Driving the ambulance: an essential component of emergency medical services: an integrative review

Lights, Sirens, and Load: Anticipatory emergency medical treatment planning causes cognitive load during emergency response driving among paramedicine students

Paramedics face various unconventional and secondary task demands while driving ambulances, leading to significant cognitive load, especially during lights-and-sirens responses. Previous research suggests that high cognitive load negatively affects driving performance, increasing the risk of accidents, particularly for inexperienced drivers. The current study investigated the impact of anticipatory treatment planning on cognitive load during emergency driving, as assessed through the use of a driving simulator. We recruited 28 non-paramedic participants to complete a simulated baseline drive with no task and a cognitive load manipulation using the 1-back task. We also recruited 18 paramedicine students who completed a drive while considering two cases they were travelling to: cardiac arrest and infant seizure, representing varying difficulty in required treatment. The results indicated that both cases imposed considerable cognitive load, as indicated by NASA Task Load Index responses, comparable to the 1-back task and significantly higher than driving with no load. These findings suggest that contemplating cases and treatment plans may impact the safety of novice paramedics driving ambulances for emergency response. Further research should explore the influence of experience and the presence of a second individual in the vehicle to generalise to broader emergency response driving contexts.

Prehospital emergency care family satisfaction scale for care provided by emergency medical technicians: Scale development and validation

RATIONALE

To date, family satisfaction with emergency medical technicians (EMTs) has only been reported through narrative statements in subjective evaluations. Although a quantitative assessment of healthcare professional satisfaction is desirable, no specific measures have been devised to assess family satisfaction with the healthcare and care provided by EMTs.

AIMS AND OBJECTIVES

This study aimed to develop and validate an EMT care family satisfaction scale to measure patient satisfaction with prehospital emergency care.

METHODS

The study population comprised 216 family members (N = 216) of patients who used ambulances between November 2020 and May 2021 in a single region in Japan. Questionnaires were distributed to the participants who provided informed consent. An exploratory factor analysis of construct validity was performed to validate the Family Satisfaction Scale. The Cronbach's alpha was used to validate the internal consistency reliability of the scale.

RESULTS

The exploratory factor analysis results revealed a four-factor structure: 'explanation and communication,' 'physical treatment,' 'psychological support,' and 'environment in the ambulance.' The Cronbach's range (0.80-0.93) for the total score for each of these four factors and the overall total score confirmed favorable internal reliability of this study.

CONCLUSIONS

The family satisfaction scale developed in this study was constructed and validated to highlight the role of EMTs and needs of the families in the prehospital care settings. Moreover, this scale can be applied in the evaluation and consideration of interventions to improve family satisfaction with EMTs.

Dynamic ambulance relocation: a scoping review

OBJECTIVES

Dynamic ambulance relocation means that the operators at a dispatch centre place an ambulance in a temporary location, with the goal of optimising coverage and response times in future medical emergencies. This study aimed to scope the current research on dynamic ambulance relocation.

DESIGN

A scoping review was conducted using a structured search in PubMed, Scopus and Web of Science. In total, 21 papers were included.

RESULTS

Most papers described research with experimental designs involving the use of mathematical models to calculate the optimal use and temporary relocations of ambulances. The models relied on several variables, including distances, locations of hospitals, demographic-geological data, estimation of new emergencies, emergency medical services (EMSs) working hours and other data. Some studies used historic ambulance dispatching data to develop models. Only one study reported a prospective, real-time evaluation of the models and the development of technical systems. No study reported on either positive or negative patient outcomes or real-life chain effects from the dynamic relocation of ambulances.

CONCLUSIONS

Current knowledge on dynamic relocation of ambulances is dominated by mathematical and technical support data that have calculated optimal locations of ambulance services based on response times and not patient outcomes. Conversely, knowledge of how patient outcomes and the working environment are affected by dynamic ambulance dispatching is lacking. This review has highlighted several gaps in the scientific coverage of the topic. The primary concern is the lack of studies reporting on patient outcomes, and the limited knowledge regarding several key factors, including the optimal use of ambulances in rural areas, turnaround times, domino effects and aspects of working environment for EMS personnel. Therefore, addressing these knowledge gaps is important in future studies.

