Evidence map›Paper›PMID 42192332›Full record

ArticleBMC medical research methodology2026

Simulating crisis triage: a methodological framework for evaluating ventilator allocation under crisis standards of care.

B Corbett Walsh, Jianan Zhu, Yang Feng, Rebecca A Betensky, Deepak Pradhan

Abstract read
In one paragraph

Article in BMC medical research methodology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

B Corbett WalshDivision of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, University of Los Angeles David Geffen School of Medicine, Los Angeles, CA, USA. BCWalsh@mednet.ucla.edu.ORCID 0000-0002-6343-4717
Jianan ZhuDepartment of Biostatistics, New York University School of Global Public Health, New York, NY, USA.
Yang FengDepartment of Biostatistics, New York University School of Global Public Health, New York, NY, USA.
Rebecca A BetenskyDepartment of Biostatistics, New York University School of Global Public Health, New York, NY, USA.
Deepak PradhanDivision of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCrisis Standards of Care (CSC) may require rationing of life-sustaining resources, such as mechanical ventilation, during public health emergencies. Simulation modeling offers a scalable, transparent method to evaluate triage frameworks before implementation. While ventilator triage frameworks vary in their use of exclusion criteria, comorbidity adjustments, and reassessment frequency, few have been rigorously compared using real-world data under realistic surge conditions. Robust platforms that simulate both front-end (initiation) and back-end (reassessment or reallocation) triage are critical for evaluating clinical, operational, and ethical performance.

methodsWe developed a computational simulation platform using retrospective real-world data from intubated adults during the Spring 2020 COVID-19 surge across a large New York City health system. The simulated surge cohort included all patients mechanically ventilated between March 1 and June 30, 2020. A crisis cohort was defined as those patients receiving ventilation once 95% of the health system's pre-pandemic ventilator supply was in use. Eight CSC strategies were evaluated, including policies from New York, Pennsylvania, Maryland, Canada, two academic frameworks, a lottery-based system, and first-come first-served. Strategies varied in their use of exclusion criteria, comorbidity modifiers, reassessment intervals, and prioritization for special populations. Daily ICU census and ventilator availability were used to simulate resource strain and drive triage decision-making. Patients simulated for ventilator rationing were simulated to expire. Manual abstraction of comorbidities and structured rules for imputing missing SOFA subscores were applied uniformly.

resultsThe platform simulated 10,000 iterations per strategy and included 2,365 intubated patients. Final analyses will be published separately.

conclusionThis platform provides a scalable, reproducible framework for evaluating ventilator triage strategies under pandemic-like conditions. By integrating both initial triage and serial reassessment (front- and back-end) logic, operational constraints, and clinical trajectories, it enables detailed comparisons of survival, resource utilization, and prognostic accuracy. The simulation also supports ethical evaluation by testing the practical impact of exclusion and comorbidity-based criteria. Such models can assist governments, health systems, and public health agencies in designing triage protocols that are evidence-informed, ethically defensible, and operationally feasible. This work demonstrates how computational modeling can strengthen health system preparedness and support public trust.

Indexed as

Computer SimulationCOVID-19Health Care RationingRespiration, ArtificialStandard of CareTriageVentilators, MechanicalFemaleHumansNew York CityPandemicsRetrospective StudiesSARS-CoV-2Computational simulationCOVID-19Crisis standards of careDecision MakingEthicsResource AllocationSimulation modelingTriage protocolsVentilatorVentilator allocation

Identifiers

PMID42192332
PMCPMC13267345

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LicenceCC BY
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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.