The proliferation of unmanned aerial vehicle (UAV) technology has the potential to change the situational awareness of medical incident commanders’ (ICs’) scene assessment of mass gatherings. Mass gatherings occur frequently and the potential for injury at these events is considered higher than the general population. These events have generated mass-casualty incidents (MCIs) in the past. The aim of this study was to compare UAV technology to standard practice (SP) in scene assessment using paramedic students during a mass-gathering event (MGE).

This study was conducted in two phases. Phase One consisted of validation of the videos and accompanying data collection tool. Phase One was completed by 11 experienced paramedics from a provincial Emergency Medical Services (EMS) service. Phase Two was a randomized comparison with 47 paramedic students from the Holland College Paramedicine Program (Charlottetown, Prince Edward Island, Canada) of the two scene assessment systems. For Phase Two, the paramedic students were randomized into a UAV or a SP group. The data collection tool consisted of two board categories: primary importance with 20 variables and secondary importance with 25 variables. After a brief narrative, participants were either shown UAV footage or the ground footage depending on their study group. After completion of the videos, study participants completed the data collection tool.

The Phase One validation showed good consensus in answers to most questions (average 79%; range 55%-100%). For Phase Two, a Fisher’s exact test was used to compare each variable from the UAV and SP groups using a P value of .05. Phase Two demonstrated a significant difference between the SP and UAV groups in four of 20 primary variables. Additionally, significant differences were found for seven out of 25 secondary variables.

This study demonstrated the accurate, safe, and feasible use of a UAV as a tool for scene assessment by paramedic students at an MGE. No observed statistical difference was noted in a majority of both primary and secondary variables using a UAV for scene assessment versus SP.

Syndromic surveillance has been useful for routine surveillance on a variety of health outcomes and for informing situational awareness during public health emergencies. Following the landfall of Hurricane Maria in 2017, the New York City (NYC) Department of Health and Mental Hygiene (DOHMH) implemented an enhanced syndromic surveillance system to characterize related emergency department (ED) visits.

ED visits with any mention of specific key words (“Puerto,” “Rico,” “hurricane,” “Maria”) in the ED chief complaint or Puerto Rico patient home Zip Code were identified from the DOHMH syndromic surveillance system in the 8-week window leading up to and following landfall. Visit volume comparisons pre- and post-Hurricane Maria were performed using Fisher’s exact test.

Analyses identified an overall increase in NYC ED utilization relating to Puerto Rico following Hurricane Maria landfall. In particular, there was a small but significant increase in visits involving a medication refill or essential medical equipment. Visits for other outcomes, such as mental illness, also increased, but the differences were not statistically significant.

Gaining this situational awareness of medical service use was informative following Hurricane Maria, and, following any natural disaster, the same surveillance methods could be easily established to aid an effective emergency response.

The proliferation of unmanned aerial vehicles (UAV) has the potential to change the situational awareness of incident commanders allowing greater scene safety. The aim of this study was to compare UAV technology to standard practice (SP) in hazard identification during a simulated multi-vehicle motor collision (MVC) in terms of time to identification, accuracy and the order of hazard identification.

A prospective observational cohort study was conducted with 21 students randomized into UAV or SP group, based on a MVC with 7 hazards. The UAV group remained at the UAV ground station while the SP group approached the scene. After identifying hazards the time and order was recorded.

The mean time (SD, range) to identify the hazards were 3 minutes 41 seconds (1 minute 37 seconds, 1 minute 48 seconds-6 minutes 51 seconds) and 2 minutes 43 seconds (55 seconds, 1 minute 43 seconds-4 minutes 38 seconds) in UAV and SP groups corresponding to a mean difference of 58 seconds (P=0.11). A non-parametric permutation test showed a significant (P=0.04) difference in identification order.

Both groups had 100% accuracy in hazard identification with no statistical difference in time for hazard identification. A difference was found in the identification order of hazards. (Disaster Med Public Health Preparedness. 2018;12:631–634)

We examined the representativeness of the nonfederal hospital emergency department (ED) visit data in the National Syndromic Surveillance Program (NSSP).

We used the 2012 American Hospital Association Annual Survey Database, other databases, and information from state and local health departments participating in the NSSP about which hospitals submitted data to the NSSP in October 2014. We compared ED visits for hospitals submitting data with all ED visits in all 50 states and Washington, DC.

