Development of Risk Evaluation Model for mass gathering events: a proposal based on Roman experience

Background
All the methods reported in international literature point out that some characteristics of MGE can increase the risk of accidents and, as a consequence, increase the MUR of EMS. The regression analysis predicts within reasonable statistical limits the PPR for mass gatherings in Australian experience. On the opposite, the EMS in Rome is used to provide a standard response for MGE related to the number of expected attendants and increases the response level one or more risk conditions are present, but does not have an analytic method.
Aims
This study tries to develop a Mass Gathering Event Risk Scoring Model (MGE-RS) to predict Medical Usage Rate (MUR) that can assist EMS providers planning for mass gatherings across a variety of events and venue types in a metropolitan area, like Rome.
Methods and results
This study includes 35 MGEs hold in Rome in 2005 and 2006 with more than 100.000 the total number of attendants was about 20.320.000; 10.178 patients came to clinical evaluation was, and 800 required transfer to hospital for further treatment. The PPR was 0,5 patients/1.000 persons in attendance to the event.. The TTHR was 0,039 people transported to a hospital/1.000 persons in attendance. The effective MUR (PPR+TTHR) was 0,82/1.000 persons in attendance.
MGE-RS scoring model is a formula that assigns points based on known information (type of event, place, duration, crowd, health system facilities) to predict the MUR of that MGE. The first step was the identification of key factors, based on a review of literature and the roman experience; the second was the identification of the characteristics of any single key factor and the assignment of a score to each voice that expresses the influence on the future outcome. MGE-RS minimum score is 16 points, while the maximum is 77 points. The MGE-RS has been divided in five Risk Level, each one corresponds to a range of MGE-RS scores and expected MUR from < 1,5 to> 45.
During the planning phase it is important to try to organize the most suitable health care response: it must be assured the primary and the emergency care; there must be a sufficient reserve for an immediate response in case of major accident. That means that is not acceptable to understimate the event in the planning phase. In the studied events the predicted MUR calculated with MGE-RS was in range in the 86% of cases and the underestimation rate was 0%.
Conclusions - MGE-RS seems to be a provider friendly tool to be used in planning phase, able to give an acceptable estimation of the Risk Level and Expected MUR of a MGE. Anyway a more accurate report in collecting data, EMS and Hospital records, are the base to improve all the prediction methods.