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

Spatiotemporal Analysis of Out-of-Hospital Cardiac Arrest Incidence and Survival Outcomes in Korea (2009-2021)

BACKGROUND

Out-of-hospital cardiac arrest is a major public health concern in Korea. Identifying spatiotemporal patterns of out-of-hospital cardiac arrest incidence and survival outcomes is crucial for effective resource allocation and targeted interventions. Thus, this study aimed to investigate the spatiotemporal epidemiology of out-of-hospital cardiac arrest in Korea, with a focus on identifying high-risk areas and populations and examining factors associated with prehospital outcomes.

METHODS

We conducted this population-based observational study using data from the Korean out-of-hospital cardiac arrest registry from January 2009 to December 2021. Using a Bayesian spatiotemporal model based on the Integrated Nested Laplace Approximation, we calculated the standardized incidence ratio and assessed the relative risk to compare the spatial and temporal distributions over time. The primary outcome was out-of-hospital cardiac arrest incidence, and the secondary outcomes included prehospital return of spontaneous circulation, survival to hospital admission and discharge, and good neurological outcomes.

RESULTS

Although the number of cases increased over time, the spatiotemporal analysis exhibited a discernible temporal pattern in the standardized incidence ratio of out-of-hospital cardiac arrest with a gradual decline over time (1.07; 95% credible interval [CrI], 1.04-1.09 in 2009 vs. 1.00; 95% CrI, 0.98-1.03 in 2021). The district-specific risk ratios of survival outcomes were more favorable in the metropolitan and major metropolitan areas. In particular, the neurological outcomes were significantly improved from relative risk 0.35 (0.31-0.39) in 2009 to 1.75 (1.65-1.86) in 2021.

CONCLUSION

This study emphasized the significance of small-area analyses in identifying high-risk regions and populations using spatiotemporal analyses. These findings have implications for public health planning efforts to alleviate the burden of out-of-hospital cardiac arrest in Korea.

Documented Use of Emergency Medical Dispatch Protocols is Associated with Improved Survival in Out of Hospital Cardiac Arrest

OBJECTIVE

There are over 300,000 out-of-hospital cardiac arrests (OHCA) annually in the United States (US) and despite many scientific advances in the field, the survival rate remains low. We seek to determine if return of spontaneous circulation (ROSC) is higher when use of emergency medical dispatch (EMD) protocols is documented for OHCA calls compared to when no EMD protocol use is documented. We also seek identify care-related processes that differ in calls that use EMD protocols.

METHODS

This is a retrospective cohort study of U.S. adults with OHCA prior to emergency medical services (EMS) arrival using 2019 National EMS Information System data. The primary exposure was EMD usage during EMS call. The primary outcome was prehospital ROSC, and secondary outcomes included automated external defibrillator (AED) use before EMS arrival, bystander CPR, and end-of-event EMS survival (survival to the end of the EMS care at transport destination). Multivariable logistic regression adjusted for age, sex, race/ethnicity, primary insurance, rurality, initial rhythm, arrest etiology, and witnessed arrest.

RESULTS

Of the 96,269 OHCA cases included, EMD use was documented in 73%. Overall, 26% of subjects achieved ROSC in EMS care. EMD subjects were more likely to achieve ROSC (27.2% vs. 23.5%, uOR 1.22, 95%CI 1.18 - 1.26) even after adjusting for subject and arrest characteristics (aOR 1.13, 95%CI 1.08 - 1.17). EMD subjects also had higher end-of-event survival (19.1% vs. 16.4%, aOR 1.20, 95%CI 1.15 - 1.25). AED use before EMS arrival was more common in the EMD group (28.3% vs. 26.3% %diff 2.0, 95%CI 1.4 to 2.6), as was CPR before EMS arrival (63.8% vs. 55.1%, difference 8.6%, 95%CI 7.9 to 9.3%).

CONCLUSIONS

In this retrospective analysis, the rate of ROSC was higher in adult OHCA patients when EMD protocol use was reported compared to when it was not reported. The group with documented EMD use also experienced higher rates of bystander AED use, bystander CPR, and end-of-event survival.

