Automated External Defibrillators Deployment Research Articles

Strategic placement of volunteer responder system defibrillators.

Volunteer responder systems (VRS) alert and guide nearby lay rescuers towards the location of an emergency. An application of such a system is to out-of-hospital cardiac arrests, where early cardiopulmonary resuscitation (CPR) and defibrillation with an automated external defibrillator (AED) are crucial for improving survival rates. However, many AEDs remain underutilized due to poor location choices, while other areas lack adequate AED coverage. In this paper, we present a comprehensive data-driven algorithmic approach to optimize deployment of (additional) public-access AEDs to be used in a VRS. Alongside a binary integer programming (BIP) formulation, we consider two heuristic methods, namely Greedy and Greedy Randomized Adaptive Search Procedure (GRASP), to solve the gradual Maximal Covering Location (MCLP) problem with partial coverage for AED deployment. We develop realistic gradually decreasing coverage functions for volunteers going on foot, by bike, or by car. A spatial probability distribution of cardiac arrest is estimated using kernel density estimation to be used as input for the models and to evaluate the solutions. We apply our approach to 29 real-world instances (municipalities) in the Netherlands. We show that GRASP can obtain near-optimal solutions for large problem instances in significantly less time than the exact method. The results indicate that relocating existing AEDs improves the weighted average coverage from 36% to 49% across all municipalities, with relative improvements ranging from 1% to 175%. For most municipalities, strategically placing 5 to 10 additional AEDs can already provide substantial improvements.

Optimizing Defibrillator Deployment with Bus-Mounted Automated External Defibrillator

Objectives Early defibrillation with an automated external defibrillator (AED) can effectively improve the survival rate of patients with out-of-hospital cardiac arrest (OHCA). Placing AEDs in public locations can reduce the defibrillation response interval from collapse to defibrillation. Most public AEDs are currently placed in a stationary way (S-AED) with limited coverage area. Bus mounted AED (B-AED) can be delivered directly to the demand point. Although B-AEDs are only available during bus operating hours, they provide greater coverage area. When the number of available AEDs is insufficient, better coverage may be achieved by placing a portion of AEDs as B-AEDs. Our purpose is developing a model to determine the optimal locations of B-AEDs and S-AEDs with a predetermined number of available AEDs. The goal is to maximize the total coverage level of all demand points. Methods We proposed a joint location model to place B-AEDs and S-AEDs based on the p-median problem (JPMP). Using data from Chang’an District, Xi’an City, China, we determined the optimal AED deployment. The performance of JPMP was compared with several other models. The coverage results of JPMP are analyzed in details, including the quantity assignment, coverage level, and geographical location of B-AEDs and S-AEDs. The impact of the bus departure intervals on coverage was also discussed. Results The use of B-AEDs results in an average 98.43% increase in the number of covered demand points, and an average 74.05% increase in total coverage level. In optimal AED deployment, B-AEDs coverage follows an inverted U-shaped curve with increasing number of available AEDs. It begins to decrease when all demand points during the operating hours are covered. With a constant number of available AEDs, the total coverage level increases and then decreases as the bus departure interval increases. The larger the number of available AEDs, the smaller the optimal departure interval. Conclusions With a given number of available AEDs, combinational deployment of B-AEDs and S-AEDs significantly improves the coverage level. B-AEDs are recommended when AEDs are insufficient. If more AEDs are available, better coverage can be obtained with reasonable location of S-AEDs and B-AEDs.

Combinations of First Responder and Drone Delivery to Achieve 5-Minute AED Deployment in OHCA

BackgroundDefibrillation in the critical first minutes of out-of-hospital cardiac arrest (OHCA) can significantly improve survival. However, timely access to automated external defibrillators (AEDs) remains a barrier. ObjectivesThe authors estimated the impact of a statewide program for drone-delivered AEDs in North Carolina integrated into emergency medical service and first responder (FR) response for OHCA. MethodsUsing Cardiac Arrest Registry to Enhance Survival registry data, we included 28,292 OHCA patients ≥18 years of age between 1 January 2013 and 31 December 2019 in 48 North Carolina counties. We estimated the improvement in response times (time from 9-1-1 call to AED arrival) achieved by 2 sequential interventions: 1) AEDs for all FRs; and 2) optimized placement of drones to maximize 5-minute AED arrival within each county. Interventions were evaluated with logistic regression models to estimate changes in initial shockable rhythm and survival. ResultsHistorical county-level median response times were 8.0 minutes (IQR: 7.0-9.0 minutes) with 16.5% of OHCAs having AED arrival times of <5 minutes (IQR: 11.2%-24.3%). Providing all FRs with AEDs improved median response to 7.0 minutes (IQR: 6.2-7.8 minutes) and increased OHCAs with <5-minute AED arrival to 22.3% (IQR: 16.4%-30.9%). Further incorporating optimized drone networks (326 drones across all 48 counties) improved median response to 4.8 minutes (IQR: 4.3-5.2 minutes) and OHCAs with <5-minute AED arrival to 56.3% (IQR: 46.9%-64.2%). Survival rates were estimated to increase by 34% for witnessed OHCAs with estimated drone arrival <5 minutes and ahead of FR and emergency medical service. ConclusionsDeployment of AEDs by FRs and optimized drone delivery can improve AED arrival times which may lead to improved clinical outcomes. Implementation studies are needed.

