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Rethinking Mass-Gathering Domains for Understanding Patient Presentations: A Discussion Paper
- Source :
- Prehospital and Disaster Medicine. 36:121-124
- Publication Year :
- 2020
- Publisher :
- Cambridge University Press (CUP), 2020.
-
Abstract
- Aim:The aim of this paper is to further develop an existing data model for mass-gathering health outcomes.Background:Mass-gathering events (MGEs) occur frequently throughout the world. Having an understanding of the complexities of MGEs is important to determine required health resources. Environmental, psychosocial, and biomedical domains may be a logical starting point to determine how data are being collected and reported in the literature; however, it may be that other factors influencing health resources are not identified within these domains.Method:Based on an exhaustive literature synthesis, this paper is the final paper in a series that explores the collection of variables that impact biomedical presentations associated with attendance/participation in MGEs.Findings:The authors propose further evolution of the Arbon model to include the addition of several domains, including: event environment; command, control, and communication (C3); public health; health promotion; and legacy when reporting the health outcomes of an event.Conclusions:Including a variety of domains that contribute to an MGE allows for formal evaluation of the event, which in turn informs future knowledge and skill development for both the event management group and the wider community.
- Subjects :
- Emergency Medical Services
medicine.medical_specialty
Knowledge management
business.industry
Event (computing)
Public health
Attendance
Emergency Nursing
Variety (cybernetics)
Crowding
Health promotion
Data model
Mass gathering
Emergency Medicine
medicine
Health Resources
Humans
Public Health
business
Psychology
Psychosocial
Forecasting
Subjects
Details
- ISSN :
- 19451938 and 1049023X
- Volume :
- 36
- Database :
- OpenAIRE
- Journal :
- Prehospital and Disaster Medicine
- Accession number :
- edsair.doi.dedup.....4fc28aedf5ec69f5756b782321cab1e8
- Full Text :
- https://doi.org/10.1017/s1049023x20001454