Spatial analysis of ambulance response times related to prehospital cardiac arrests in the city-state of Singapore

Examining district-level disparity and determinants of timeliness of emergency medical services in Maharashtra, India

The quality of emergency medical services remains a major public health issue in developing countries in terms of access, availability, or timely delivery, owing to high socio-economic and ethnic disparities. Particularly, the timeliness of EMS remains a drawback, leading to higher mortality and morbidity. The aim of the study is to assess the district-level differences and factors that influence ambulance travel time, as there was no study done in the Indian scenario. Sequential Explanatory Design was applied here, which involved a descriptive study and spatial analysis of the call volume and distribution to understand the operational challenges of MEMS, followed by in-depth interviews among medical officers and officials to explore the reasons for the challenges. The data, shared by the Department of Health, Government of Maharashtra, consisted of 38,823 records (emergency: 16,197 and hospital-to-hospital transfer: 22,626), including emergency and hospital-to-hospital transfer calls across 36 districts of Maharashtra for November 2022. Spatial analyses were performed to identify the districts with challenges of timeliness. The average ambulance response time (T) across the districts was reported at 134.5 min for emergency cases and 222.80 min for hospital-to-hospital transfer cases. The total ambulance response time, was classified as preparation time (t1:3.53 min for emergency, 3.69 min for hospital-to-hospital transfer), travel time from base to scene (t2: 23.15 min for emergency, 17.18 min for hospital-to-hospital transfer), time required at scene (t3: 12.12 min for emergency, 14.72 min for hospital-to-hospital transfer), travel time from scene to hospital (t4:39.41 min for emergency, 74.34 min for hospital-to-hospital transfer), patient handover time (t5: 10.85 min for emergency, 13.84 min for hospital-to-hospital transfer), and return from base to hospital (t6: 41.89 min for emergency, 94.72 min for hospital-to-hospital transfer). Multivariate linear regression was conducted to investigate the factors that influence ambulance travel time. The finding identifies that the ambulance travel time increased for the districts with lesser population density, lower road density, fewer hospitals, a higher district area served per ambulance, and a higher population served per ambulance. Additionally, socio-cultural reasons affecting health-seeking behaviour, early closing of healthcare centres, undercapacity and resource-deficit healthcare centres, and overloading of specialised tertiary hospitals were identified as determinants of delay in patient assessment and handover time in qualitative findings. A decisive and multi-sectoral approach is required to address the timeliness of EMS in the Indian context.

Influence of advanced life support response time on out-of-hospital cardiac arrest patient outcomes in Taipei

Background

The association between out-of-hospital cardiac arrest patient survival and advanced life support response time remained controversial. We aimed to test the hypothesis that for adult, non-traumatic, out-of-hospital cardiac arrest patients, a shorter advanced life support response time is associated with a better chance of survival. We analyzed Utstein-based registry data on adult, non-traumatic, out-of-hospital cardiac arrest patients in Taipei from 2011 to 2015.

Methods

Patients without complete data, witnessed by emergency medical technicians, or with response times of ≥ 15 minutes, were excluded. We used logistic regression with an exposure of advanced life support response time. Primary and secondary outcomes were survival to hospital discharge and favorable neurological outcomes (cerebral performance category ≤ 2), respectively. Subgroup analyses were based on presenting rhythms of out-of-hospital cardiac arrest, bystander cardiopulmonary resuscitation, and witness status.

Results

A total of 4,278 cases were included in the final analysis. The median advanced life support response time was 9 minutes. For every minute delayed in advanced life support response time, the chance of survival to hospital discharge would reduce by 7% and chance of favorable neurological outcome by 9%. Subgroup analysis showed that a longer advanced life support response time was negatively associated with the chance of survival to hospital discharge among out-of-hospital cardiac arrest patients with shockable rhythm and pulse electrical activity groups.

Conclusions

In non-traumatic, adult, out-of-hospital cardiac arrest patients in Taipei, a longer advanced life support response time was associated with declining odds of survival to hospital discharge and favorable neurologic outcomes, especially in patients presenting with shockable rhythm and pulse electrical activity.