Abstract 421: Automated External Defibrillator Implementation Gaps in Three Non-Urban U.S. Communities

Introduction: Automated external defibrillators (AEDs) represent a crucial component of bystander response to out-of-hospital cardiac arrest (OHCA), yet epidemiologic evidence suggests that AEDs are deployed by laypersons in less than 5% of OHCA events in the US. The reasons for low utilization remain poorly characterized, especially in rural/suburban environments. We hypothesized that in these non-urban environments, layperson AED use is mostly in commercial or public locations despite most arrests occuring in private residences. Methods: We conducted an analysis of EMS-treated atraumatic OHCA events from 3 non-urban US regions (Cumberland County, PA; Jackson, TN; Forsyth County, GA), abstracted from EMS patient care reports. Data included Utstein reporting elements, arrest location type, and response intervals as calculated by dispatch and EMS arrival times. We excluded events in skilled nursing facilities and prisons. CPR and AED delivery by laypersons was measured. Results: Between 12/8/17-12/31/21, we identified 1542 adult OHCA patients with median age 66.5 y (IQR 22.5), 37% female, 18% had initial shockable rhythms, and 75% occurred in private residences. Return of spontaneous circulation was obtained in 19% of cases. Bystander CPR was performed in 23% and AEDs were deployed by laypersons in 3%. Laypersons applied AEDs in 12% of OHCA in commercial locations, 6% of OHCA in public, and 3% of OHCA in private residences. EMS response times were 4% less than 4 min, 48% 4-9 min, and 48% &gt;9 min; prevalence of AED use was indistinguishable between time intervals of EMS response. 16% OHCA victims still had initial shockable rhythms even among the &gt;9 min EMS response cases; of these, 1% received AED use from laypersons. Conclusion: In three non-urban US regions, most arrests occurred in private residences while AED use was much more likely in public or commercial locales, suggesting an important gap in AED deployment. Even in cases with prolonged response times, many patients had shockable rhythms, suggesting an important opportunity for earlier AED deployment. Future work will test whether placement of AEDs in residential areas using trained volunteer responders in these same communities will improve OHCA response and survival outcomes.

Spatiotemporal Optimization for the Placement of Automated External Defibrillators Using Mobile Phone Data.

With over 350,000 cases occurring each year, out-of-hospital cardiac arrest (OHCA) remains a severe public health concern in the United States. The correct and timely use of automated external defibrillators (AEDs) has been widely acknowledged as an effective measure to improve the survival rate of OHCA. While general guidelines have been provided by the American Heart Association (AHA) for AED deployment, the lack of detailed instructions hindered the adoption of such guidelines under dynamic scenarios with various time and space distributions. Formulating the AED deployment as a location optimization problem under budget and resource constraints, we proposed an overlayed spatio-temporal optimization (OSTO) method, which accounted for the spatiotemporal heterogeneity of potential OHCAs. To highlight the effectiveness of the proposed model, we applied the proposed method to Washington DC using user-generated anonymized mobile device location data. The results demonstrated that optimization-based planning provided an improved AED coverage level. We further evaluated the effectiveness of adding additional AEDs by analyzing the cost-coverage increment curve. In general, our framework provides a systematic approach for municipalities to integrate inclusive planning and budget-limited efficiency into their final decision-making. Given the high practicality and adaptability of the framework, the OSTO is highly amenable to different healthcare facilities' deployment tasks with flexible demand and resource restraints.

Optimal deployment of automated external defibrillators in a long and narrow environment.

