into topics on personalized care and reproduction of biological structures and another group of operational applications, subdivided into topics such as optimization of operational processes, reproduction of physical structures, and development of devices and drugs. The use of DT in healthcare presents important challenges related to data integration, privacy, and interoperability. However, trends indicate exciting potential in personalizing treatment, prevention, remote monitoring, informed decision-making, and process management, which can result in significant improvements in quality and efficiency in healthcare.
Indexed as
Identifiers
What OpenQuestion holds
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.