Urban traffic accidents in Isfahan city: a study of prehospital response time intervals

Abstract

Introduction

Traffic accidents are a major public health concern worldwide, resulting in significant injuries, fatalities, and economic costs. In urban zones, traffic accident dynamics can vary significantly due to population density, infrastructure, and emergency response capabilities. The present study was conducted to determine the time intervals of prehospital emergencies in traffic accidents by separating the 15 zones of Isfahan city, Iran.

Methods

This descriptive study was conducted in 2023. The sampling approach involved a census that included all prehospital emergency missions that occurred in the second half of 2022. A total of 7613 missions were examined. To collect the data, a checklist covering demographic characteristics and mission-specific features was utilized. The information was recorded in an Excel spreadsheet and described via the prehospital emergency information system.

Results

After analyzing 7,613 urban missions, it was determined that Zone 12 had the highest number of prehospital emergency missions in all three time periods: morning, afternoon, and evening. Therefore, all the times (reaction time, response time, scene time, transfer time, and hospitalization time) were in accordance with prehospital emergency time standards in Iran.

Conclusion

On the basis of the findings of this study, it is crucial to identify zones with greater population movement, highways, or high traffic volume and establish bases in suitable locations whenever feasible. Additionally, in zones with a greater number of missions, there should be an appropriate number of ambulances in proportion to the mission volume.

Introduction

According to studies, road traffic crashes (RTCs) are the eighth leading cause of mortality globally [1,2,3,4]. Every year, more than one million deaths due to RTCs occur worldwide [1, 4, 5]. Globally, road traffic accidents (RTAs) are the most common cause of injury and mortality, especially in developing countries and individuals aged 5–29 years [1, 2]. According to the current trend, road traffic injuries (RTIs), known as “time-dependent diseases,” are a significant global public health concern and are predicted to become the seventh leading cause of mortality worldwide by 2030 [1, 6]. In response to the Global Status Report on Road Safety 2010, which highlighted alarming statistics, the World Health Organization (WHO) initiated the “Decade of Action for Road Safety 2011 − 2020” [7]. The objective was to reduce road traffic fatalities by 50%. However, this goal was not achieved, leading to the launch of the “Decade of Action for Road Traffic Safety 2021 − 2030” with the same aim [1, 8, 9].

To address road safety comprehensively, the WHO identifies five crucial pillars: road safety management, road infrastructure, safe vehicles, user behavior, and postcrash care [10, 11]. The response time following a crash, defined as the duration between receiving information about the incident and arriving at the scene, plays a critical role in facilitating survival [12].

Research shows that several factors affect emergency response times, including [13,14,15,16]:

Geographical location: Urban zones often experience faster response times because of their proximity to emergency services, but traffic congestion can negate this advantage. Time of day: Response times can vary significantly depending on traffic patterns, with peak hours often leading to delays. Incident type: The nature of the traffic incident (e.g., severity, number of vehicles involved) can also affect the response time.

Numerous sociodemographic factors have been recognized as significant contributors to the effectiveness of prehospital care. These include male sex, younger age, engagement in risky behaviors, substance use (both alcohol and drugs), insufficient use of personal protective equipment, disregard for traffic laws, and delays in the provision of emergency medical services to victims [15, 17]. Other factors that influence the effectiveness of prehospital care include accurate information systems, access, ambulance equipment, staff skills, mean ambulance response time, dispatch networks, communications, appropriate transport of injured persons, and the type of care provided. Inadequate collaboration between prehospital and emergency departments has also been cited as a contributing factor to the high death rate in traffic accidents in many developing countries, as identified by various studies [18, 19].

Prehospital emergency care is critical for improving patient outcomes after traffic accidents [13]. Timely delivery of patients, ensuring continuity of care and strengthening effective cooperation between prehospital and hospital emergency services can have a significant impact on saving people’s lives [20].

The early arrival of emergency medical care teams ensures the stabilization of individuals with life-threatening injuries, enables timely triage, and facilitates hospital admission. Conversely, delays in response time increase the risk of mortality [21].

Reducing the time gap between traffic accidents and the provision of professional emergency care is a key global objective for road safety. This is because implementing effective medical interventions within the “golden hour” significantly improves patient outcomes [22, 23].

