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

case reporting conceptual modeling mass gathering mass-gathering health mass-gathering medicine

Journal

Prehospital and disaster medicine
ISSN: 1945-1938
Titre abrégé: Prehosp Disaster Med
Pays: United States
ID NLM: 8918173

Informations de publication

Date de publication:
Apr 2021
Historique:
pubmed: 20 2 2021
medline: 26 11 2021
entrez: 19 2 2021
Statut: ppublish

Résumé

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. 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. 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. 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. 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.

Identifiants

pubmed: 33602350
pii: S1049023X21000108
doi: 10.1017/S1049023X21000108
doi:

Types de publication

Journal Article

Langues

eng

Pagination

227-233

Auteurs

Adam Lund (A)

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 (S)

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 (H)

Mass Gathering Medicine Interest Group, Department of Emergency Medicine, University of British Columbia, Canada.

Matthew Brendan Munn (MB)

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 (E)

Mass Gathering Medicine Interest Group, Department of Emergency Medicine, University of British Columbia, Canada.

Jamie Ranse (J)

Department of Emergency Medicine, Gold Coast Health, Southport, Queensland, Australia.
Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland, Australia.

Alison Hutton (A)

School of Nursing, Newcastle University, New South Wales, Australia.

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