Evidence map›Paper›PMID 40053123›Full record

ArticleJMIR formative research2025

HUMAn, a Real-Time Evolutive Patient Model for Major Incident Simulation: Development and Validation Study.

Maxence Laurent, Arnaud Jaccard, Laurent Suppan, Elio Erriquez, Xavier Good, Eric Golay, Dominique Jaccard, Mélanie Suppan

Abstract readValidation Study
In one paragraph

Article in JMIR formative research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Trial
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Maxence LaurentMedia Engineering Institute, School of Management and Engineering Vaud, University of Applied Sciences and Arts of Western Switzerland, Avenue des Sports 20, Yverdon, 1400, Switzerland, 41 244592638.ORCID 0000-0003-0257-3489
Arnaud JaccardFaculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland.ORCID 0000-0001-8065-3199
Laurent SuppanDivision of Emergency Medicine, Department of Anesthesiology, Clinical Pharmacology, Intensive Care and Emergency Medicine, University of Geneva Hospitals and Faculty of Medicine, Geneva, Switzerland.ORCID 0000-0001-6989-6421
Elio ErriquezDivision of Emergency Medicine, Department of Anesthesiology, Clinical Pharmacology, Intensive Care and Emergency Medicine, University of Geneva Hospitals and Faculty of Medicine, Geneva, Switzerland.ORCID 0009-0005-6996-7556
Xavier GoodMedia Engineering Institute, School of Management and Engineering Vaud, University of Applied Sciences and Arts of Western Switzerland, Avenue des Sports 20, Yverdon, 1400, Switzerland, 41 244592638.ORCID 0009-0002-8798-3179
Eric GolayDivision of Emergency Medicine, Department of Anesthesiology, Clinical Pharmacology, Intensive Care and Emergency Medicine, University of Geneva Hospitals and Faculty of Medicine, Geneva, Switzerland.ORCID 0000-0002-7348-470X
Dominique JaccardMedia Engineering Institute, School of Management and Engineering Vaud, University of Applied Sciences and Arts of Western Switzerland, Avenue des Sports 20, Yverdon, 1400, Switzerland, 41 244592638.ORCID 0000-0002-4037-2322
Mélanie SuppanDivision of Anesthesiology, Department of Anesthesiology, Clinical Pharmacology, Intensive Care and Emergency Medicine, University of Geneva Hospitals and Faculty of Medicine, Geneva, Switzerland.ORCID 0000-0002-8807-9619

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Major incidents correspond to any situation where the location, number, severity, or type of casualties requires extraordinary resources. Major incident management must be efficient to save as many lives as possible. As any paramedic or emergency medical technician may unexpectedly have to respond to major incidents, regular training is mandatory. Those trainings usually include simulations. The vast majority of major incident simulations are limited by the fact that simulated patients do not evolve during the simulation, regardless of the time elapsed and treatment decisions. Therefore, most simulations fail to incorporate the critical temporal effect of decision-making. Objective: This study aimed to develop and validate a simplified mathematical model of physiology, capable of plausibly simulating the real-time evolution of several injuries. Methods: A modified version of the user-centered design framework, including a relevance, development, and validation phase, was used to define the development process of the physiological model. A 12-member design and development team was established, including prehospital physicians, paramedics, and computer scientists. To determine whether the developed model was clinically realistic, 15 experienced professionals working in the prehospital field participated in the validation phase. They were asked to rate clinical and physiological parameters according to a 5-point Likert scale ranging from 1 (impossible) to 5 (absolutely realistic). Results: The design and development team led to the development of the HUMAn model (Human is an Uncomplicated Model of Anatomy). During the relevance phase, the team defined the needed features of the model: clinically realistic, able to compute the evolution of prehospital vital signs, yet simple enough to allow real-time computation for several simulated patients on regular computers or tablets. During the development phase, iterations led to the development of a heart-lung-brain interaction model coupled to functional blocks representing the main anatomical body parts. During the validation phase, the evolution of nine simulated patients presenting pathologies devised to test the different systems and their interactions was assessed. Overall, clinical parameters of all patients had a median rating of 5 (absolutely realistic; IQR 4-5). Most (n=52, 96%) individual clinical parameters had a median rating of 5, the remainder (n=2, 4%) being rated 4. Overall physiological parameters of all patients had a median rating of 5 (absolutely realistic; IQR 3-5). The majority of individual physiological parameters (n=43, 79%) had a median rating of 5, with (n=9, 17%) rated 4, and only (n=2 ,4%) rated 3. Conclusions: A simplified model of trauma patient evolution was successfully created and deemed clinically realistic by experienced clinicians. This model should now be included in computer-based simulations and its impact on the teaching of major incident management assessed through randomized trials.

Indexed as

Mass Casualty IncidentsPatient SimulationComputer SimulationHumansReproducibility of Resultscomputer simulationcontinuing educationemergency medicinehealthcare professional educationmajor incident managementmass casualtiesmathematical modelphysiological modelprofessional education

Identifiers

PMID40053123
PMCPMC11908467

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Registered trials

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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.