This objective necessitates the development of emergency medical services (EMSs), which are acknowledged as the backbone of the healthcare system [24]. EMSs play a vital role in the prompt transportation of patients to medical facilities and ensure that they receive appropriate treatment at the right location [14]. In this system, seconds and minutes indicate the difference between life and death [25]. Research suggests that enhancing the quality of prehospital emergency care can substantially reduce health-related complications and increase patient survival rates [14].

Response time is a fundamental indicator of emergency medical services, with researchers employing descriptive statistics to assess this parameter. Europe and the USA have led the way in publishing studies that present this information [26]. Some articles utilize stochastic and mathematical methods to propose models that simulate scenarios of response time reduction and suggest such proposals to the local EMS [26,27,28,29,30].

The associations between prehospital time and patient outcomes have predominantly been examined previously. A study conducted by Keykha et al. [15] in 2023 in Zahedan, Iran, revealed that the mortality rate of patients in the first 24 h was influenced by the duration of the patient’s transfer from the accident scene to the hospital. In the 2023 study by Ebrahimpour et al. [31] in Mashhad, Iran, the results revealed that, owing to the lack of manpower and ambulance equipment, the response time was longer than the standard time, and as a result, the effectiveness of the missions was reduced. In another study, Wang et al. [14] demonstrated that prompt medical intervention markedly lowered both mortality and morbidity rates in 2020. Research conducted by Byrne et al. [32] in the United States in 2019 revealed a correlation between prolonged response times and increased mortality rates. A study by Kumar et al. in India in 2017 revealed that shorter prehospital times were correlated with improved patient outcomes [33]. Furthermore, Sanchez et al. [34] in 2010 indicated that a mere 10-minute decrease in response time could diminish the likelihood of death by one-sixth.

Importantly, urban environments present unique challenges for EMSs. High population density can lead to increased traffic congestion and complicated timely access to accident sites. Furthermore, urban infrastructure, including road design and the availability of emergency lanes, plays a vital role in determining response times [14, 30].

In the context of Isfahan, a city characterized by its historical importance and urban complexity, understanding the dynamics of traffic accidents and emergency response is very important. Few studies have focused specifically on Isfahan, and recent studies in Iran have shown that the number of urban traffic accidents is increasing, highlighting the need to improve emergency response strategies [35]. Factors such as inadequate road infrastructure, lack of public awareness, and insufficient emergency services have been identified as barriers to effective response [19, 36].

Isfahan, Iran’s third most populous city, faces several significant challenges and high population density, and rapid urban expansion outpaces the development of essential infrastructure, leading to increased traffic volumes and congestion, especially during peak hours and around industrial zones. This congestion hampers emergency vehicle navigation and delays prehospital emergency care. Additionally, infrastructure limitations such as poorly designed roads and a lack of emergency lanes further exacerbate response times.

Emergency services are unevenly distributed, with some high-risk areas suffering from delayed responses due to inadequate EMS bases and resource allocation. Sociodemographic factors, such as high-risk behaviors and limited public awareness about road safety, increase accident rates and demand emergency services. Finally, effective coordination between EMSs and hospitals is crucial but often hindered by gaps in response protocols. Addressing these challenges is vital for improving emergency care and patient outcomes in Isfahan.

The motivation for this study stems from the critical public health concern posed by RTAs, especially in urban areas such as Isfahan, where dense populations and complex traffic patterns exacerbate the issue. The increasing number of RTAs in such cities highlights the urgent need to improve emergency response strategies. Efficient prehospital emergency care can significantly reduce the adverse outcomes associated with RTAs, making it vital to understand and optimize response times. This study aims to analyze prehospital emergency response time intervals for traffic accidents across 15 zones in Isfahan city, Iran. By identifying variations in response times and their contributing factors, this study seeks to provide actionable insights for enhancing EMSs in urban settings.

In the context of Isfahan, a city characterized by its historical importance and urban complexity, understanding the dynamics of traffic accidents and emergency response is very important. Few studies have focused specifically on Isfahan, and recent studies in Iran have shown that the number of urban traffic accidents is increasing, highlighting the need to improve emergency response strategies. Factors such as inadequate road infrastructure, lack of public awareness, and insufficient emergency services have been identified as barriers to effective response. The present study was carried out to determine the intervals in prehospital emergency traffic accidents categorized by urban areas in the city of Isfahan, Iran.