On the Modelling of Emergency Ambulance Trips: The Case of the Žilina Region in Slovakia

The efficient operation of emergency medical services is critical for any society. Typically, optimisation and simulation models support decisions on emergency ambulance stations’ locations and ambulance management strategies. Essential inputs for such models are the spatiotemporal characteristics of ambulance trips. Access to data on the movements of ambulances is limited, and therefore modelling efforts often rely on assumptions (e.g., the Euclidean distance is used as a surrogate of the ambulance travel time; the closest available ambulance is dispatched to a call; or the travel time estimates, offered by application programming interfaces for ordinary vehicles, are applied to ambulances). These simplifying assumptions are often based on incomplete data or common sense without being fully supported by the evidence. Thus, data-driven research to model ambulance trips is required. We investigated a unique dataset of global positioning system-based measurements collected from seventeen emergency ambulances over three years. We enriched the data by exploring external sources and designed a rule-based procedure to extract ambulance trips for emergency cases. Trips were split into training and test sets. The training set was used to develop a series of statistical models that capture the spatiotemporal characteristics of emergency ambulance trips. The models were used to generate synthetic ambulance trips, and those were compared with the test set to decide which models are the most suitable and to evaluate degrees to which they fit the statistical properties of real-world trips. As confirmed by the low values of the Kullback–Leibler divergence (0.004–0.229) and by the Kolmogorov–Smirnov test at the significance level of 0.05, we found a very good fit between the probability distributions of spatiotemporal properties of synthetic and real trips. A reasonable modelling choice is a model where the exponential dependency on the population density is used to locate emergency cases, emergency cases are allocated to hospitals following empirical probabilities, and ambulances are routed using the fastest paths. The models we developed can be used in optimisations and simulations to improve their validity.

Factors affecting development of air ambulance base: A systematic review and thematic analysis

Nowadays, air ambulances have been developed as part of advanced emergency medicine services with many countries employing these services for transferring patients in usual and emergency conditions. However, there are challenges concerning the optimal development of air ambulance base. The present research aimed to identify factors affecting the development of air ambulance bases to provide the opportunity of planning to improve the quality of emergency medical services. In this systematic literature review, the peer-reviewed papers in fiv electronic databases, including Medline through PubMed, Scopus, Web of Science, ScienceDirect, and ProQuest, as well as available gray literature, were searched and selected. Two combinations of groups were used as keywords: the Health Planning and development factor, air ambulance base. The focus was on the PRISMA checklist, with no time limitations until from 1990 to January 2020. Finally, through 5156 related citations, 20 articles were included. Descriptive and thematic content analyses were evaluated. The factors affecting the development of the air ambulance base were classified in fiv categories and 14 subcategories as follows: navigation criteria, process indications and standards, sociopolitical factors, and current situation of the area. There are few studies on factors affecting the development of air ambulance bases. It is necessary to apply multidimensional models to consider various factors for development. The development of high populated cities, events and ceremonies with a crowd of participants, and increase of human-made disasters are making these services increasingly indispensable.

Comparison of pre-hospital emergency services time intervals in patients with heart attack in Arak, Iran

Background:

After cardiac arrest, the possibility of death or irreversible complications will highly increase in the absence of cardiac resuscitation within 4 to 6 minutes. Accordingly, measuring the pre-hospital services time intervals is important for better management of emergency medical services delivery. The purpose of this study then was to investigate pre-hospital time intervals for patients with heart attack in Arak city, based on locations and time variables.

Methods:

This is a retrospective descriptive cross-sectional study, which was conducted at the Arak Emergency Medical Services (EMS) during 2017-2018. Data were analyzed by SPSS version 13.