Survival After Out-of-Hospital Cardiac Arrest: The Role of Racial Residential Segregation

Racial and racialized economic residential segregation has been empirically associated with outcomes across multiple health conditions but not yet explored in relation to out-of-hospital cardiac arrest (OHCA). We sought to examine if measures of racial and economic residential segregation are associated with differences in survival to discharge after OHCA for Black and White Medicare beneficiaries. Utilizing age-eligible Medicare fee-for-service claims data from 2013 to 2015, we identified OHCA claims and determined survival to discharge. The primary predictor, residential segregation, was calculated using the index of concentration at the extremes (ICE) for the beneficiary residential ZIP code. Multilevel modified Poisson regression models were used to determine the association of OHCA outcomes and ZIP code level ICE measures. In total, 194,263 OHCA cases were identified among beneficiaries residing in 75% of US ZIP codes. Black beneficiaries exhibited 12.1% survival to discharge, compared with 12.5% of White beneficiaries. In fully adjusted models of the three ICE measures accounting for differences in treating hospital characteristics, there was as high as a 28% (RR 1.28, CI 1.23-1.26) higher relative likelihood of survival to discharge in the most segregated White ZIP codes (Q5) as compared to the most segregated Black ZIP codes (Q1). Racial residential segregation is independently associated with disparities in OHCA outcomes; among Medicare beneficiaries who generated a claim after suffering an OHCA, ICE measures of racial segregation are associated with a lower likelihood of survival to discharge for those living in the most segregated Black and lower income quintiles compared to higher quintiles.

The epidemiology of out-of-hospital cardiac arrest in Australia and New Zealand: A binational report from the Australasian Resuscitation Outcomes Consortium (Aus-ROC)

INTRODUCTION

The Australasian Resuscitation Outcomes Consortium (Aus-ROC) out-of-hospital cardiac arrest (OHCA) Epistry (Epidemiological Registry) now covers 100% of Australia and New Zealand (NZ). This study reports and compares the Utstein demographics, arrest characteristics and outcomes of OHCA patients across our region.

METHODS

We included all OHCA cases throughout 2019 as submitted to the Epistry by the eight Australian and two NZ emergency medical services (EMS). We calculated crude and age-standardised incidence rates and performed a national and EMS regional comparison.

RESULTS

We obtained data for 31,778 OHCA cases for 2019: 26,637 in Australia and 5,141 in NZ. Crude incidence was 107.9 per 100,000 person-years in Australia and 103.2/100,000 in NZ. Overall, the majority of OHCAs occurred in adults (96%), males (66%), private residences (76%), were unwitnessed (63%), of presumed medical aetiology (83%), and had an initial monitored rhythm of asystole (64%). In non-EMS-witnessed cases, 38% received bystander CPR and 2% received public defibrillation. Wide variation was seen between EMS regions for all OHCA demographics, arrest characteristics and outcomes. In patients who received an EMS-attempted resuscitation (13,664/31,778): 28% (range across EMS=13.1% to 36.7%) had return of spontaneous circulation (ROSC) at hospital arrival and 13% (range across EMS=9.9% to 20.7%) survived to hospital discharge/30-days. Survival in the Utstein comparator group (bystander-witnessed in shockable rhythm) varied across the EMS regions between 27.4% to 42.0%.

CONCLUSION

OHCA across Australia and NZ has varied incidence, characteristics and survival. Understanding the variation in survival and modifiable predictors is key to informing strategies to improve outcomes.

Spatiotemporal variation in the risk of out-of-hospital cardiac arrests in Queensland, Australia

BACKGROUND

Spatiotemporal analysis of out-of-hospital cardiac arrest (OHCA) risk is essential to design targeted public health strategies. Such information is lacking in the state of Queensland and Australia more broadly.

METHODS

We developed a spatiotemporal Bayesian model accounting for spatial and temporal dimensions, space-time interactions, and demographic factors. The model was fit to data of all OHCA cases attended by paramedics in Queensland between January 2007 and December 2019. Parameter inference was performed using the integrated nested Laplace approximation method. We estimated and thematically mapped area-year risk of OHCA occurrence for all 78 local government areas (LGAs) in Queensland.

RESULTS

We observed spatial variability in OHCA risk among the LGAs. Areas in the north half of the state and two areas in the south exhibited the highest risk; whereas OHCA risk was lowest in the west and south west parts of the state. Demographic factors did not have significant impact on the heterogeneity of risk between the LGAs. An overall trend of modestly decreasing risk of OHCA was found.