Methods

Study design

This descriptive, cross-sectional, retrospective study was conducted in 2023 in Isfahan city, Iran. Isfahan is the sixth most populous province, and after Tehran and Mashhad, Isfahan is Iran’s third most populous city, the 165th most populous city worldwide, and the ninth most populous city in Western Asia. Isfahan is also the 14th most populated metropolis in the Middle East [37]. In this sense, this city is in a sensitive and important position in the urban hierarchy of Iran. The metropolis zone population of Esfahan in 2023 was 2,258,000, a 1.76% increase from 2022 [38]. The urban zone of Isfahan, according to Statistics for 2022, Isfahan Municipality Statistics and Analysis Department, has 15 urban zones. This metropolis is outside the city limits from the west to Khomeini Shahr and Najaf Abad, from the south to Sofe Mountain and Sepahanshahr, from the north to Shahin Shahr, and ends in a desert zone to the east [37].

Study population

The research population included all the calls made to prehospital emergency departments in Isfahan city. The sampling method included the census of all prehospital emergency missions conducted during the second half of 2022.

The inclusion criterion was traffic accidents leading to ambulance dispatch on the streets of Isfahan city, so all missions in which the patient was taken to the hospital and hospitalized were included in the study. The exclusion criteria focused on traffic accidents requiring ambulance dispatch, excluding nontraffic missions (e.g., falls, industrial accidents) and traffic accidents not necessitating an ambulance, to ensure relevance to road traffic incidents.

Ethical considerations

The study was conducted in accordance with the Declaration of Helsinki in its current version (World Medical Association [WMA], 2013). The ethics committee of Isfahan University of Medical Sciences approved this study (approval number: IR.MUI.MED.REC.1399.032). Through the informed oral consent of patients or their first-degree relatives, data were collected and presented anonymously in this project.

Data collection

Data collection was conducted via ASAYAR software, which is approved by the Ministry of Health of Iran for the electronic registration of EMS missions throughout Iran. This software was employed to gather data on the demographic characteristics and specific features of each mission. The dataset included a range of demographic information, such as age, gender, and type of vehicle involved, as well as key factors related to high-risk road networks, the number of missions conducted by each base, the outcome of each mission, and the location at which each mission was deployed.

ASAYAR software consists of two main components. The first component contains information about the patient, the rationale behind the call, the diagnosis rendered by the attending technicians, and the location of the incident. The second component includes prehospital emergency time indicators such as delay time, response time, time spent at the scene, total execution time, transportation time, and departure time.

Ultimately, the data were collected with the assistance of ASAYAR software, which analyzed a total of 7613 missions. According to the operational procedures governing prehospital emergencies in Iran, the standard response time index is 14 min in suburban areas, 12 min in large cities, and 8 min in other cities. Additionally, the standard stage time is less than 20 min.

Quality control

The data underwent rigorous quality control, including initial reviews for completeness and accuracy, with any records containing missing or implausible values flagged and crosschecked with original mission logs. Incomplete records were excluded. The data were entered into an Excel spreadsheet and validated against the prehospital emergency information system, and a random 10% of the entries were cross-verified by a second researcher. Quality control checks also included verifying time stamps and geographical coordinates to ensure accurate recording of response times and mission locations. The study period covered the second half of 2022 to provide an overview of emergency response times across different seasons and capture temporal variations in traffic patterns.

Data analysis

Statistical analysis was conducted via SPSS software (version 24) at a significance level of 0.05. Descriptive statistics, including the means ± standard deviations for continuous variables and frequency distributions for categorical variables, were used. Inferential statistics such as chi-square tests and t tests/ANOVAs were employed to examine associations and compare group means, whereas logistic regression analysis was used to assess the impact of various factors on dissatisfaction rates. Multiple regression and survival analyses were also utilized to identify predictors and analyze time-to-event data, respectively. Data visualization tools and geospatial analysis further enhanced the interpretation of the results.

Results

As shown in Table 1, the current study analyzed a total of 7,613 urban missions, with 77.2% involving male victims. The victims had a mean age of 31.17 ± 9.33 years.

Table 1 Demographic characteristics of different urban zones of Isfahan

Figure 1 illustrates the geographical position of Isfahan Province and Isfahan city within Iran. Additionally, for a more comprehensive understanding, Fig. 2 depicts the locations of the 15 zones of Isfahan city and the prehospital emergency stations within these zones. Notably, the existing map was created by the most recent amendments in September 2024 via GIS software.

