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A timeliness analysis of emergency services and cardiovascular outcomes in cardiac patients referred through prehospital emergency services between 2020 and 2023: a cross-sectional study in Iran

BMC Research Notes volume 17, Article number: 250 (2024) Cite this article

Abstract

Objective

Effective time management is crucial for the survival of all patients, particularly those with cardiovascular conditions. This is especially true in the context of pre-hospital emergency services, where prompt intervention can significantly impact outcomes. This study delves into the timeliness of emergency services and the subsequent outcomes for hospitalized cardiovascular patients in EMS center in Fasa University of Medical Sciences, southern Iran.

Results

A total of 4972 emergency calls related to cardiac diagnoses were received between 2020 and 2023. The transport time was significantly correlated with age, location of the mission, and type of mission. Of the total, 86 underwent angioplasty within the standard time of less than 90 min, of which 81 were discharged and 5 died. 51 patients underwent angioplasty after more than 90 min, of which 47 were discharged and 4 died. In addition, 124 of these patients experienced cardiopulmonary resuscitation, of which 63 were successful and 61 were unsuccessful.

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Introduction

Prehospital emergency services are typically the first point of contact for victims, injured persons, and patients at the scene of an accident or in the patient’s home. In fact, time management in emergency services can mean the difference between life and death for patients [1, 2].

Cardiovascular diseases are responsible for one-third of all deaths worldwide, and among heart diseases, ischemic heart disease ranks first in mortality [3, 4]. Time management in prehospital emergency services refers to responding within a standard time frame and avoiding delays. Consequently, time management and the absence of delays in prehospital emergency services, especially in patients with ischemic heart disease, patients with ST-segment elevation myocardial infarction, and patients with cardiac arrhythmias, is a critical factor that is directly related to patient mortality [5,6,7]. According to data from the American Heart Association, performing percutaneous coronary interventions within 90 min of symptom onset in patients with suspected heart attack is a critical goal in the treatment system and minimizes mortality and complications [8].

Minimizing cardiac ischemic time, improving blood flow, and ensuring rapid emergency response are all critical factors in preserving patient life. In urban areas, emergency response should take no longer than 5 min from the time of the call, and in rural areas, no longer than 15 min [9]. Time management by prehospital emergency personnel from the onset of symptoms to the start of the first treatment intervention can be of great importance in patients with ischemic heart disease [10, 11].

In the present study, we aim to investigate the timing of emergency services and the final cardiovascular outcome, including death, discharge, coronary interventions and their outcomes, the number of successful and unsuccessful cardiopulmonary resuscitations, and the time of their delivery by the emergency and hospital teams. By presenting the results, we can identify the strengths and weaknesses in this area.

Main text

Study design

This study is a descriptive-analytical, cross-sectional study in emergency medical services (EMS) in Fasa University of Medical Sciences, in Fars Province, Southern Iran, that collected research timing data through the ASAYAR system. The ASAYAR automation system is responsible for managing and controlling the service delivery process in the National Emergency Organization from the moment the caller contacts the system until the end of the mission. Using this system, the demographic characteristics, all times, and patient problems are quickly registered systematically and reported to treatment centers [12]. This dataset included demographic information, all timing data for cardiac patients from the time of call to hospital transfer, mission location, destination hospital name, emergency location, and outcome from 2020 to 2023, and contained 4972 data points. According to the emergency timing data, the 10 recorded times included 1-call time (patient call to the emergency center), 2-response time (the time the emergency center answers the call), 3-mission receipt time, 4-departure time from the base, 5-arrival time at the emergency scene, 6-departure time from the emergency scene, 7-arrival time at the treatment center, 8-delivery time to the treatment center, 9-mission end time, and 10-arrival time at the base. In addition, three other time intervals were considered, which included; 1- the time from calling the base to arriving at the scene (Response Time), 2- the time from the ambulance arriving at the scene to the decision to leave the scene (Scene Time), and 3- the time from the ambulance leaving the scene to arriving at the triage unit of the emergency department (Transport Time) [13, 14]. Given the high importance of these three time intervals in evaluating the timing performance of emergency services, they are reported.

To verify and identify patients in the hospital, four items, including name, date of admission, time of admission, and age of patients, were carefully examined in the emergency department and hospital system files to ensure the accuracy of the information. Finally, the patients were confidently matched in the hospital system and the emergency department file. After the files were prepared, they were sorted in consultation with the statistical consultant, and central tendency measures such as mean, standard deviation, frequency, and percentage were used for data analysis.