CONCLUSIONS

This study identified areas of high OHCA risk in Queensland, providing valuable information to guide public health policy and optimise resource allocation. Further research is needed to investigate the specifics of the areas that may explain their risk profile.

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.

Spatio-temporal prediction model of out-of-hospital cardiac arrest: Designation of medical priorities and estimation of human resources requirement

Aims

To determine the out-of-hospital cardiac arrest (OHCA) rates and occurrences at municipality level through a novel statistical model accounting for temporal and spatial heterogeneity, space-time interactions and demographic features. We also aimed to predict OHCAs rates and number at municipality level for the upcoming years estimating the related resources requirement.

Methods

All the consecutive OHCAs of presumed cardiac origin occurred from 2005 until 2018 in Canton Ticino region were included. We implemented an Integrated Nested Laplace Approximation statistical method for estimation and prediction of municipality OHCA rates, number of events and related uncertainties, using age and sex municipality compositions. Comparisons between predicted and real OHCA maps validated our model, whilst comparisons between estimated OHCA rates in different yeas and municipalities identified significantly different OHCA rates over space and time. Longer-time predicted OHCA maps provided Bayesian predictions of OHCA coverages in varying stressful conditions.

Results

2344 OHCAs were analyzed. OHCA incidence either progressively reduced or continuously increased over time in 6.8% of municipalities despite an overall stable spatio-temporal distribution of OHCAs. The predicted number of OHCAs accounts for 89% (2017) and 90% (2018) of the yearly variability of observed OHCAs with prediction error ≤1OHCA for each year in most municipalities. An increase in OHCAs number with a decline in the Automatic External Defibrillator availability per OHCA at region was estimated.

Conclusions

Our method enables prediction of OHCA risk at municipality level with high accuracy, providing a novel approach to estimate resource allocation and anticipate gaps in demand in upcoming years.

A Bayesian spatiotemporal statistical analysis of out-of-hospital cardiac arrests

We propose a Bayesian spatiotemporal statistical model for predicting out-of-hospital cardiac arrests (OHCAs). Risk maps for Ticino, adjusted for demographic covariates, are built for explaining and forecasting the spatial distribution of OHCAs and their temporal dynamics. The occurrence intensity of the OHCA event in each area of interest, and the cardiac risk-based clustering of municipalities are efficiently estimated, through a statistical model that decomposes OHCA intensity into overall intensity, demographic fixed effects, spatially structured and unstructured random effects, time polynomial dependence, and spatiotemporal random effect. In the studied geography, time evolution and dependence on demographic features are robust over different categories of OHCAs, but with variability in their spatial and spatiotemporal structure. Two main OHCA incidence-based clusters of municipalities are identified.

The Case for Drone-assisted Emergency Response to Cardiac Arrest: An Optimized Statewide Deployment Approach

BACKGROUND Despite evidence linking rapid defibrillation to out-of-hospital cardiac arrest (OHCA) survival, bystander use of automatic external defibrillators (AEDs) remains low, due in part to AED placement and accessibility. AED-equipped drones may improve time-to-defibrillation, yet the benefits and costs are unknown.METHODS We designed drone deployment networks for the state of North Carolina using mathematical optimization models to select drone stations from existing infrastructure by specifying the number of stations and the targeted AED arrival time. Expected outcomes were evaluated over the drone's lifespan (4 years). We estimated the following parameters: proportion of OHCAs within a targeted AED delivery time, bystander utilization of AEDs, survival/neurological status, and incremental cost per quality-adjusted life year (QALY).RESULTS Statewide, 16,503 adults aged 18 or older were expected to experience OHCA with an attempted resuscitation over 4 years. Compared to no drone network, all proposed drone networks were expected to improve survival outcomes. For example, assuming 46% of OHCAs have bystanders willing to use an AED, a 500-drone network decreased the median time of defibrillator arrival from 7.7 to 2.7 minutes compared to no drone network. Expected survival rates doubled (24.5% versus 12.3%), resulting in an additional 30,267 QALYs ($858/incremental QALY). If just 4.5% of OHCAs had willing bystanders, 13.8% of victims would have survived. Sensitivity analysis demonstrated that an AED drone network remained cost-effective over a wide range of assumptions.CONCLUSIONS With proper integration into existing systems, large-scale networks for drone AED delivery have the potential to substantially improve OHCA survival rates while remaining cost-effective. Public health researchers should consider advocating for feasibility studies and policy development surrounding drones.

