Hostname: page-component-cd9895bd7-lnqnp Total loading time: 0 Render date: 2024-12-23T04:35:57.087Z Has data issue: false hasContentIssue false
  • English
  • Français

The Development of PRIMA - A Belgian Prediction Model for Patient Encounters at Mass Gatherings

Published online by Cambridge University Press:  29 July 2020

Kris Spaepen Open the ORCID record for Kris Spaepen [Opens in a new window] ,
Winne AP Haenen  and
Ives Hubloue
Kris Spaepen*
Affiliation:
Vrije Universiteit Brussel, Research Group on Emergency and Disaster Medicine, Brussels, Belgium
Winne AP Haenen
Affiliation:
Crisis Management at Federal Public Health Service, Brussels, Belgium
Ives Hubloue
Affiliation:
Vrije Universiteit Brussel, Research Group on Emergency and Disaster Medicine, Brussels, Belgium
*
Correspondence: Kris Spaepen, RN, MSc, EMDM, Research Group on Emergency and Disaster Medicine, Vrije Universiteit Brussel, Faculty of Medicine and Pharmacy, Laarbeeklaan 103, 1090Brussels, Belgium, E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Introduction:

Mass gatherings (MGs) grow in frequency around the world. With the intrinsic potential for significant health risks for all involved, MGs pose a challenge for those responsible for the provision of on-site medical care. Belgian law obliges local governments to identify and analyze the risks involving a MG. Though medical risk factors are long known, all too often, resourcing for in-event health services is based on anecdotal and previous experiences.

Problem:

Despite the fast-evolving science on MGs, the lack of reliable tools – based on empirical and analytical approaches – to predict patient presentation rates (PPRs) at MGs remains.

Methods:

A two-step method was followed to develop, update, and support a Plan Risk Manifestation (PRIMA) program. First, a continuous systematic literature review was conducted. Once developed, the model was run using data obtained from Belgian Federal Public Service (FPS; Brussels, Belgium) Health, Food Chain Safety, and Environment (HFCSE); event organizers; and municipalities.

Results:

In total, 231 studies and documents were included to form the program. With the data provided, three variables were computed to run the calculation model to predict the PPR. Three medical risk axes were defined for this model: (1) isolation risk; (2) population risk; and (3) risk at illness. A combined dataset was derived from the prediction of the PRIMA program combined with the actual data obtained after the MG. This proved a solid basis for the calculation model of the PRIMA program.

Conclusion:

Despite that validation is needed, the PRIMA program and its prediction model for PPRs at MGs carries the promise of a general, applicable prediction and risk analysis tool for a multitude of events.

Keywords

Emergency Medical Servicesmass gatheringpatient presentationspublic healthrisk assessment
Type
Original Research
Information
Prehospital and Disaster Medicine , Volume 35 , Issue 5 , October 2020 , pp. 554 - 560
Copyright
© World Association for Disaster and Emergency Medicine 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