Data analysis

The collected data were analyzed with SPSS software 22.0. The mean timing of emergency department stages was compared in population subgroups, and the mean timing of outcomes such as angioplasty, hospitalization, death, and others was also compared using ANOVA and regression analysis. The relationship between outcomes and mission details (timing of different stages, gender, urban and rural location, etc.) was examined using the chi-square test.

Results

According to the results obtained from the emergency department timekeeping file, there were 4972 telephone calls related to cardiac diagnosis between 2020 and 2023. There were 2874 male and 2098 female cases. The location of the mission was 2335 cases in the city and 2637 cases outside the city. there were 4424 telephone cases and 548 face-to-face cases. The final results announced by the emergency department were 4035 cases of transfer to the hospital, 98 cases of first aid, 549 cases of non-cooperation and 275 cases of death before the arrival of the technician. In this study the mean score ± SD, time from calling the base to arriving at the scene (Response Time) was found to be 1.54 ± 0.91 min, the mean score ± SD of time from the ambulance arriving at the scene to the decision to leave the scene (Scene Time) was 5.57 ± 4.38 min, and the mean score ± SD, the time from the ambulance leaving the scene to arriving at the triage unit of the emergency department (Transport Time) was 6.14 ± 8.81 min respectively. Figure 1: presents the timing of pre-hospital emergency services from the moment of receiving a call to the moment of delivering the patient to the hospital.

Fig. 1
figure 1

The timing of pre-hospital emergency services from the moment of receiving a call to the moment of delivering the patient to the hospital. The first number is the median and in parentheses (mean and standard deviation). Times are calculated in minutes

Full size image

Based on the findings of our study, the most common clinical symptoms reported by patients were chest pain, cold sweats, shoulder pain, jaw pain and epigastric pain. According to Table 1, the relationship between response time and age was significant for patients over 65 years old (mean 8.508 ± 4.096 min) compared to patients between 30 and 45 years old (mean 8.966 ± 4.607 min), with a P-value of 0.020. The relationship between response time and location of mission was also significant, with a mean response time of 8.04 ± 3.154 min for inner city patients and 9.361 ± 5.177 min for outer city patients (P-value = p < 0.001).

Table 1 Mean and standard deviation of response time of prehospital emergency centers
Full size table

According to Table 2, there was a significant relationship between scene time and gender, with male patients having a mean scene time of 15.013 ± 10.289 min and female patients having a mean scene time of 15.918 ± 9.648 min (P-value = 0.002). There was also a significant relationship between scene time and age, with patients over 65 years old having a mean scene time of 17.022 ± 11.233 min compared to patients between 30 and 45 years old with a mean scene time of 14.436 ± 9.042 min and patients between 45 and 65 years old with a mean scene time of 14.44 ± 9.178 min (both P-values = p < 0.001).

Table 2 Mean and standard deviation of scene time of prehospital emergency centers
Full size table

Based on the location of the mission, there was a significant relationship between scene time and location, with inner city patients having a mean scene time of 7.794 ± 5.033 min compared to outer city patients with a mean scene time of 28.246 ± 14.379 min. Based on the type of mission, there was also a significant relationship between scene time and type of mission, with telephone patients having a mean scene time of 18.711 ± 15.094 min compared to in-person patients with a mean scene time of 24.156 ± 15.008 min (P-value = p < 0.001).

In terms of scene time, the longest time, with a mean of 29.924 ± 17.914 min, was for patients who died before the arrival of the technician. The next longest times were for other outcomes (including handover to another ambulance, transfer by personal vehicle, cancellation of the mission by the control center, and false mission), with a mean of 23.225 ± 15.369 min; non-cooperation, with a mean of 20.151 ± 8.745 min; first aid, with a mean of 17.335 ± 9.967 min; and transfer, with a mean of 13.725 ± 8.3 min. There was a significant relationship between all patients and patients transferred to hospital, and also between patients who died before the arrival of the technician and patients who received first aid and non-cooperation (P-value < 0.005).

The data in Table 3 showed that there was a significant relationship between transfer time and age, with patients over 65 years old having a mean transfer time of 20.554 ± 15.936 min compared to patients between 30 45 years old with a mean transfer time of 17.84 ± 14.367 min and patients between 45 and 65 years old with a mean transfer time of 19.05 ± 14.831 min (P-value = p < 0.001 and P-value = 0.022, respectively).