Mandated 30-minute Scene Time Interval Correlates With Improved Return of Spontaneous Circulation at Emergency Department Arrival: A Before and After Study

BACKGROUND

Conflicting ideas exist about whether or not Emergency Medical Service (EMS) personnel should treat a cardiac arrest on scene or transport immediately.

OBJECTIVE

Our aim was to examine patient outcomes before and after an urban EMS system implemented a protocol change mandating a 30-min scene time interval (STI) for out-of-hospital cardiac arrest (OHCA).

METHODS

This was a retrospective, single-center, observational study of OHCA patients before and after an EMS protocol change mandating resuscitation on scene. Data were retrieved from an EMS cardiac arrest database for all adults with non-traumatic OHCA between January 2015 and August 2016. Descriptive statistics were used to summarize the study population, and a regression model was used to determine the associations of the protocol with the return of spontaneous circulation (ROSC).

RESULTS

A total of 633 patients were included in the study population, which was primarily male (61.3%) with a mean age of 65 years. After the 30-min STI was implemented, ROSC from OHCA increased to 40.1% of cases compared to 27.3% before the protocol change (p = 0.001; 95% confidence interval [CI] 0.053-0.203). The STI increased from 19 min 23 s to 29 min 40 s in the pre and post periods, respectively (p < 0.001). Regression indicated that the protocol change was independently associated with an improved chance of ROSC (OR 1.81; 95% CI 1.23-2.64).

CONCLUSIONS

A protocol change mandating a 30-min STI in OHCA correlated with increased STI and increased ROSC. While increased ROSC may not always equate with positive neurologic outcome, logistic regression indicated that the protocol change was independently associated with improved ROSC at emergency department arrival.

Patient, Neighborhood, and Spatial Determinants of Out-of-Hospital Cardiac Arrest Outcomes Throughout the Chain of Survival: A Community-Oriented Multilevel Analysis

Objective: Global and national trends of out-of-hospital cardiac arrest (OHCA) have been examined; however, geographic variation and socioeconomic disparities of OHCA outcomes in the community setting are less understood. We developed and tested a replicable, community-oriented assessment strategy aimed to identify spatial variations in OHCA outcomes using socioeconomic, prehospital, and in-hospital factors. Methods: Emergency medical service (EMS) records of adult, non-traumatic OHCA within Alachua County, FL (2012-2017) were retrospectively reviewed and matched to corresponding medical records at the University of Florida (UF). Incidence of cardiac arrest was geocoded to census tracts and connected to U.S. census socioeconomic attribute data. Primary outcomes include survival to emergency department (ED), hospital admission, discharge, and discharge to home. Multilevel mixed-effects logistic regression models were developed to assess sub-county geographic variance, probabilities of survival, and prehospital risk factors. Getis-Ord Gi statistic and Moran's I-test was applied to assess spatial clustering in outcome survival rates. Results: Of the 1562 OHCA cases extracted from EMS records, 1,335 (85.5%) were included with 372 transported to study site. Predicted probability of survival to ED was 57.0% (95CI: 51.3-62.3%). Of transported cases to study site ED, predicted probabilities of survival was to 41.7% (95CI: 36.1-47.6%) for hospital admission, 16.1% (95CI: 10.7-23.5%) for hospital discharge, and 7.1% (95CI: 3.7-13.3%) for home discharge. Census tracts accounted for significant variability in survival to ED (p < 0.001), discharge (p = 0.031), and home discharge outcomes (p = 0.036). There was no significant geographic variation in survival to admission outcome. Neighborhood-level factors significantly improved model fit for survival to ED, discharge, and discharge home outcomes. Multiple modifiable patient- and neighborhood-level variables of interest were identified, including rural-urban differences. Conclusion: We identified important geographic disparities that exist in OHCA outcomes at the community level. By using a replicable schematic, this variation can be explained through community-oriented modifiable socioeconomic and prehospital factors.

Identifying rural-urban differences in the predictors of emergency ambulance service demand and misuse

OBJECTIVE

This study aims to assess rural-urban differences in the predictors of emergency ambulance service (EAS) demand and misuse in New Taipei City. Identifying the predictors of EAS demand will help the EAS service managing authority in formulating focused policies to maintain service quality.

