Evidence map›Paper›PMID 34275344›Full record

ArticleHuman factors2022

Dynamic Communication Quantification Model for Measuring Information Management During Mass-Casualty Incident Simulations.

Omer Perry, Eli Jaffe, Yuval Bitan

Abstract read
In one paragraph

Article in Human factors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Digital coordination in mass casualty incidents: a retrospective analysis of prehospital distribution times before and after IVENA-MANV implementation.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2026
    Observational
  2. Observational
  3. Article
  4. Article
  5. Key performance indicators in pre-hospital response to disasters and mass casualty incidents: a scoping review.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2024
    Article
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

3 authors.

Omer Perry26732 Ben-Gurion University of the Negev, Beer-Sheva, Israel.ORCID 0000-0002-1994-7291
Eli Jaffe26732 Ben-Gurion University of the Negev, Beer-Sheva, Israel.
Yuval Bitan26732 Ben-Gurion University of the Negev, Beer-Sheva, Israel.ORCID 0000-0001-7053-7012

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo develop a new model to quantify information management dynamically and to identify factors that lead to information gaps.

backgroundInformation management is a core task for emergency medical service (EMS) team leaders during the prehospital phase of a mass-casualty incident (MCI). Lessons learned from past MCIs indicate that poor information management can lead to increased mortality. Various instruments are used to evaluate information management during MCI training simulations, but the challenge of measuring and improving team leaders' abilities to manage information remains.

methodThe Dynamic Communication Quantification (DCQ) model was developed based on the knowledge representation typology. Using multi point-of-view synchronized video, the model quantifies and visualizes information management. It was applied to six MCI simulations between 2014 and 2019, to identify factors that led to information gaps, and compared with other evaluation methods.

resultsOut of the three methods applied, only the DCQ model revealed two factors that led to information gaps: first, consolidation of numerous casualties from different areas, and second, tracking of casualty arrivals to the medical treatment area and departures from the MCI site.

conclusionThe DCQ model allows information management to be objectively quantified. Thus, it reveals a new layer of knowledge, presenting information gaps during an MCI. Because the model is applicable to all MCI team leaders, it can make MCI simulations more effective. APPLICATION: This DCQ model quantifies information management dynamically during MCI training simulations.

Indexed as

Disaster PlanningEmergency Medical ServicesMass Casualty IncidentsCommunicationHumansInformation Managementcommunicationinformation managementmass-casualty incidentsimulationteamwork

Identifiers

PMID34275344
PMCPMC8873974

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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.