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Measuring the Masses: Mass-Gathering Medical Case Reporting, Conceptual Modeling – The DREAM Model (Paper 5)

Published online by Cambridge University Press:  19 February 2021

Adam Lund ,
Sheila Turris ,
Haddon Rabb Open the ORCID record for Haddon Rabb [Opens in a new window] ,
Matthew Brendan Munn ,
Elizabeth Chasmar ,
Jamie Ranse  and
Alison Hutton Open the ORCID record for Alison Hutton [Opens in a new window]
Adam Lund*
Affiliation:
Department of Emergency Medicine, University of British Columbia, Vancouver, British Columbia, Canada Mass Gathering Medicine Interest Group, Department of Emergency Medicine, University of British Columbia, Canada University of British Columbia, School of Nursing, Vancouver, British Columbia, Canada
Sheila Turris
Affiliation:
Department of Emergency Medicine, University of British Columbia, Vancouver, British Columbia, Canada Mass Gathering Medicine Interest Group, Department of Emergency Medicine, University of British Columbia, Canada
Haddon Rabb
Affiliation:
Mass Gathering Medicine Interest Group, Department of Emergency Medicine, University of British Columbia, Canada
Matthew Brendan Munn
Affiliation:
Department of Emergency Medicine, University of British Columbia, Vancouver, British Columbia, Canada Mass Gathering Medicine Interest Group, Department of Emergency Medicine, University of British Columbia, Canada
Elizabeth Chasmar
Affiliation:
Mass Gathering Medicine Interest Group, Department of Emergency Medicine, University of British Columbia, Canada
Jamie Ranse
Affiliation:
Department of Emergency Medicine, Gold Coast Health, Southport, Queensland, Australia Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland, Australia
Alison Hutton
Affiliation:
School of Nursing, Newcastle University, New South Wales, Australia
*
Correspondence: Adam Lund, BSc, MD, MEd, FRCPCMass Gathering Medicine Interest GroupUniversity of British ColumbiaVancouver, British Columbia, CanadaE-mail: [email protected]
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Abstract

Introduction:

Without a robust evidence base to support recommendations for first aid, health, and medical services at mass gatherings (MGs), levels of care will continue to vary. Streamlining and standardizing post-event reporting for MG medical services could improve inter-event comparability, and prospectively influence event safety and planning through the application of a research template, thereby supporting and promoting growth of the evidence base and the operational safety of this discipline. Understanding the relationships between categories of variables is key. The present paper is focused on theory building, providing an evolving conceptual model, laying the groundwork for exploring the relationships between categories of variables pertaining the health outcomes of MGs.

Methods:

A content analysis of 54 published post-event medical case reports, including a comparison of the features of published data models for MG health outcomes.

Findings:

A layered model of essential conceptual components for post-event medical reporting is presented as the Data Reporting, Evaluation, & Analysis for Mass-Gathering Medicine (DREAM) model. This model is relational and embeds data domains, organized operationally, into “inputs,” “modifiers,” “actuals,” and “outputs” and organized temporally into pre-, during, post-event, and reporting phases.

Discussion:

Situating the DREAM model in relation to existing models for data collection vis a vis health outcomes, the authors provide a detailed discussion on similarities and points of difference.

Conclusion:

Currently, data collection and analysis related to understanding health outcomes arising from MGs is not informed by robust conceptual models. This paper is part of a series of nested papers focused on the future state of post-event medical reporting.

Keywords

case reportingconceptual modelingmass gatheringmass-gathering healthmass-gathering medicine
Type
Special Report
Information
Prehospital and Disaster Medicine , Volume 36 , Issue 2 , April 2021 , pp. 227 - 233
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Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of the World Association for Disaster and Emergency Medicine

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