Fig. 1

Locations of Isfahan Province and Isfahan city in Iran

Fig. 2

Locations of the 15 zones of Isfahan city and the locations of the EMS stations in these zones. Air Ambulance (H: Helicopter). *Prehospital Road Stations

Chart 1

Distribution of accident occurrence in urban zones

Chart 1 illustrates the distribution of accidents across different urban zones in Isfahan. During the morning hours (6 a.m. to 1 p.m.), the highest number of prehospital emergency missions occurred in Zones 12, 8, and 5, respectively. In the afternoon (2 p.m. to 7 p.m.), Zones 12, 3, and 10 had the highest number of prehospital emergency missions. At night (8 p.m. to 6 a.m.), Zones 10 (12, 5, and 3), and 6 recorded the highest number of prehospital emergency missions

Table 2 presents the mean intervals for prehospital emergency traffic incidents, categorized by zone, and compares them with the standard time duration. Among the 739 missions (6.9%), there were instances of dissatisfaction with the transfer, with the highest dissatisfaction rates observed in Zones 10, 3, and 14.

Reaction time

Zone 12 presented a mean response time that exceeded the standard time limit, whereas Zones 11, 2, and 8 presented the shortest response times.

Scene time

Zone 2 had a mean response time that was close to the standard time limit and higher than that of all other areas. Zones 13, 14, and 4 had the shortest response times.

The mean scene time across all areas fell within the standard time limit. Zones 14, 1, and 13 had the shortest scene times, whereas Zones 6, 2, and 7 had the longest scene times. The mean transfer time was approximately 56.10 ± 7.96 min. Zones 4, 8, and 10 had the shortest transfer times, whereas Zones 11, 13, and 1 had the longest transfer times. For missions related to Zones 13 and 1, the mean hospital stay duration exceeded the standard time limit. Additionally, missions associated with Zones 2, 15, 7, and 4 had the lowest mean hospital stay duration.

Table 2 Mean ± SD of time intervals in prehospital emergency traffic incidents

Table 3 shows the mean duration of hospital stay, along with the placement of hospitals in each zone. Hospital B had the longest hospital stay duration, whereas Hospital F had the shortest duration. Three ambulance codes, namely, 2033 (Zone 5), 2153 (Zone 8), and 2383 (Zone 2), demonstrated the shortest reaction times. On the other hand, four ambulance codes, namely, 2203 (Zone 15), 2393 (Zone 3), 2323 (Zone 1), and 2423 (Zone 3), presented the longest reaction times.

Table 3 Mean hospital stay time of ambulances by hospital

Additionally, Chart 2 shows the mean duration of ambulance stoppages at each hospital, with a ranking based on percentage. Hospital B, with a rate of 23%, presented the longest mean ambulance wait time, whereas Hospital F, with a rate of 9%, presented the shortest.

Chart 2

Percentage and mean hospital stay time of ambulances by hospital

Discussion

As mentioned in the introduction, RTIs are a major global public health concern [1,2,3,4,5,6] and are considered a major public health challenge in Isfahan, and there is a need for efficient prehospital emergency responses to reduce adverse outcomes. This discussion explores important aspects of prehospital response time intervals, drawing insights from various studies.

The prehospital response time is a vital factor in the management of traffic accident victims. It includes the time from when an emergency call is received to the arrival of the EMSs at the scene, the on-scene time, and the transportation time to a medical facility [13,14,15,16, 39, 40]. Studies have consistently shown that shorter response times are associated with better outcomes for trauma patients, emphasizing the need for timely intervention [20,21,22]. As in many metropolises, in the metropolis of Isfahan, several factors affect the prehospital response time. The geographical layout of the city plays a significant role, with larger zones and those with higher population densities experiencing more emergency missions [41,42,43,44]. The presence of industrial zones and major highways further exacerbates the frequency of traffic accidents, leading to increased demand for EMSs.

