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Validation of a Modified Medical Resource Model for Mass Gatherings

Published online by Cambridge University Press:  26 October 2012

Wayne P. Smith ,
Heather Tuffin ,
Samuel J. Stratton  and
Lee A. Wallis
Wayne P. Smith*
Affiliation:
Division of Emergency Medicine, University of Cape Town and Stellenbosch University, Cape Town, South Africa
Heather Tuffin
Affiliation:
Division of Emergency Medicine, University of Cape Town and Stellenbosch University, Cape Town, South Africa
Samuel J. Stratton
Affiliation:
Fielding School of Public Health and The Geffen School of Medicine, University of California, Los Angeles, California USA
Lee A. Wallis
Affiliation:
Division of Emergency Medicine, University of Cape Town and Stellenbosch University, Cape Town, South Africa
*
Correspondence: Wayne P. Smith, BSc, MBChB, EMDM, ACEM (SA) Private Bag X24, Bellville 7535 Cape Town, South Africa E-mail smithw@iafrica.com
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Abstract

Introduction

A modified Medical Resource Model to predict the medical resources required at mass gatherings based on the risk profile of events has been developed. This study was undertaken to validate this tool using data from events held in both a developed and a developing country.

Methods

A retrospective study was conducted utilizing prospectively gathered data from individual events at Old Trafford Stadium in Manchester, United Kingdom, and Ellis Park Stadium, Johannesburg, South Africa. Both stadia are similar in design and spectator capacity. Data for Professional Football as well as Rugby League and Rugby Union (respectively) matches were used for the study. The medical resources predicted for the events were determined by entering the risk profile of each of the events into the Medical Resource Model. A recently developed South African tool was used to predetermine medical staffing for mass gatherings. For the study, the medical resources actually required to deal with the patient load for events within the control sample from the two stadia were compared with the number of needed resources predicted by the Medical Resource Model when that tool was applied retrospectively to the study events. The comparison was used to determine if the newly developed tool was either over- or under-predicting the resource requirements.

Results

In the case of Ellis Park, the model under-predicted the basic life support (BLS) requirement for 1.5% of the events in the data set. Mean over-prediction was 209.1 minutes for BLS availability. Old Trafford displayed no events for which the Medical Resource Model would have under-predicted. The mean over-prediction of BLS availability for Old Trafford was 671.6 minutes. The intermediate life support (ILS) requirement for Ellis Park was under-predicted for seven of the total 66 events (10.6% of the events), all of which had one factor in common, that being relatively low spectator attendance numbers. Modelling for ILS at Old Trafford did not under-predict for any events. The ILS requirements showed a mean over-prediction of 161.4 minutes ILS availability for Ellis Park compared with 425.2 minutes for Old Trafford. Of the events held at Ellis Park, the Medical Resource Model under-predicted the ambulance requirement in 4.5% of the events. For Old Trafford events, the under-prediction was higher: 7.5% of cases.

Conclusion

The medical resources that are deployed at a mass gathering should best match the requirement for patient care at a particular event. An important consideration for any model is that it does not continually under-predict the resources required in relation to the actual requirement. With the exception of a specific subset of events at Ellis Park, the rate of under-prediction for this model was acceptable.

SmithWP, TuffinH, StrattonSJ, WallisLA. Validation of a Modified Medical Resource Model for Mass Gatherings. Prehosp Disaster Med.2013;28(1):1-7.

Keywords

EMSemergency medical servicesevent medicinemass gatheringmedical emergencysports medicine
Type
Original Research
Information
Prehospital and Disaster Medicine , Volume 28 , Issue 1 , February 2013 , pp. 16 - 22
Copyright
Copyright © World Association for Disaster and Emergency Medicine 2012

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