World Health Organization. Public health for mass gatherings: key considerations. Geneva, Switzerland: World Health Organization; 2015. https://www.who.int/ihr/publications/WHO_HSE_GCR_2015.5/en/. Accessed March 4, 2019.Google Scholar
Arbon, P. Mass-gathering medicine: a review of the evidence and future directions for research. Prehosp Disaster Med. 2007;22(2):131–135.CrossRefGoogle ScholarPubMed
Friedman, NMG, O’Connor, EK, Munro, T, Goroff, D. Mass-gathering medical care provided by a collegiate-based first response service at an annual college music festival and campus-wide celebration. Prehosp Disaster Med. 2019;34(1):98–103.CrossRefGoogle Scholar
Federal Public Service Interior. Royal Decree of February 16, 2006 regarding the Contingency and Intervention Plans; Brussels, Belgium; 2006.Google Scholar
Arbon, P, Bridgewater, FHG, Smith, C. Mass gathering medicine: a predictive model for patient presentation and transport rates. Prehosp Disaster Med. 2001;16(3):150–158.CrossRefGoogle ScholarPubMed
Milsten, AM, Maguire, BJ, Bissell, RA, Seaman, KG. Mass-gathering medical care: a review of the literature. Prehosp Disaster Med. 2002;17(3):151–162.CrossRefGoogle ScholarPubMed
Moore, R, Williamson, K, Sochor, M, Brady, WJ. Large-event medicine - event characteristics impacting medical need. Am J Emerg Med. 2011;29(9):1217–1221.Google ScholarPubMed
Zeitz, KM, Zeitz, CJ, Arbon, P. Forecasting medical work at mass-gathering events: predictive model versus retrospective review. Prehosp Disaster Med. 2005;20(3):164–168.CrossRefGoogle ScholarPubMed
Westrol, MS, Koneru, S, McIntyre, N, Caruso, AT, Arshad, FH, Merlin, MA. Music genre as a predictor of resource utilization at outdoor music concerts. Prehosp Disaster Med. 2017;32(3):289–296.CrossRefGoogle ScholarPubMed
Alquthami, AH, Pines, JM. A systematic review of noncommunicable health issues in mass gatherings. Prehosp Disaster Med. 2014;29(2):167–175.CrossRefGoogle ScholarPubMed
Locoh-Donou, S, Guofen, Y, Welcher, M, Berry, T, O’Connor, RE, Brady, WJ. Mass-gathering medicine: a descriptive analysis of a range of mass-gathering event types. Am J Emerg Med. 2013;31(5):843–846.CrossRefGoogle ScholarPubMed
Dutch, MJ, Austin, KB. Hospital in the field: prehospital management of GHB intoxication by medical assistance teams. Prehosp Disaster Med. 2012;27(5):463–467.CrossRefGoogle ScholarPubMed
Gogaert, S, Vande Veegaete, A, Scholliers, A, Vandekerckhove, P. “MedTRIS” (Medical Triage and Registration Informatics System): a web-based client server system for the registration of patients being treated in first aid posts at public events and mass gatherings. Prehosp Disaster Med. 2016;31(5):557–562.CrossRefGoogle ScholarPubMed
Arbon, P, Bottema, M, Zeitz, K, et al. Nonlinear modelling for predicting patient presentation rates for mass gatherings. Prehosp Disaster Med. 2018;33(4):362–367.CrossRefGoogle ScholarPubMed
Hartman, N, Williamson, A, Sojka, B, et al. Predicting resource use at mass gatherings using a simplified stratification scoring model. Am J Emerg Med. 2008;27(3):337–343.Google Scholar
Federal Public Service Health Food Chain Safety and Health. Medical Intervention Plan (MIP) Brussels; 2017. https://www.health.belgium.be/en/node/31238. Published 2017. Accessed July 1, 2017.Google Scholar
Liberati, A, Altman, D, Tetzlaff, J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med. 2009;6(7).CrossRefGoogle ScholarPubMed
Ranse, J, Hutton, A, Turris, SA, Lund, A. Enhancing the minimum data set for mass-gathering research and evaluation: an integrative literature review. Prehosp Disaster Med. 2014;29(3):280–289.CrossRefGoogle Scholar
Ranse, J, Hutton, A, Keene, T, et al. Health service impact from mass gatherings: a systematic literature review. Prehosp Disaster Med. 2017;32(S1):S138–S139.CrossRefGoogle ScholarPubMed
Turris, SA, Callaghan, CW, Rabb, H, Munn, MB, Lund, A. On the way out: an analysis of patient transfers from four large-scale North American music festivals over two years. Prehosp Disaster Med. 2019;34(1):72–81.CrossRefGoogle Scholar
Lund, A, Turris, SA, Bowles, R, et al. Mass-gathering health research foundational theory: Part 1 - population models for mass gatherings—Corrigendum. Prehosp Disaster Med. 2015;30(2):223.Google Scholar
Perkins, GD, Handley, AJ, Koster, RW, et al. European Resuscitation Council Guidelines for Resuscitation 2015: Section 2. Adult basic life support and automated external defibrillation. Resuscitation. 2015;95:81–99.CrossRefGoogle ScholarPubMed
Hutton, A, Ranse, J, Munn, MB. Developing public health initiatives through understanding motivations of the audience at mass-gathering events. Prehosp Disaster Med. 2018;33(2):191–196.CrossRefGoogle ScholarPubMed
Ranse, J, Hutton, A. Minimum data set for mass-gathering health research and evaluation: a discussion paper. Prehosp Disaster Med. 2012;27(6):543–550.CrossRefGoogle ScholarPubMed
Sanders, AB, Criss, E, Steckl, P, Meislin, HW, Raife, J, Allen, D. An analysis of medical care at mass gatherings. Ann Emerg Med. 1986;15(5):515–519.CrossRefGoogle ScholarPubMed
Lund, A, Turris, S. The event chain of survival in the context of music festivals: a framework for improving outcomes at major planned events. Prehosp Disaster Med. 2017;32(4):437–443.CrossRefGoogle ScholarPubMed
Supplementary material: File

Spaepen et al. supplementary material

Spaepen et al. supplementary material

Download Spaepen et al. supplementary material(File)
File 939.7 KB