Since accidents are the most common reason for prehospital emergency calls, this study focused on missions related to traffic accidents. A review and analysis of 7,613 urban missions revealed that most of the injured were men (5846 (77.2%)). The mean age of the injured patients was 33.09 ± 17.31 years. During the morning hours (6 a.m. to 1 p.m.), the highest number of prehospital emergency missions occurred in Zones 12, 8, and 5, respectively. Most accidents were related to Zones 10, 3, and 8. The highest dissatisfaction rates were observed in Zones 10, 3, and 14.

Various studies have been conducted on standard time intervals and comparisons of prehospital emergency missions with these standards. According to Sabbagh (2023) [45], after 17,860 prehospital emergency missions in Iran were analyzed, accidents were found to be the most common reason for emergency calls. The indicators of prehospital emergency response time also increased following the COVID-19 pandemic. In the study of Chegini et al. [24], which was conducted in Qazvin, Iran, in 2024, accidents (29.41%) were the most common reason for contact with the prehospital emergency room. Similar results were obtained by Stirparo (2022) [46] in Italy.

In Mashhad, Jafari (2021) [47] examined 21,142 missions and reported that the mean age of the injured was 15.9 ± 29.8 years, with a mean response time of 9 min, 1 s ± 2 min and 46 s. However, these findings did not align with the findings of the current study, which reported a higher mean age and longer response time. Notably, the present study included only missions related to traffic accidents, whereas all missions were conducted in Mashhad.

Zone 12 had the highest frequency of prehospital emergency calls during the morning, afternoon and evening hours, raising concerns about the efficiency and effectiveness of emergency management in the zone. This pattern can be explained by a number of factors. Compared with the other zones, Zone 12 in northern Isfahan city encompasses a larger geographical zone. This zone has a relatively large population and urban traffic, which naturally results in a relatively high frequency of emergency calls at different times of the day. The size of the zone means that the emergency services have to cover a wider zone, increasing the likelihood of incidents requiring immediate attention. This geographical factor alone contributes significantly to the overall volume of emergency calls, as a larger zone inherently provides more opportunities for emergencies to occur. Additionally, the high population density of the zone plays an important role in increasing the demand for emergency services. The concentration of people not only increases the frequency of incidents but also places an additional burden on emergency services, which must be prepared to respond to a greater volume of calls on time. In addition to the aforementioned demographic factors, the presence of a sizable industrial zone within Zone 12 serves to augment the demand for emergency services. The confluence of a bustling industrial zone and a densely populated residential zone gives rise to a distinctive setting where the demand for emergency services is persistently high. Furthermore, the geographical location of Zone 12 presents additional challenges for emergency services. Many patients in this Zone require transfer to medical facilities located outside the metropolis of Isfahan, which complicates the logistics of emergency response. This need for transfer to medical facilities located outside of the city can further extend the time it takes for patients to receive critical care, particularly in urgent situations. The time of day also influences the frequency of ambulance calls in Zone 12. During the morning hours, for example, the rush of commuters and the start of industrial operations can lead to a spike in accidents and health-related incidents. Similarly, during the afternoon and evening hours, leisure activities and social gatherings increase, which can also lead to emergencies. This peak in activity is associated with an extended interval between the moment of an emergency call and the actual dispatch of emergency services. Such delays can be detrimental, as they may impede timely medical intervention and potentially worsen patient outcomes.

In a study conducted by Sariyer et al. [48], in 2017, the aim was to investigate the demand for EMS services on the basis of time and location trends in the city of Izmir, Türkiye. The demand for 112 services in Izmir during the first six months of 2013 was evaluated. The main variables used to describe the data are time, place and status of the calls (the differentiation between emergency and nonemergency calls was made by the dispatcher physician according to predefined protocols). The analyses revealed that the demand for ambulance services varied at different times of the day and on different days of the week. For the night period, demand was greater on weekends than on weekdays, whereas for daytime hours, demand was greater during the week. For weekdays, a statistically significant relationship was observed between the call distributions of the morning and evening periods. The percentage of demand also varied according to location. Among the 30 locations, the five most frequent destinations for ambulances, which are also correlated with high population density, accounted for 55.66% of the total. This finding was in line with our results.

The ongoing delays in response times underscore the urgent need for enhanced response strategies tailored to the unique challenges faced by Zone 12. The implementation of more efficient dispatch protocols, increasing the availability of emergency personnel, and improving traffic management during peak hours are potential strategies that could help address the elevated volume of emergencies in this zone. By prioritizing these improvements, emergency services can better meet the needs of the community and ensure that residents receive prompt and effective care when they need it most.

