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Measuring the Masses: Domains Driving Data Collection and Analysis for the Health Outcomes of Mass Gatherings (Paper 3)

Published online by Cambridge University Press:  19 February 2021

Sheila Turris ,
Adam Lund ,
Matthew Brendan Munn ,
Elizabeth Chasmar ,
Haddon Rabb Open the ORCID record for Haddon Rabb [Opens in a new window] ,
Christopher W. Callaghan ,
Jamie Ranse  and
Alison Hutton Open the ORCID record for Alison Hutton [Opens in a new window]
Sheila Turris*
Affiliation:
Department of Emergency Medicine, University of British Columbia (UBC), Vancouver, British Columbia, Canada Mass Gathering Medicine Interest Group, Department of Emergency Medicine, University of British Columbia, Canada
Adam Lund
Affiliation:
Department of Emergency Medicine, University of British Columbia (UBC), Vancouver, British Columbia, Canada Mass Gathering Medicine Interest Group, Department of Emergency Medicine, University of British Columbia, Canada
Matthew Brendan Munn
Affiliation:
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
Haddon Rabb
Affiliation:
Mass Gathering Medicine Interest Group, Department of Emergency Medicine, University of British Columbia, Canada
Christopher W. Callaghan
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 and Midwifery, University of Newcastle, NSW, Australia
*
Correspondence: Sheila Turris, RN, BHSc, MSN, PhD, Mass Gathering Medicine Interest Group, University of British Columbia, Vancouver, British Columbia, Canada, E-mail: Sheila.Turris@ubc.ca
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Abstract

Introduction:

Without a robust evidence base to support recommendations for medical services at mass gatherings (MGs), levels of care will continue to vary and preventable morbidity and mortality will exist. Accordingly, researchers and clinicians publish case reports and case series to capture and explain some of the health interventions, health outcomes, and host community impacts of MGs. Streamlining and standardizing post-event reporting for MG medical services and associated health outcomes could improve inter-event comparability, thereby supporting and promoting growth of the evidence base for this discipline. The present paper is focused on theory building, proposing a set of domains for data that may support increasingly comprehensive, yet lean, reporting on the health outcomes of MGs. This paper is paired with another presenting a proposal for a post-event reporting template.

Methods:

The conceptual categories of data presented are based on a textual analysis of 54 published post-event medical case reports and a comparison of the features of published data models for MG health outcomes.

Findings:

A comparison of existing data models illustrates that none of the models are explicitly informed by a conceptual lens. Based on an analysis of the literature reviewed, four data domains emerged. These included: (i) the Event Domain, (ii) the Hazard and Risk Domain, (iii) the Capacity Domain, and (iv) the Clinical Domain. These domains mapped to 16 sub-domains.

Discussion:

Data modelling for the health outcomes related to MGs is currently in its infancy. The proposed illustration is a set of operationally relevant data domains that apply equally to small, medium, and large-sized events. Further development of these domains could move the MG community forward and shift post-event health outcomes reporting in the direction of increasing consistency and comprehensiveness.

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 reportingdata modelingevent medicinemass gatheringmass-gathering healthmass-gathering medicine
Type
Special Report
Information
Prehospital and Disaster Medicine , Volume 36 , Issue 2 , April 2021 , pp. 211 - 217
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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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