Results:

The total number of heart attack patients registered in Arak emergency medical services was 2,659 of which 51% of patients were males. Six percent of patients were under 25 and about 49 percent were between 46 and 65 years old. The average of activation, response, on-scene, transportation, recovery and total time intervals were 3:30, 7:56, 15:15, 13:34, 11:07, 12:11, and 41:25, respectively. In the city area, the shortest and longest average response time intervals were in spring and winter, respectively. In out of the city area, the shortest average response time interval was in summer and the longest one in autumn. The shortest and the longest average response time intervals in the city area were in June and March, respectively, and in out of the city area, the shortest average response time interval was in June and the longest one in April.

Conclusions:

The shorter response and delivery time interval compared to the other studies may indicate improvement in the provision of EMS. Special attention should be paid to the facilities and equipment of vehicles during cold seasons to be in the shortest possible time. Also, training and informing the staff more about the code of cardiac patients along with general public education can help improve these intervals.

Spatial-time analysis of cardiovascular emergency medical requests: enlightening policy and practice

Background

Response time to cardiovascular emergency medical requests is an important indicator in reducing cardiovascular disease (CVD) -related mortality. This study aimed to visualize the spatial-time distribution of response time, scene time, and call-to-hospital time of these emergency requests. We also identified patterns of clusters of CVD-related calls.

Methods

This cross-sectional study was conducted in Mashhad, north-eastern Iran, between August 2017 and December 2019. The response time to every CVD-related emergency medical request call was computed using spatial and classical statistical analyses. The Anselin Local Moran’s I was performed to identify potential clusters in the patterns of CVD-related calls, response time, call-to-hospital arrival time, and scene-to-hospital arrival time at small area level (neighborhood level) in Mashhad, Iran.

Results

There were 84,239 CVD-related emergency request calls, 61.64% of which resulted in the transport of patients to clinical centers by EMS, while 2.62% of callers (a total of 2218 persons) died before EMS arrival. The number of CVD-related emergency calls increased by almost 7% between 2017 and 2018, and by 19% between 2017 and 2019. The peak time for calls was between 9 p.m. and 1 a.m., and the lowest number of calls were recorded between 3 a.m. and 9 a.m. Saturday was the busiest day of the week in terms of call volume. There were statistically significant clusters in the pattern of CVD-related calls in the south-eastern region of Mashhad. Further, we found a large spatial variation in scene-to-hospital arrival time and call-to-hospital arrival time in the area under study.

Conclusion

The use of geographical information systems and spatial analyses in modelling and quantifying EMS response time provides a new vein of knowledge for decision makers in emergency services management. Spatial as well as temporal clustering of EMS calls were present in the study area. The reasons for clustering of unfavorable time indices for EMS response requires further exploration. This approach enables policymakers to design tailored interventions to improve response time and reduce CVD-related mortality.

Epidemiological profile of emergency medical services in Japan: a population-based descriptive study in 2016

Aim

The aim of our study is to describe the characteristics of patients who use emergency medical services (EMS), EMS performance, and regional variations in Japan.

Methods

We undertook a nationwide, population‐based, descriptive review of anonymized ambulance transport records obtained from the Fire and Disaster Management Agency in Japan. All emergency patients transported to emergency medical institutions by EMS personnel from January to December 2016 were enrolled in this study, excluding patients who were not transported.

Results

During the study period, 5,097,838 patients were transported to a hospital. Their median age was 69 years, 51.4% were male, and 56.5% were over 65 years old. Median durations from EMS call to EMS arrival on scene were similar among the regions, ranging from 7 to 9 min. However, the longest median duration from EMS call to hospital arrival was 38 min, and the shortest was 31 min across the regions. Among all patients, 350,865 (6.9%) were assessed as being in a severe condition, 14,410 (0.3%) were in very severe condition, and 74,780 (1.5%) were confirmed to be dead at the time of initial medical examination in the emergency department.

Conclusions

We described the characteristics of emergency patients and EMS performance in Japan. This registry serves as a basis for providing relevant information to improve prehospital emergency medical systems.