Zone 5, similar to Zone 12 but to southern Isfahan city, plays a central role as a transit corridor, facilitating communication with a wide range of industrial towns, including Shahreza and Mobarakeh. It is anticipated that this role as a transit route will increase traffic accidents, particularly during the early morning hours. The increase in incidents during this interval can be largely attributed to the influx of commuter traffic, as workers and individuals traveling to their places of employment in industrial areas navigate through this zone. Furthermore, the traffic dynamics in Zone 5 are further complicated by the return of the workforce later in the day. As these individuals return to the zone in the evening, the volume of vehicles on the road increases significantly. The aforementioned surge in traffic during the evening hours has been identified as a contributing factor to the higher incidence of accidents, as evidenced by the research findings. The confluence of early morning commuter traffic and the evening return of workers has resulted in a pattern of heightened risk for accidents, thereby underscoring the necessity for the implementation of enhanced safety measures and traffic management strategies in Zone 5 to mitigate these risks.

According to our results, most accidents were related to Zones 10, 3, and 8. Zone 8, with a population of 241,652, is the most populous area among the fifteen zones of Isfahan. In terms of size, it is the third largest zone, preceded only by Zones 12 and 10. As previously stated, the elevated population density of the area is a significant contributing factor to the increased demand for emergency services. The concentration of people in a single area not only increases the number of incidents but also exerts greater pressure on emergency response teams to respond to a high volume of calls in a timely manner. Additionally, Zone 8 is traversed by two major highways, which experience a considerable volume of traffic during the early morning hours (6:00 a.m. to 1:00 p.m.). The interplay of these elements—high population density, heavy traffic, and the frequency of incidents—result in an increased number of emergency missions within the city, necessitating a well-coordinated and efficient response system. However, despite the challenges posed by the high demand for emergency services, Zone 8 has been observed to exhibit the shortest transfer times for injured individuals to hospitals. This efficiency can be attributed to the adequacy of emergency stations and ambulances in relation to the population. The strategic placement of these resources allows for quicker response times, ensuring that individuals in need of urgent medical attention receive care as swiftly as possible. This aspect of emergency management is crucial, as timely medical intervention can significantly impact outcomes for those involved in accidents or emergencies. In contrast to Zone 8, the greatest number of missions was recorded in Zones 3 and 10 during both the afternoon and evening periods. Zone 3 is a particularly active area, with a concentration of medical facilities, entertainment venues, and shopping centers. These establishments attract a considerable number of visitors, particularly in the period following the conclusion of the working day. As people leave their places of work, they often seek medical appointments, entertainment options, or shopping opportunities. This results in a surge in traffic, which in turn gives rise to a considerable volume of missions during these peak times.

Similarly, Zone 10 is characterized by a high population density and a vast geographical area, making it a crucial area for transportation services. The area is intersected by two major highways, which facilitate the movement of people and goods. This infrastructure not only supports the daily commute but also contributes to the elevated number of missions observed during the noon and night hours. The combination of a large population and the accessibility provided by highways creates an environment where transportation needs are heightened, particularly during these times. In summary, the observed traffic patterns and mission volumes in Zones 3, 8, and 10 can be attributed to the distinctive features of each area. The early morning traffic flow in Zone 8, the array of attractions in Zone 3 that draw visitors after work, and the high population density and significant highways in Zone 10 all play pivotal roles in shaping the demand for transportation services throughout the day. It is therefore imperative to gain an understanding of these areas’ dynamics to effectively manage and respond to the transportation needs of the community.

The areas displaying the most pronounced levels of discontent about transfers were Zones 10 and 14 in the eastern area, along with Zone 3 in the central area. High dissatisfaction rates in these zones were attributed to factors such as proximity to medical facilities leading to high expectations for quick transfers, traffic congestion causing delays, and perceived lower quality of care due to insufficient communication. Additionally, sociodemographic factors, high-risk behaviors, and longer response and transfer times contributed to dissatisfaction.

To address these issues, recommendations include improving traffic management, enhancing EMS communication, increasing resource allocation, engaging with communities, and continuously monitoring and evaluating EMS performance. These measures aim to reduce response times and improve the overall efficiency and satisfaction of emergency medical services in high-dissatisfaction zones.