METHODS

Over 160,000 electronic EAS usage records were used with a negative binomial regression model to assess rural-urban differences in the predictors of EAS demand and misuse.

RESULTS

The factors of 1) ln-transformed population density, 2) percentage of residents who completed up to junior high school education, 3) accessibility of hospitals without an emergency room, and 4) accessibility of EAS were found to be predictors of EAS demand in rural areas, whereas only the factor of percentage of people aged above 65 was found to predict EAS demand in urban areas. For EAS misuse, only the factor of percentage of low-income households was found to be a predictor in rural areas, whereas no predictor was found in the urban areas.

CONCLUSION

Results showed that the factors predicting EAS demand and misuse in rural areas were more complicated compared to urban areas and, therefore, formulating EAS policies for rural areas based on the results of urban studies may not be appropriate.

Demographic, social, economic and geographic factors associated with long-term outcomes in a cohort of cardiac arrest survivors

BACKGROUND

Demographic, social, economic and geographic factors are associated with increased short-term mortality after cardiac arrest. We sought to determine if these factors are additionally associated with long-term outcome differences using a detailed clinical database linked to state-wide administrative data.

METHODS

We included cardiac arrest patients surviving to hospital discharge from five hospitals in the United States from 2005 to 2013, with follow-up through 2015. We obtained information on sex, race, arrest location, initial rhythm, median ZIP code income, post-arrest illness severity, cardiac catheterization, internal cardioverter-defibrillator insertion, rural residence and drive time from residence to the nearest acute care hospital. We used Cox proportional hazard models identify predictors of mortality.

RESULTS

We included 891 patients followed for 2081 patient-years. There were 340 deaths with median survival 6 years. In adjusted models we identified an interaction effect between median ZIP code income and cardiac catheterization. Among patients who had cardiac catheterization there was an attenuated benefit from cardiac catheterization at progressively lower neighborhood incomes (adjusted HR: 0.21 to 0.46 to 0.56). Residence more than 20 min from the nearest acute care hospital was associated with increased hazard of death (adjusted HR: 1.48; 95%CI: 1.35-1.62), after controlling for rural residence and residence in a Medically Underserved Area/Population. Female patients showed less benefit following ICD placement (male adjusted HR: 0.49; female adjusted HR: 0.66).

CONCLUSIONS

There are persistent long-term outcome differences in cardiac arrest survival based on sex, income, and geographic access acute care.

Effects of modifiable prehospital factors on survival after out-of-hospital cardiac arrest in rural versus urban areas

Background

The modifiable prehospital system factors, bystander cardiopulmonary resuscitation (CPR), emergency medical services (EMS), response time, and EMS physician attendance, may affect short- and long-term survival for both rural and urban out-of-hospital cardiac arrest (OHCA) patients. We studied how such factors influenced OHCA survival in a mixed urban/rural region with a high survival rate after OHCA.

Methods

We analyzed the association between modifiable prehospital factors and survival to different stages of care in 1138 medical OHCA patients from an Utstein template-based cardiac arrest registry, using Kaplan-Meier type survival curves, univariable and multivariable logistic regression and mortality hazard plots.

Results

We found a significantly higher probability for survival to hospital admission (OR: 1.84, 95% CI 1.43–2.36, p < 0.001), to hospital discharge (OR: 1.51, 95% CI 1.08–2.11, p = 0.017), and at 1 year (OR: 1.58, 95% CI 1.11–2.26, p = 0.012) in the urban group versus the rural group. In patients receiving bystander CPR before EMS arrival, the odds of survival to hospital discharge increased more than threefold (OR: 3.05, 95% CI 2.00–4.65, p < 0.001). However, bystander CPR was associated with increased patient survival to discharge only in urban areas (survival probability 0.26 with CPR vs. 0.08 without CPR, p < 0.001). EMS response time ≥ 10 min was associated with decreased survival (OR: 0.61, 95% CI 0.45–0.83, p = 0.002), however, only in urban areas (survival probability 0.15 ≥ 10 min vs. 0.25 < 10 min, p < 0.001). In patients with prehospital EMS physician attendance, no significant differences were found in survival to hospital discharge (OR: 1.37, 95% CI 0.87–2.16, p = 0.17). In rural areas, patients with EMS physician attendance had an overall better survival to hospital discharge (survival probability 0.17 with EMS physician vs. 0.05 without EMS physician, p = 0.019). Adjusted for modifiable factors, the survival differences remained.