Community-based transport system in Shinyanga, Tanzania: A local innovation averting delays to access health care for maternal emergencies

In achieving the sustainable development goal 3.1, Tanzania needs substantial investment to address the three delays which responsible for most of maternal deaths. To this end, the government of Tanzania piloted a community-based emergency transport intervention to address the second delay through m-mama program. This study examined secondary data to determine the cost-effectiveness of this intervention in comparison to the standard ambulance system alone. The m-mama program was implemented in six councils of Shinyanga region. The m-mama program data analyzed included costs of referral services using the Emergency Transportation System (EmTS) compared with the standard ambulance system. Analysis was conducted using Microsoft Excel, whose data was fed into a TreeAge Pro Healthcare 2022 model. The cost and effectiveness data were discounted at 5% to make a fair comparison between the two systems. During m-mama program implementation a total of 989 referrals were completed. Of them, 30.1% used the standard referral system using ambulance, while 69.9% used the EmTS. The Emergency transport system costed USD 170.4 per a completed referral compared to USD 472 per one complete referral using ambulance system alone. The introduction of m-mama emergency transportation system is more cost effective compared to standard ambulance system alone in the context of Shinyanga region. Scaling up of similar intervention to other regions with similar context and burden of maternal mortality may save cost of otherwise normal emergency ambulance system. Through lessons learned while scaling up, the intervention may be improved and tailored to local challenges and further improve its effectiveness.

A Retrospective, Single-Agency Analysis of Ambulance Crashes during a 3-Year Period: Association with EMS Driver Characteristics and a Telematics-Measured Safe Driving Score

BACKGROUND

Driver demographics and aggressive driving behavior are established risk factors for traffic accidents, yet their role in ambulance crashes remains poorly studied. We reviewed all ambulance crashes that occurred in our emergency medical services (EMS) agency during a 3-year period, and examined incidence rates (IR) by driver characteristics and telematics-measured driver behavior.

METHODS

This retrospective study was conducted in a U.S. EMS agency that operates 75 Type III ambulances and requires personnel to document all ambulance collisions, regardless of severity. Crashes reported between September 2017 and August 2020 were reviewed, and established criteria were used to classify injury and vehicle damage severity. Serious crashes were defined as events with any injury and/or functional or disabling damage. A vehicle telematics system installed fleet-wide in 2017 continuously captures driver-specific data, including miles driven and indicators related to speeding, harsh cornering and braking, and seatbelt use. A composite score characterizes compliance with safe driving behaviors (1 = low compliance to 5 = high compliance). Crash IR per 100,000 miles, IR ratios (IRR), and Poisson regression were used in analysis. Driver sex, age, agency tenure, miles driven, and safe driving score were examined.

RESULTS

Clinicians reported 214 crashes and the IR of any crash and serious crash were 2.1 and 0.63 per 100,000 miles, respectively. Injuries occurred in 8% of crashes and were all of low acuity. About one third of crashes produced functional (21%) or disabling (8%) vehicle damage, and the ambulance required towing in 10%. In a multivariate model, female sex (IRR = 1.50, 95%CI = 1.13-1.97), age 18-24 (IRR = 1.67, 95%CI = 1.06-2.66), and being in the lowest quartile of safe driving score (IRR = 1.51, 95%CI = 1.14-2.02) were EMS driver factors independently associated with an increased risk of any collision.

CONCLUSION

Most ambulance crashes are minor events, but the proportion that result in injury and/or functional or disabling vehicle damage may be as high as one-third. Poor driver compliance with objectively measured safe driving behaviors may increase risk for collisions independent of driver sex and age. The EMS industry would benefit from additional studies that examine the full spectrum of ambulance crashes and expand understanding of EMS driver-related risk factors.