The results of our study overlapped to some extent with the results of the study by Colla et al. [49] in Brazil, which investigated the response time of an ambulance in a Brazilian emergency medical service. According to the results of our study, the response time was related to factors such as the time of day, sex (men), location of the incident, dispatch time, population density and number of emergency stations. The study by Colla et al. was conducted in 2023 and was based on data from 2019. The results revealed that dispatch time, travel time, time of day, service to injured men and critical cases affected the ambulance response time. However, there was a notable disparity in the ambulance response times reported in our study compared with those documented by Colla et al. In their analysis of 12,050 ambulance dispatches, the Colla study revealed a mean response time of 14 min and 25 s. In contrast, our findings indicated a mean response time of 7.19 ± 4.75 min. This variation in response times may be attributed to several factors, particularly the differences in the research contexts and the specific characteristics of the populations served by the ambulance services in each study. In Kermanshah, Mohammadi et al. (2014) [50] evaluated the time performance of the emergency response center to provide prehospital emergency services in Kermanshah. The results revealed that, out of a total of 500 missions, most patients in the emergency missions were male. The maximum time spent rescuing people is related to the interval between reaching the scene to moving from the scene and then is related to the interval between moving from the scene to reaching the hospital. The overall mean performance time from the scene to the health center was 11.34 min. Although in both studies, most of the transported casualties were men, the current study revealed a shorter time interval from arriving at the scene to moving from the scene, which differed from Mohammadi’s results. This disparity may be attributed to the fact that only traffic accidents were investigated in the present study, and the patient population for home missions differed.

Asadi (2021) [51] examined 327 missions in Ardabil and reported that EMS response times were at an acceptable level. Similarly, Taheri (2017) [52] investigated 299,956 missions in Isfahan and discovered that the mean response time met the standard limit in only 50.6% of cases, which contrasts with the findings of the current study, where the response time met the standard limit in all zones.

Importantly, empirical evidence from various global studies indicates that the typical response time in urban settings is typically shorter than that in rural areas [4, 39, 42, 53,54,55,56]. The results of our study also demonstrated that the mean response time, on-scene time, and transfer time from the scene of the accident to the hospital were shorter for inner-city locations than for road locations. This finding aligns with the research outcomes of Bigdeli et al. [39] and Alruwaili et al. [53]. A retrospective cross-sectional study was conducted by Bigdeli et al. [39] in 2010 to estimate the mean intervals during the prehospital care process and to investigate the differences between these time intervals in terms of RTI on the urban and intercity roads of Urmia. In total, 2027 RTI victims were analyzed. The mean response time, on-scene time, and transport time from the scene to the hospital and the mean total prehospital time for city locations were less than those for interurban road locations. Alruwaili et al. (2022) [53] conducted a systematic review of emergency medical services (EMS) studies to discuss the differences in prehospital time intervals between rural and urban communities. A total of 78.4% reported a difference in response time between rural and urban areas. All the studies reported a significantly shorter prehospital time in urban communities than in rural communities.

In summary, one of the major challenges identified is the extended response time in Zone 12, which often exceeds standard limits. This delay can be attributed to the high volume of emergency calls and the logistical difficulties associated with navigating densely populated and industrial zones. To address this, strategic placement of EMS units and the implementation of advanced dispatching systems are needed to optimize response times. In addition, dissatisfaction with patient transfers in Zones 10, 14, and 3 highlights the need for improved coordination between the EMS and medical facilities. The reluctance of patients to transfer from zones with medical centers suggests a preference for proximity to medical services that should be considered in EMS planning.

Limitations

The absence of the injury severity score (ISS) for each mission restricted the ability to assess injury severity fully and its correlation with response times, thus limiting the analysis of their impact on patient outcomes. Selection bias is a concern since the study included only traffic accidents requiring ambulance dispatch, excluding minor or self-managed cases. Reporting bias may have occurred because of the reliance on accurate recording by emergency medical services personnel, potentially leading to inconsistencies or inaccuracies.

The retrospective study design limits the findings to the accuracy and completeness of historical data, preventing control for confounding variables and the establishment of causality. Specifically, we encountered issues with the EMS database, which included impaired and incomplete data. Additionally, the dataset only records injury dates without specifying the days of the week or holidays. Consequently, we were unable to subdivide the time periods of accidents into smaller segments beyond morning, evening, and night.

