ArticleJMIR formative research2026
Digital Twin-Based Virtual Hospital Platform for IT Outage Disaster Response Training: Implementation and Evaluation Study.
Article in JMIR formative research, 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHospital IT outages severely disrupt clinical workflows and use of electronic medical records, threatening patient safety and operational continuity. Traditional disaster response training faces limitations, including high resource requirements, restricted repeatability, and inability to be conducted without interrupting 24/7 hospital operations. Digital twin technology enables realistic, repeatable simulation training in virtual environments, avoiding operational disruption.
objectiveThis study developed and implemented a digital twin-based virtual hospital platform for level 1 IT outage disaster response training and evaluated its feasibility through quantitative performance metrics and participant survey feedback.
methodsA digital twin-based virtual hospital platform modeling 317 clinical spaces and 6 building entrances of Yongin Severance Hospital, South Korea, was developed to simulate a hospital information system failure (code white level 1 IT outage) with 7 patient cases of varying complexity levels, covering complete outpatient workflows from registration to payment. A total of 60 multidisciplinary participants (physicians, nurses, laboratory technicians, pharmacists, and administrative staff) were recruited through purposive sampling from clinical departments and support services directly involved in outpatient IT outage response. Emergency prescription and patient information lookup systems were integrated into the training. Performance evaluation included scenario completion rates, prescription accuracy, completion times, and operational readiness scores. Training outcomes were compared with 2023 conventional training records from the same institution using descriptive metrics. Open-ended survey responses were analyzed using structured content summarization with text mining and word cloud techniques. A 7-item operational readiness checklist was assessed by a panel of 5 training facilitators to evaluate system functional completeness.
resultsIn July 2024, a total of 60 multidisciplinary participants completed the training exercise. All 7 patient scenarios achieved 100% completion rates, with perfect accuracy in medical billing concordance and prescription entry timeliness. Scenario completion times ranged from 25 to 47 minutes, with variations reflecting testing wait times and workflow complexity. The overall operational readiness score was 80% (with 70% for digital twin platform operational readiness and 90% for emergency prescription program operational readiness). Training reduced resource consumption by 70 minutes compared to the 2023 conventional training approach, decreasing full-time equivalent requirements from 0.072 to 0.038. Open-ended survey feedback yielded 5 content categories (target extensions, mock training ideas, drug and prescription system improvement, operations and evaluation systems, and process improvement), with "realism," "collaboration," and "prescription" as the most frequent keywords.
conclusionsThis proof-of-concept study demonstrates that a simulation-oriented digital twin platform can support multi-department IT disaster response training with complete workflow execution. Identified technical gaps in user permissions and prescription classification provide a concrete development road map for institutional deployment.
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.