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      Minimum Data Set for Mass-Gathering Health Research and Evaluation: A Discussion Paper

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      Prehospital and Disaster Medicine
      Cambridge University Press (CUP)

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          Abstract

          This paper discusses the need for consistency in mass-gathering data collection and biomedical reporting. Mass gatherings occur frequently throughout the world, and having an understanding of the complexities of mass gatherings is important to inform health services about the possible required health resources. Factors within the environmental, psychosocial and biomedical domains influence the usage of health services at mass gatherings. The biomedical domain includes the categorization of presenting injury or illness, and rates such as patient presentation rate, transferred to hospital rate and referred to hospital rate. These rates provide insight into the usage of onsite health services, prehospital ambulance services. and hospital emergency department services.

          Within the literature, these rates are reported in a manner that is varied, haphazard and author dependent. This paper proposes moving away from an author-dependent practice of collection and reporting of data. An expert consensus approach is proposed as a means of further developing mass-gathering theory and moving beyond the current situation of reporting on individual case studies. To achieve this, a minimum data set with a data dictionary is proposed in an effort to generate conversation about a possible agreed minimum amount and type of information that should be collected consistently for research and evaluation at mass gatherings. Finally, this paper outlines future opportunities that will emerge from the consistent collection and reporting of mass-gathering data, including the possibility for meta-analysis, comparison of events across societies and modeling of various rates to inform health services.

          RanseJ, HuttonA. Minimum data set for mass-gathering health research and evaluation: a discussion paper. Prehosp Disaster Med. 2012;27(6):1-8.

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          Most cited references12

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          Mass Gathering Medicine: A Predictive Model for Patient Presentation and Transport Rates

          This paper reports on research into the influence of environmental factors (including crowd size, temperature, humidity, and venue type) on the number of patients and the patient problems presenting to firstaid services at large, public events in Australia. Regression models were developed to predict rates of patient presentation and of transportation-to-a-hospital for future mass gatherings. To develop a data set and predictive model that can be applied across venues and types of mass gathering events that is not venue or event specific. Data collected will allow informed event planning for future mass gatherings for which health care services are required. Mass gatherings were defined as public events attended by in excess of 25,000 people. Over a period of 12 months, 201 mass gatherings attended by a combined audience in excess of 12 million people were surveyed through-out Australia. The survey was undertaken by St. John Ambulance Australia personnel. The researchers collected data on the incidence and type of patients presenting for treatment and on the environmental factors that may influence these presentations. A standard reporting format and definition of event geography was employed to overcome the event-specific nature of many previous surveys. There are 11,956 patients in the sample. The patient presentation rate across all event types was 0.992/1,000 attendees, and the transportation-to-hospital rate was 0.027/1,000 persons in attendance. The rates of patient presentations declined slightly as crowd sizes increased. The weather (particularly the relative humidity) was related positively to an increase in the rates of presentations. Other factors that influenced the number and type of patients presenting were the mobility of the crowd, the availability of alcohol, the event being enclosed by a boundary, and the number of patient-care personnel on duty. Three regression models were developed to predict presentation rates at future events. Several features of the event environment influence patient presentation rates, and that the prediction of patient load at these events is complex and multifactorial. The use of regression modeling and close attention to existing historical data for an event can improve planning and the provision of health care services at mass gatherings.
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            Forecasting medical work at mass-gathering events: predictive model versus retrospective review.

            Mass-gathering events are dynamic and challenge traditional medical management systems. To improve the system for the provision of first aid at mass-gathering events, an evaluation of two models that assist in forecasting the number of patients presenting for first-aid services was conducted.
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              • Record: found
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              • Article: not found

              Minimum Data Set for Mass-Gathering Health Research and Evaluation: A Discussion Paper

              This paper discusses the need for consistency in mass-gathering data collection and biomedical reporting. Mass gatherings occur frequently throughout the world, and having an understanding of the complexities of mass gatherings is important to inform health services about the possible required health resources. Factors within the environmental, psychosocial and biomedical domains influence the usage of health services at mass gatherings. The biomedical domain includes the categorization of presenting injury or illness, and rates such as patient presentation rate, transferred to hospital rate and referred to hospital rate. These rates provide insight into the usage of onsite health services, prehospital ambulance services. and hospital emergency department services. Within the literature, these rates are reported in a manner that is varied, haphazard and author dependent. This paper proposes moving away from an author-dependent practice of collection and reporting of data. An expert consensus approach is proposed as a means of further developing mass-gathering theory and moving beyond the current situation of reporting on individual case studies. To achieve this, a minimum data set with a data dictionary is proposed in an effort to generate conversation about a possible agreed minimum amount and type of information that should be collected consistently for research and evaluation at mass gatherings. Finally, this paper outlines future opportunities that will emerge from the consistent collection and reporting of mass-gathering data, including the possibility for meta-analysis, comparison of events across societies and modeling of various rates to inform health services. Ranse J , Hutton A . Minimum data set for mass-gathering health research and evaluation: a discussion paper . Prehosp Disaster Med . 2012 ; 27 ( 6 ):1-8.
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                Author and article information

                Journal
                Prehospital and Disaster Medicine
                Prehosp. Disaster med.
                Cambridge University Press (CUP)
                1049-023X
                1945-1938
                December 2012
                September 19 2012
                December 2012
                : 27
                : 6
                : 543-550
                Article
                10.1017/S1049023X12001288
                23174040
                cc851827-506a-49fe-869e-e826e780cbd4
                © 2012

                https://www.cambridge.org/core/terms

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