The introduction of advanced practitioner roles has challenged the traditional boundaries of health care. While studies have been undertaken to understand the role of physicians in respect of mass-gathering medicine, the role of advanced nurse practitioners (ANPs) has not been investigated.

Does the presence of an ANP reduce the referral rates of patients presenting for medical care at mass-gathering events to external health care resources?

A prospective observational study was undertaken to determine whether the presence of an ANP would reduce the patient referral rate to external health care services by first aiders and paramedics working within an event medical team. Patients identified as requiring referral were reviewed by an ANP as part of the on-site medical provision for four mass-gathering events in the south of England. Additionally, information was gathered identifying which patients would have been transported to hospital by ambulance compared to those actually transported following ANP review. Statistical analysis was undertaken for three key measures (referrals to all local health resources, referrals to hospital-based acute services, and transfers to hospital by ambulance).

A rounded total of 842,000 people attended four mass-gathering events held over 14 days. Of these, 652 presented for medical care, many self-referring.

Using a one-tailed Fisher’s Exact Test and Phi analysis, this study demonstrated statistically significant reductions in the overall referral of patients to all external health care resources (P<.001; φ=0.44), to the emergency department (ED; P<.001; φ=0.43), and a reduction in ambulance transport (P<.001; φ=0.42). Effect size analysis demonstrated a medium-sized effect evident for all of the above, which was also demonstrated in economic terms.

The event medical team would have referred 105 (16.3%) of the 652 patient presentations to external health care services; 47 (7.2%) would have been transported by ambulance. In comparison, the ANP referred 23 patients (3.5%) with 11 (1.7%) being transported by ambulance. It also was noted that the first aiders and paramedics could be more selective in their referral habits that were focused primarily on the ED.

Appropriately trained and experienced ANPs working within event medical teams have a positive impact on referral rates from mass-gathering events.

KempAE . Mass-gathering Events: The Role of Advanced Nurse Practitioners in Reducing Referrals to Local Health Care Agencies. Prehosp Disaster Med. 2016;31(1):58–63.

Predicting the number of patient encounters and transports during mass gatherings can be challenging. The nature of these events necessitates that proper resources are available to meet the needs that arise. Several prediction models to assist event planners in forecasting medical utilization have been proposed in the literature.

The objective of this study was to determine the accuracy of the Arbon and Hartman models in predicting the number of patient encounters and transportations from the Baltimore Grand Prix (BGP), held in 2011 and 2012. It was hypothesized that the Arbon method, which utilizes regression model-derived equations to estimate, would be more accurate than the Hartman model, which categorizes events into only three discreet severity types.

This retrospective analysis of the BGP utilized data collected from an electronic patient tracker system. The actual number of patients evaluated and transported at the BGP was tabulated and compared to the numbers predicted by the two studied models. Several environmental features including weather, crowd attendance, and presence of alcohol were used in the Arbon and Hartman models.

Approximately 130,000 spectators attended the first event, and approximately 131,000 attended the second. The number of patient encounters per day ranged from 19 to 57 in 2011, and the number of transports from the scene ranged from two to nine. In 2012, the number of patients ranged from 19 to 44 per day, and the number of transports to emergency departments ranged from four to nine. With the exception of one day in 2011, the Arbon model overpredicted the number of encounters. For both events, the Hartman model overpredicted the number of patient encounters. In regard to hospital transports, the Arbon model underpredicted the actual numbers whereas the Hartman model both overpredicted and underpredicted the number of transports from both events, varying by day.

These findings call attention to the need for the development of a versatile and accurate model that can more accurately predict the number of patient encounters and transports associated with mass-gathering events so that medical needs can be anticipated and sufficient resources can be provided.

NableJV , MargolisAM , LawnerBJ , HirshonJM , PerriconeAJ , GalvagnoSM , LeeD , MillinMG , BissellRA , AlcortaRL . Comparison of Prediction Models for Use of Medical Resources at Urban Auto-racing Events. Prehosp Disaster Med. 2014;29(6):1-6.

Unpredictable environmental conditions, crowd dynamics, and a variety of medical emergencies create logistical and clinical obstacles when planning emergency medical response coverage for mass-gathering events. In a collaborative endeavor between a university athletics program and an academic division of Emergency Medicine, a stadium emergency medical response system was created consisting of hospital-based healthcare providers and pre-hospital healthcare providers.

Provide descriptive statistics relevant to the nature and frequency of injury/illness, location of treatment within stadium confines, and resources used in the care of students, event staff, and spectators during collegiate football operations, to assist in future planning of mass-gathering events.

A continuously updated, quality assurance database of de-identified, aggregate statistics was utilized to analyze trends regarding aspects of medical operations.

During a 7-game home football season, there were a total of 399 patients encounters, including 1 cardiac arrest (0.25%), 12 “life-threatening” (3.01%), 121 urgent (30.33%), and 266 routine (66.67%). Total season attendance was 201,248 attendees (28,749/game and 19.83 patients encounters per 10,000 in attendance). Twenty-eight patients were transported (1.39 per 10,000), with eight resultant hospital admissions. Encounters varied by complaint, with skin (42%) comprising the largest number of encounters. Other categories included: (1) heat-related (23.5%); (2) allergic (15%); (3) neurologic (10.3%); (4) cardiopulmonary (3.5%); (5) gastrointestinal (3.6%); (6) musculoskeletal (5%); and (7) other (5%). Encounters increased noticeably when the heat index was greater than 80 °F– (29.4 vs. 10.5 per 10,000 attendees).

The collaborative effort by a multi-level provider model adequately covered presenting medical conditions. Consistent with previously literature, a strong correlation existed between heat index and number of patient encounters deemed urgent and routine. Interestingly, the number of “life-threatening” encounters did not appear to vary much with the heat index. Further studies of medical presentations and provider/resource utilization could provide for predictive modeling of future staffing and supply models.