Association between ambulance response time and neurologic outcome in patients with cardiac arrest

PURPOSE

Emergency medical services (EMS) response time is one of prehospital factors associated with survival rate of patients with out-of-hospital cardiac arrest (OHCA). The objective of this study was to determine whether short EMS response time was associated with improved neurologic outcome of patients with OHCA through prospective analysis.

METHODS

We performed a prospective observational analysis of collected data from KoCARC registry between October 2015 and December 2016. OHCA patients aged 18 years or older with presumed cardiac etiology by emergency physicians in emergency department were included in this study.

RESULTS

Of 3187 cardiac arrest patients enrolled in the KoCARC registry, 2309 patients were included in the final analysis. Response time threshold was 11.5 min for prehospital return of spontaneous circulation and 7.5 min for survival to discharge and favorable neurologic outcome. Patients in the ≤7.5 min response time group showed increased odds of survival to discharge (OR: 1.54, 95% CI: 1.13-2.10, p = .006) and favorable neurologic recovery (OR: 2.01, 95% CI: 1.36-2.99, p = .001). When response time was decreased by 1 min, all outcomes were improved (survival to discharge, OR: 1.08; 95% CI: 1.04-1.12, p < .001; favorable neurological outcome, OR: 1.14, 95% CI: 1.07-1.21, p < .001).

CONCLUSION

We found that shorter EMS response time could lead to favorable neurologic outcome in patients with OHCA of presumed cardiac origin. EMS response time threshold associated with improved favorable outcome was ≤7.5 min.

Association of the Emergency Medical Services-Related Time Interval with Survival Outcomes of Out-of-Hospital Cardiac Arrest Cases in Four Asian Metropolitan Cities Using the Scoop-and-Run Emergency Medical Services Model

BACKGROUND

Response time interval (RTI) and scene time interval (STI) are key time variables in the out-of-hospital cardiac arrest (OHCA) cases treated and transported via emergency medical services (EMS).

OBJECTIVE

We evaluated distribution and interactive association of RTI and STI with survival outcomes of OHCA in four Asian metropolitan cities.

METHODS

An OHCA cohort from Pan-Asian Resuscitation Outcome Study (PAROS) conducted between January 2009 and December 2011 was analyzed. Adult EMS-treated cardiac arrests with presumed cardiac origin were included. A multivariable logistic regression model with an interaction term was used to evaluate the effect of STI according to different RTI categories on survival outcomes. Risk-adjusted predicted rates of survival outcomes were calculated and compared with observed rate.

RESULTS

A total of 16,974 OHCA cases were analyzed after serial exclusion. Median RTI was 6.0 min (interquartile range [IQR] 5.0-8.0 min) and median STI was 12.0 min (IQR 8.0-16.1). The prolonged STI in the longest RTI group was associated with a lower rate of survival to discharge or of survival 30 days after arrest (adjusted odds ratio [aOR] 0.59; 95% confidence interval [CI] 0.42-0.81), as well as a poorer neurologic outcome (aOR 0.63; 95% CI 0.41-0.97) without an increasing chance of prehospital return of spontaneous circulation (aOR 1.12; 95% CI 0.88-1.45).

CONCLUSIONS

Prolonged STI in OHCA with a delayed response time had a negative association with survival outcomes in four Asian metropolitan cities using the scoop-and-run EMS model. Establishing an optimal STI based on the response time could be considered.

Spatial methods for evaluating critical care and trauma transport: A scoping review

PURPOSE

The objective of this scoping review is to inform future applications of spatial research regarding transportation of critically ill patients. We hypothesized that this review would reveal gaps and limitations in the current research regarding use of spatial methods for critical care and trauma transport research.

MATERIALS AND METHODS

Four online databases, Ovid Medline, PubMed, Embase and Scopus, were searched. Studies were selected if they used geospatial methods to analyze a patient transports dataset. 12 studies were included in this review.

RESULTS

Majority of the studies employed spatial methods only to calculate travel time or distance even though methods and tools for more complex spatial analyses are widely available. Half of the studies were found to focus on hospital bypass, 2 studies focused on transportation (air or ground) mode selection, 2 studies compared predicted versus actual travel times, and 2 studies used spatial modeling to understand spatial variation in travel times.