To extract and analyze these additional details, nearly 8000 records need to be assessed, which is a time-intensive process. This limitation restricts our ability to provide more granular time data, which would have been beneficial for decision-makers in planning accident prevention and improving emergency services. We acknowledge the importance of this detail and address this constraint in future research efforts.

The results are specific to Isfahan city and may not be generalizable to other regions with different infrastructures or emergency response systems. Despite efforts to ensure data quality, missing or incomplete records could affect the overall analysis. External factors such as weather conditions, public events, and policy changes were not systematically accounted for, which might have influenced the traffic accident rates and response times.

This study provides valuable insights, but future research should address these limitations by using prospective designs, comprehensive injury severity assessments, and robust data quality control. Expanding the study to various urban and rural settings could improve the generalizability of the findings.

Conclusion

The findings of the present study yielded valuable insights into the diversity and frequency of missions conducted in a prehospital emergency setting. The results demonstrated that certain indicators presented values within the standard range, whereas others presented values that were considerably disparate from those reported in other areas of the country and the world. The results of this research emphasize the importance of identifying zones characterized by significant population mobility, major roads or high traffic levels and, if possible, establishing operational bases in these strategic locations. In addition, in zones that experience a greater number of missions, it is necessary to ensure that the number of ambulances is sufficiently coordinated with the volume of missions performed. The study of prehospital response time intervals in Isfahan underscores the critical need for efficient emergency medical services to manage urban traffic accidents effectively. By understanding the factors influencing response times and addressing challenges through strategic planning and technological advancements, Isfahan can enhance its EMS capabilities and improve outcomes for traffic accident victims.

Continued research and investment in EMS infrastructure are essential to ensure timely and effective prehospital care in urban settings. Future research should aim to develop targeted strategies to improve emergency response times and ultimately improve patient outcomes and reduce mortality and morbidity in traffic accidents.

Practical recommendations for policy interventions and infrastructure improvements

• Enhanced Traffic Management: Utilizing advanced traffic monitoring and control systems, such as intelligent traffic systems (ITS), can significantly reduce congestion, particularly during peak hours. Establishing designated emergency lanes ensures that emergency vehicles can navigate through high-traffic areas without delay, improving their response times to accident scenes.

• Strategic Placement of EMS Bases: Strategically placing EMS bases in high-risk areas identified through traffic volume and accident frequency analysis can minimize response times. Expanding the number of EMS stations in densely populated and high-risk zones, ensuring that they are adequately staffed and equipped, is crucial for efficient emergency response.

• Public Awareness Campaigns: Launching educational campaigns to increase public awareness about road safety measures, adherence to traffic laws, and the use of protective equipment such as seat belts and helmets can reduce risky behaviors and improve overall safety. These campaigns can significantly contribute to reducing the number of traffic accidents.

• Technological enhancements: Equipping ambulances with GPS and real-time tracking systems optimizes route planning and reduces travel times to accident scenes. The development of mobile applications for emergency services can enable citizens to report accidents quickly, provide real-time updates, and receive immediate guidance while waiting for the EMS to arrive.

• Training and Resources for EMS personnel: Regular training programs for EMS personnel focusing on rapid response techniques, advanced life support, and effective communication are essential. Ensuring that ambulances are equipped with state-of-the-art medical equipment and supplies will enhance the quality of prehospital care provided.

• Infrastructure improvements: Investing in the improvement of road conditions, including the construction of safer intersections, pedestrian crossings, and traffic calming measures, can reduce accident risks. The development of specific emergency response corridors optimized for quick emergency responses, with clear signage and traffic regulations favoring emergency vehicle passage, is also vital.

• Policy and Regulation Adjustments: Strengthening the enforcement of traffic laws, including penalties for speeding, driving under influence, and noncompliance with seat belt usage, is necessary. Collaboration between the EMS and law enforcement agencies can ensure coordinated responses to traffic accidents and efficient management of accident scenes. Implementing these practical recommendations can increase the efficiency of emergency medical services and reduce response times in urban areas. By combining technological advancements, strategic planning, public education, and infrastructure development, policymakers can improve citizen safety and well-being, ultimately saving lives and reducing the impact of traffic accidents.

Data availability

Data are available upon reasonable request from the corresponding author.