Conclusions

Overall, OHCA survival was higher in urban compared to rural areas, and the effect of bystander CPR, EMS response time and EMS physician attendance on survival differ between urban and rural areas. The effect of modifiable factors on survival was highest in the prehospital stage of care. In patients surviving to hospital admission, there was no significant difference in in-hospital mortality or in 1 year mortality between OHCA in rural versus urban areas.

Bystander automated external defibrillator use and clinical outcomes after out-of-hospital cardiac arrest: A systematic review and meta-analysis

AIM

To systematically review studies comparing bystander automated external defibrillator (AED) use to no AED use in regard to clinical outcomes in out-of-hospital cardiac arrest (OHCA), and to provide a descriptive summary of studies on the cost-effectiveness of bystander AED use.

METHODS

We searched Medline, Embase, the Web of Science, and the Cochrane Library for randomized trials and observational studies published before June 1, 2017. Meta-analyses were performed for patients with all rhythms, shockable rhythms, and non-shockable rhythms.

RESULTS

Forty-four observational studies, 3 randomized trials, and 13 cost-effectiveness studies were included. Meta-analysis of 6 observational studies without critical risk of bias showed that bystander AED use was associated with survival to hospital discharge (all rhythms OR: 1.73 [95%CI: 1.36, 2.18], shockable rhythms OR: 1.66 [95%CI: 1.54, 1.79]) and favorable neurological outcome (all rhythms OR: 2.12 [95%CI: 1.36, 3.29], shockable rhythms OR: 2.37 [95%CI: 1.58, 3.57]). There was no association between bystander AED use and neurological outcome for non-shockable rhythms (OR: 0.76 [95%CI: 0.10, 5.87]). The Public-Access Defibrillation trial found higher survival rates when volunteers were equipped with AEDs. The other trials found no survival difference, although their study settings differed. The quality of evidence was low for randomized trials and very low for observational studies. AEDs were cost-effective in settings with high cardiac arrest incidence, with most studies reporting ratios < $100,000 per quality-adjusted life years.

CONCLUSIONS

The evidence supports the association between bystander AED use and improved clinical outcomes, although the quality of evidence was low to very low.

Spatial decision on allocating automated external defibrillators (AED) in communities by multi-criterion two-step floating catchment area (MC2SFCA)

BACKGROUND

The occurrence of out-of-hospital cardiac arrest (OHCA) is a critical life-threatening event which frequently warrants early defibrillation with an automated external defibrillator (AED). The optimization of allocating a limited number of AEDs in various types of communities is challenging. We aimed to propose a two-stage modeling framework including spatial accessibility evaluation and priority ranking to identify the highest gaps between demand and supply for allocating AEDs.

METHODS

In this study, a total of 6135 OHCA patients were defined as demand, and the existing 476 publicly available AEDs locations and 51 emergency medical service (EMS) stations were defined as supply. To identify the demand for AEDs, Bayesian spatial analysis with the integrated nested Laplace approximation (INLA) method is applied to estimate the composite spatial risks from multiple factors. The population density, proportion of elderly people, and land use classifications are identified as risk factors. Then, the multi-criterion two-step floating catchment area (MC2SFCA) method is used to measure spatial accessibility of AEDs between the spatial risks and the supply of AEDs. Priority ranking is utilized for prioritizing deployment of AEDs among communities because of limited resources.

RESULTS

Among 6135 OHCA patients, 56.85 % were older than 65 years old, and 79.04 % were in a residential area. The spatial distribution of OHCA incidents was found to be concentrated in the metropolitan area of Kaohsiung City, Taiwan. According to the posterior mean estimated by INLA, the spatial effects including population density and proportion of elderly people, and land use classifications are positively associated with the OHCA incidence. Utilizing the MC2SFCA for spatial accessibility, we found that supply of AEDs is less than demand in most areas, especially in rural areas. Under limited resources, we identify priority places for deploying AEDs based on transportation time to the nearest hospital and population size of the communities.

CONCLUSION

The proposed method will be beneficial for optimizing resource allocation while considering multiple local risks. The optimized deployment of AEDs can broaden EMS coverage and minimize the problems of the disparity in urban areas and the deficiency in rural areas.