Approximately 60.4 million of 134.6 million ED visits nationwide (~45%) were reported to have been submitted to the NSSP. ED visits in 5 of 10 regions and the majority of the states were substantially underrepresented in the NSSP. The NSSP ED visits were similar to national ED visits in terms of many of the characteristics of hospitals and their service areas. However, visits in hospitals with the fewest annual ED visits, in rural trauma centers, and in hospitals serving populations with high percentages of Hispanics and Asians were underrepresented.

NSSP nonfederal hospital ED visit data were representative for many hospital characteristics and in some geographic areas but were not very representative nationally and in many locations. Representativeness could be improved by increasing participation in more states and among specific types of hospitals. (Disaster Med Public Health Preparedness. 2016;10:562–569)

Situational awareness (SA), or being aware of what is going on and what might happen next, is essential for the successful management of prehospital emergency care. However, far too little attention has been paid to the flow of information. Having the right information is important when formulating plans and actions.

The aim of this study was to analyze and describe the type of information that is meaningful for SA in the work of paramedic field supervisors, and to create an information profile for them in the context of prehospital emergency care.

Data were collected from January through March 2012 from semi-structured interviews with ten paramedic field supervisors representing four rescue departments in Finland. The interviews were based on three different types of real-life scenarios in the context of prehospital emergency care, and deductive content analysis was employed according to the information exchange meta-model. Data management and analysis were performed using Atlas.ti 7.

A paramedic field supervisor information interest profile was formulated. The most important information categories were Events, Means, Action Patterns, and Decisions. The profile showed that paramedic field supervisors had four roles – situation follower, analyzer, planner and decision maker – and they acted in all four roles at the same time in the planning and execution phases.

Paramedic field supervisors are multitasking persons, building SA by using the available data, combining it with extensive know-how from their working methods and competencies, and their tacit knowledge. The results can be used in developing work processes, training programs, and information systems.

Norri-SederholmT, KuusistoR, KurolaJ, SarantoK, PaakkonenH. A Paramedic Field Supervisor's Situational Awareness in Prehospital Emergency Care. Prehosp Disaster Med. 2014;29(2):1-9.

The 2005 Gulf Coast hurricane season was one of the most costly and deadly in US history. Hurricane Rita stressed hospitals and led to multiple, simultaneous evacuations. This study systematically identified community factors associated with patient movement out of seven hospitals evacuated during Hurricane Rita.

This study represents the second of two systematic, observational, and retrospective investigations of seven acute care hospitals that reported off-site evacuations due to Hurricane Rita. Participants from each hospital included decision makers that comprised the Incident Management Team (IMT). Investigators applied a standardized interview process designed to assess evacuation factors related to external situational awareness of community activities during facility evacuation due to hurricanes. The measured outcomes were responses to 95 questions within six sections of the survey instrument.

Investigators identified two factors that significantly impacted hospital IMT decision making: (1) incident characteristics affecting a facility's internal resources and challenges; and (2) incident characteristics affecting a facility's external evacuation activities. This article summarizes the latter and reports the following critical decision making points: (1) Emergency Operations Plans (EOP) were activated an average of 85 hours (3 days, 13 hours) prior to Hurricane Rita's landfall; (2) the decision to evacuate the hospital was made an average of 30 hours (1 day, 6 hours) from activation of the EOP; and (3) the implementation of the evacuation process took an average of 22 hours. Coordination of patient evacuations was most complicated by transportation deficits (the most significant of the 11 identified problem areas) and a lack of situational awareness of community response activities. All evacuation activities and subsequent evacuation times were negatively impacted by an overall lack of understanding on the part of hospital staff and the IMT regarding how to identify and coordinate with community resources.

Hospital evacuation requires coordinated processes and resources, including situational awareness that reflects the condition of the community as a result of the incident. Successful hospital evacuation decision making is influenced by community-wide situational awareness and transportation deficits. Planning with the community to create realistic EOPs that accurately reflect available resources and protocols is critical to informing hospital decision making during a crisis. Knowledge of these factors could improve decision making and evacuation practices, potentially reducing evacuation times in future hurricanes.

DowneyEL, AndressK, SchultzCH. External Factors Impacting Hospital Evacuations Caused by Hurricane Rita: The Role of Situational Awareness. Prehosp Disaster Med. 2013;28(3):1-8.