Table 3 Mean and standard deviation of transport time of prehospital emergency centers
Full size table

The data in Table 4 showed that 137 out of 500 cases (27.4%) with code 247 underwent angioplasty. Of those who underwent angioplasty, 86 cases (62.7%) were performed within 90 min, which is the standard time for coronary intervention. Of these, 81 cases were discharged and 5 cases died. 51 cases (37.3%) were performed over 90 min, of which 47 cases were discharged and 4 cases died.

Table 4 Frequency and percentage frequency of angioplasty within the standard time based on gender, outcome, and time sequence during the years 2020 to 2023
Full size table

According to Table 4, the relationship between patients who underwent angioplasty within 90 min (the golden time) and those who underwent angioplasty after 90 min (with a delay) was assessed based on the following factors: gender, outcome, year of the event, and season of the event. The results are as follows:

According to patient outcomes, 63.3% of discharged patients underwent angioplasty within the standard time, while 36.7% of discharged patients underwent angioplasty outside the standard time. Additionally, 55.6% of deceased patients underwent angioplasty within the standard time, while 44.4% of deceased patients underwent angioplasty outside the standard time.

According to the year of the event, in 2020, 65% of patients underwent angioplasty within the standard time and 35% underwent angioplasty outside the standard time. In 2021, 69% of patients underwent angiography within the standard time and 31% underwent angiography outside the standard time. In 2022, 63.4% of patients underwent angiography within the standard time and 36.6% of patients underwent angiography outside the standard time. Finally, in 2023, 57.4% of patients underwent angiography within the standard time and 42.6% of patients underwent angiography outside the standard time.

Discussion

The golden and standard time for response time in out-of-city missions is 12 min, in inner-city missions of metropolitan cities is 12 min, and in inner-city missions of cities is 8 min. The scene time should also be as short as possible and less than 20 min. However, this time may increase depending on specific conditions such as cardiopulmonary resuscitation, security requirements, and difficulties in exiting the scene [15,16,17].

Based on Table 1, emergency personnel arrive at the scene of an accident more quickly in urban missions than in out-of-city missions. This time (3.154 ± 8.04 min) is slightly longer than the standard 8-minute time, but it is very close to the international standard, which indicates the quality of the emergency response. There is also a significant correlation between the two times. This significant difference is likely due to the difference in distance between urban and out-of-city missions.

Table 2 shows that the time to arrive at the scene of an emergency until leaving the scene of the emergency (scene time) is related to the gender of the individuals and is higher in females than in males. This is while previous studies have shown that mortality in women with cardiovascular disease is higher than in men, and cardiovascular diseases are associated with greater risks in women [18]. Previous studies have also shown that gender has a significant impact on prevention, clinical manifestations, diagnostic and therapeutic approaches, prognosis, psychological and social effects, and interaction with the healthcare system [19]. One of the most important reasons for this can be cultural issues in our country, the lack of female technicians in prehospital emergency services in our country, and some sensitivities about the female gender.

In relation to the age of individuals, it has been shown according to both scene time and transfer time that it takes significantly longer for individuals over 65 years of age to be transferred to the hospital. Possible reasons for this include loneliness, low health literacy, previous medical history (more advanced disease), comorbid diseases as a result of older age, resuscitation in the scene, and emergency technicians being involved in stabilizing the condition of elderly patients [20,21,22].

Additionally, the time that emergency personnel spend at the scene of an accident in out-of-city missions is shorter. Possible reasons for this include the lack of interference and harassment from bystanders, and the less traffic congestion and crowds in out-of-city missions compared to in-city missions.

This study demonstrates that if patients are transferred to the county referral hospital, we can allocate more time for their treatment and less time is wasted, as it appears that several minutes are spent by the prehospital emergency team deciding whether to transfer to a treatment centre with adequate facilities.

Individuals who approach the personnel in person are triaged in a shorter amount of time, which is a very important issue because rapid triage of cardiac patients and transferring them to the hospital with minimal movement is one of the most critical factors in cardiac patient care.

Table 3 shows the relationship between the time of departure from the emergency scene and arrival at the hospital. As mentioned earlier, there is a significant relationship between this transfer time and the age of individuals, with the transfer time increasing as the age of the individuals, increases.

