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dc.contributor.authorLund, A
dc.contributor.authorTurris, S
dc.contributor.authorRabb, H
dc.contributor.authorMunn, MB
dc.contributor.authorChasmar, E
dc.contributor.authorRanse, J
dc.contributor.authorHutton, A
dc.date.accessioned2021-03-04T01:30:33Z
dc.date.available2021-03-04T01:30:33Z
dc.date.issued2021
dc.identifier.issn1049-023X
dc.identifier.doi10.1017/S1049023X21000108
dc.identifier.urihttp://hdl.handle.net/10072/402762
dc.description.abstractIntroduction: 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.
dc.description.peerreviewedYes
dc.languageen
dc.publisherCambridge University Press (CUP)
dc.relation.ispartofpagefrom1
dc.relation.ispartofjournalPrehospital and Disaster Medicine
dc.subject.fieldofresearchBiomedical and clinical sciences
dc.subject.fieldofresearchcode32
dc.titleMeasuring the Masses: Mass-Gathering Medical Case Reporting, Conceptual Modeling - The DREAM Model (Paper 5)
dc.typeJournal article
dc.type.descriptionC1 - Articles
dcterms.bibliographicCitationLund, A; Turris, S; Rabb, H; Munn, MB; Chasmar, E; Ranse, J; Hutton, A, Measuring the Masses: Mass-Gathering Medical Case Reporting, Conceptual Modeling - The DREAM Model (Paper 5), Prehospital and Disaster Medicine, 2021
dc.date.updated2021-03-04T00:04:05Z
gro.description.notepublicThis publication has been entered as an advanced online version in Griffith Research Online.
gro.hasfulltextNo Full Text
gro.griffith.authorRanse, Jamie C.


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