Urban-sub-urban-rural variation in the supply and demand of emergency medical services

Background

Emergency medical services (EMSs) are a critical component of health systems, often serving as the first point of contact for patients. Understanding EMS supply and demand is necessary to meet growing demand and improve service quality. Nevertheless, it remains unclear whether the EMS supply matches the demand after the 2016 healthcare reform in China. Our objective was to comprehensively investigate EMS supply-demand matching, particularly among urban vs. sub-urban vs. rural areas.

Methods

Data were extracted from the Tianjin Medical Priority Dispatch System (2017-2021). From supply and demand perspectives, EMS resources and patient characteristics were analyzed. First, we performed a descriptive analysis of characteristics, used Moran's I to explore the spatial layout, and used the Gini coefficient to evaluate the equity of EMS supply and demand. Second, we analyzed urban-sub-urban-rural variation in the characteristics of EMS supply and demand by using the chi-square test. Finally, we examined the association between the EMS health resource density index and the number of patients by using the Spearman correlation and divided supply-demand matching types into four types.

Results

In 2021, the numbers of medical emergency stations and ambulances were 1.602 and 3.270 per 100,000 population in Tianjin, respectively. There were gradients in the health resource density index of the number of emergency stations (0.260 vs. 0.059 vs. 0.036; P = 0.000) in urban, sub-urban, and rural areas. There was no spatial autocorrelation among medical emergency stations, of which the G values by population, geographical distribution, and the health resource density index were 0.132, 0.649, and 0.473, respectively. EMS demand was the highest in urban areas, followed by sub-urban and rural areas (24.671 vs. 15.081 vs. 3.210 per 1,000 population and per year; P = 0.000). The EMS supply met the demand in most districts (r = 0.701, P = 0.003). The high supply-high demand types with stationary demand trends were distributed in urban areas; the low supply-high demand types with significant demand growth trends were distributed in sub-urban areas; and the low supply-low demand types with the highest speed of demand growth were distributed in rural areas.

Conclusion

EMS supply quantity and quality were promoted, and the supply met the demand after the 2016 healthcare reform in Tianjin. There was urban-sub-urban-rural variation in EMS supply and demand patterns.

Driving Speeds in Urgent and Non-Urgent Ambulance Missions during Normal and Reduced Winter Speed Limit Periods—A Descriptive Study

Objective: Most traffic research on emergency medical services (EMS) focuses on investigating the time saved with emergency response driving. Evidence regarding driving speed during non-urgent ambulance missions is lacking. In contrast, this descriptive study compared registered driving speeds to the road speed limit in urgent A-missions and non-urgent D-missions. Specifically, the study examined driving speeds during normal speed limits, periods of reduced winter speed limits, and speeding during non-urgent D-missions. Methods: Urgent A-missions and non-urgent D-missions were included. Registered ambulance locations and speed data from Pirkanmaa Hospital District, Finland between 1 January 2018 and 31 December 2018 were used. Ambulance locations were linked to OpenStreetMap digital road network data. The registered driving speed distribution was reported as quartiles by the effective road speed limit. Furthermore, the results during the normal speed limit and reduced winter speed limit periods were reported separately. Driving speeds in non-urgent missions were compared with current Finnish traffic violation legislation. Results: As expected, the urgent A-missions exceeded the speed limits during both the normal speed limit and reduced winter speed limit periods. On the smallest streets with speed limits of 30 km/h, the driving speeds in urgent missions were lower than the speed limit. The driving speeds in non-urgent D-missions were broadly similar throughout the whole year on high-speed roads, and mostly on lower speed limit roads. However, within the 30 km/h speed limits, the mean speed in non-urgent missions appeared to increase during the winter. One-fifth of the registered non-urgent D-missions were speeding. Conclusions: Speeding is common in urgent A-missions and non-urgent D-missions throughout the year. Stricter guidelines for EMS are needed to increase driving safety.