Based on the type of mission, it has been shown that more time is spent on in-person missions than on telephone missions, which contradicts the type of mission at the scene time. The reason for this is that patients who are transferred between hospitals are usually included in these missions, which usually significantly increases this time due to the time it takes to prepare and transfer them.

The average response time for inner-city patients was very close to the global standard time of 8 min, and for out-of-city patients it was less than the standard time of 12 min. The average scene time for both inner-city and out-of-city patients was also within the global standard time of 20 min in our country. This can be attributed to the standard number of bases in the city of Fasa, which is 6 inner-city and 11 out-of-city, with a road base every 15 km [17].

According to various studies, the golden and standard time for performing coronary interventions is 90 min from the time of admission to the hospital to the performance of angioplasty. In such a way that the mortality of patients has a direct relationship with the increase in this time [23].

According to the data in Table 4, regarding the outcome of patients after angioplasty, the majority of patients, 86 cases (62.7%), underwent angioplasty within the standard time frame. Additionally, 51 cases (37.3%) required more than 90 min for PCI. This may be due to various reasons, including unstable patient conditions for angioplasty, the necessity for additional tests and echocardiography before angioplasty, the unavailability of a specialist in coronary interventions, the patient’s initial refusal to undergo angioplasty and subsequent consent, and other similar factors. Notably, these factors did not result in increased mortality among these patients, and no significant findings were observed. Nevertheless, there should be no justification for wasting time and putting the patient’s life at risk. Although no significant findings were observed, there is an increasing trend in the number and delay of coronary interventions among cardiac patients in all years except 2020. The possible reasons for this include a shortage of equipment, an increase in coronary artery diseases, especially due to the global COVID-19 pandemic and its direct association with inflammatory and vascular diseases, patients’ lack of familiarity with emergencies and their importance in cardiac patients, and increased urban traffic leading to delays in patient transfer [24].

Limitations

One of the problems of the ASAYAR system’s registration in the patient information sheet in the emergency medical services was the lack of registration of the complete demographic information of the patients, including occupation, educational qualification, and medical history. Also, the outcomes of cardiac patients, including the number and cause of death of cardiac patients after referral to the hospital, have not been recorded. It is recommended that senior emergency managers use more accurate and comprehensive up-to-date systems to register patients in emergency services.

Conclusion

An analysis of the timeliness of emergency services showed that the response, scene, and transport times were all within the global standard.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

The authors appreciate Fasa University of Medical Sciences for financially supporting this research. Also, authors would like to appreciate Fasa University of Medical Sciences & Clinical Research Development Unit of Fasa, Valiasr hospital for financially supporting this research. Also, the authors would like to appreciate emergency medical services (EMS) in Fasa University of Medical Sciences for supporting this research.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not for profit sectors.

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Authors and Affiliations

  1. Student Research Committee, School of Nursing, Fasa University of Medical Sciences, Fasa, Iran

    Mohammad Soleimanian

  2. Department of Medical Surgical Nursing, School of Nursing, Fasa University of Medical Sciences, Fasa, Iran

    Mostafa Bijani, Leila Nikrouz, Kamran Ranjbar & Gholamali Heidari

  3. Noncommunicable Diseases Research Center (NCDRC), Fasa University of Medical Sciences, Fasa, Iran

    Mohammad Mehdi Naghizadeh

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  1. Mohammad Soleimanian
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Contributions

MB, MS and LN have participated in the conception and design of the study. MN, KR and GH, contributed the acquisition and analysis of data. MB and MS, prepared the first draft of the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Mostafa Bijani or Leila Nikrouz.

Ethics declarations

Ethics approval and consent to participate

All participants signed a written and informed consent to participate in this study. This study was carried out based on the principles of the revised Declaration of Helsinki, a statement of ethical principles that guides the medical researchers investigating human subjects. Before the interviews, the objectives of the study were explained for all the subjects, and we ensured them about their voluntary participation in the study; Moreover, the study was approved by the Institutional Research Ethics Committee of Fasa University of Medical Sciences, Fasa, Iran (ethical code: IR.FUMS.REC. 1401.114).

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Competing interests

The authors declare no competing interests.

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Soleimanian, M., Bijani, M., Nikrouz, L. et al. A timeliness analysis of emergency services and cardiovascular outcomes in cardiac patients referred through prehospital emergency services between 2020 and 2023: a cross-sectional study in Iran. BMC Res Notes 17, 250 (2024). https://doi.org/10.1186/s13104-024-06922-5

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ISSN: 1756-0500

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