CONCLUSIONS

There is a gap between the availability of spatial tools and their usage for analyzing and improving medical transportation. The adoption of geospatially guided transport decisions can meaningfully impact healthcare expenditures, especially in healthcare systems looking to strategically control expenditures with minimum impact on patient outcomes.

Spatial Variation and Resuscitation Process Affecting Survival after Out-of-Hospital Cardiac Arrests (OHCA)

BACKGROUND

Ambulance response times and resuscitation efforts are critical predictors of the survival rate after out-of-hospital cardiac arrests (OHCA). On the other hand, rural-urban differences in the OHCA survival rates are an important public health issue.

METHODS

We retrospectively reviewed the January 2011-December 2013 OHCA registry data of Kaohsiung City, Taiwan. With particular focus on geospatial variables, we aimed to unveil risk factors predicting the overall OHCA survival until hospital admission. Spatial analysis, network analysis, and the Kriging method by using geographic information systems were applied to analyze spatial variations and calculate the transport distance. Logistic regression was used to identify the risk factors for OHCA survival.

RESULTS

Among the 4,957 patients, the overall OHCA survival to hospital admission was 16.5%. In the multivariate analysis, female sex (adjusted odds ratio:, AOR, 1.24 [1.06-1.45]), events in public areas (AOR: 1.30 [1.05-1.61]), exposure to automated external defibrillator (AED) shock (AOR: 1.70 [1.30-2.23]), use of laryngeal mask airway (LMA) (AOR: 1.35 [1.16-1.58]), non-trauma patients (AOR: 1.41 [1.04-1.90]), ambulance bypassed the closest hospital (AOR: 1.28 [1.07-1.53]), and OHCA within the high population density areas (AOR: 1.89 [1.55-2.32]) were positively associated with improved OHCA survival. By contrast, a prolonged total emergency medical services (EMS) time interval was negatively associated with OHCA survival (AOR: 0.98 [0.96-0.99]).

CONCLUSIONS

Resuscitative efforts, such as AED or LMA use, and a short total EMS time interval improved OHCA outcomes in emergency departments. The spatial heterogeneity of emergency medical resources between rural and urban areas might affect survival rate.

General practitioner contribution to out-of-hospital cardiac arrest outcome: A national registry study

BACKGROUND

There is a wide variation in reported survival from out-of-hospital cardiac arrest (OHCA). One factor in this variation may be the contribution of general practitioners to pre-hospital resuscitation. Studies using self-reported data describe increased survival proportions when general practitioners are involved.

OBJECTIVES

This study aims to investigate the contribution of general practitioner involvement in out-of-hospital cardiac arrest events.

DESIGN AND SETTING

A retrospective observational study using data collected from ambulance records in the Republic of Ireland to describe general practitioner (GP) contribution to pre-hospital resuscitation attempts (n = 2369). Analysis is limited to patients with presumed cardiac cause and first arrest rhythm recorded as shockable (n = 510).

RESULTS

When a GP is present at scene (n = 199) patients are less likely to achieve return of spontaneous circulation (ROSC) (P < 0.001) or be transported to hospital (P < 0.001). When GPs participate in resuscitation (n = 92), patients are more likely to have collapsed in a public place (P < 0.01), receive bystander CPR (P < 0.001) and survive to hospital discharge (P < 0.001). Multiple logistic analysis of survival suggests that GP participation in resuscitation increases the odds of survival (4.6; 95% CI 1.6-13.3) and having collapsed in a public place increases chances of survival (5.8; 95% CI 2.1-15.7).

CONCLUSION

Our analysis suggests that in this subgroup, GP participation in OHCA resuscitation attempts is associated with improved patient survival. Furthermore, resuscitation is more likely to be ceased at scene when a GP is present, highlighting the role that GPs play in the compassionate management of death in unviable circumstances.