Public access to automated external defibrillators (AEDs) plays a key role in increasing survival outcomes for patients with out-of-hospital cardiac arrest. Based on the concept of maximizing "rescue benefit" of AEDs, we aimed to propose a systematic methodology for optimizing the deployment of AEDs, and develop such strategies for long and narrow spaces. We classified the effective coverage of an AED in hot, warm, and cold zones. The AEDs were categorized, according to their accessibility, as fixed, summonable, or patrolling types. The overall rescue benefit of the AEDs were evaluated by the weighted size of their collective hot zones. The optimal strategies for the deployment of AEDs were derived mathematically and numerically verified by computer programs. To maximize the overall rescue benefit of the AEDs, the AEDs should avoid overlapping with each other's coverage as much as possible. Specific rules for optimally deploying one, two, or multiple AEDs, and various types of AEDs are summarized and presented. A methodology for assessing the rescue benefit of deployed AEDs was proposed, and deployment strategies for maximizing the rescue benefit of AEDs along a long, narrow, corridor-like, finite space were derived. The strategies are simple and readily implementable. Our methodology can be easily generalized to search for optimal deployment of AEDs in planar areas or three-dimensional spaces.

Pediatric and adult Out-of-Hospital cardiac arrest incidence within and near public schools in British Columbia: Missed opportunities for Systematic AED deployment strategies

BackgroundSystematic automated external defibrillator(AED) placement in schools may improve pediatric out-of-hospital cardiac arrest(OHCA) survival. To estimate their utility, we identified school-located pediatric and adult OHCAs to estimate the potential utilization of school-located AEDs. Further, we identified all OHCAs within an AED-retrievable distance of the school by walking, biking, and driving. MethodsWe used prospectively collected data from the British Columbia(BC) Cardiac Arrest Registry(2013–2020), and geo-plotted all OHCAs and schools(n = 824) in BC. We identified adult and pediatric(age < 18 years) OHCAs occurring in schools, as well as nearby OHCAs for which a school-based externally-placed AED could be retrieved by a bystander prior to emergency medical system(EMS) arrival. ResultsOf 16,409 OHCAs overall in the study period, 28.6 % occurred during school hours. There were 301 pediatric OHCAs. 5(1.7 %) occurred in schools, of whom 2(40 %) survived to hospital discharge. Among both children and adults, 28(0.17 %) occurred in schools(0.0042/school/year), of whom 21(75 %) received bystander resuscitation, 4(14 %) had a bystander AED applied, and 14(50 %) survived to hospital discharge. For each AED, an average of 0.29 OHCAs/year(95 % CI 0.21–0.37), 0.93 OHCAs/year(95 % CI 0.69–1.56) and 1.69 OHCAs/year(95 % CI 1.21–2.89) would be within the potential retrieval distance of a school-located AED by pedestrian, cyclist and automobile retrieval, respectively, using the median EMS response times. ConclusionWhile school-located OHCAs were uncommon, outcomes were favourable. 11.1% to 60.9% of all OHCAs occur within an AED-retrievable distance to a school, depending on retrieval method. Accessible external school-located AEDs may improve OHCA outcomes of school children and in the surrounding community.

Utilization and cost-effectiveness of school and community center AED deployment models in Canadian cities

BackgroundThe optimal locations and cost-effectiveness of placing automated external defibrillators (AEDs) for out-of-hospital cardiac arrest (OHCAs) in urban residential neighbourhoods are unclear. MethodsWe used prospectively collected data from 2016 to 2018 from the British Columbia OHCA Registry to examine the utilization and cost-effectiveness of hypothetical AED deployment in municipalities with a population of over 100 000. We geo-plotted OHCA events using seven hypothetical deployment models where AEDs were placed at the exteriors of public schools and community centers and fetched by bystanders. We calculated the “radius of effectiveness” around each AED within which it could be retrieved and applied to an individual prior to EMS arrival, comparing automobile and pedestrian-based retrieval modes. For each deployment model, we estimated the number of OHCAs within the “radius of effectiveness”. ResultsWe included 4017 OHCAs from ten urban municipalities. The estimated radius of effectiveness around each AED was 625 m for automobile and 240 m for pedestrian retrieval. With AEDs placed outside each school and community center, 2567 (64%) and 605 (15%) of OHCAs fell within the radii of effectiveness for automobile and pedestrian retrieval, respectively. For each AED, there was an average of 1.20–2.66 and 0.25–0.61 in-range OHCAs per year for automobile retrieval and pedestrian retrieval, respectively, depending on the deployment model. All of our proposed surpassed the cost-effectiveness threshold of 0.125 OHCA/AED/year provided > 5.3–11.6% in-range AEDs were brought-to-scene. ConclusionsThe systematic deployment of AEDs at schools and community centers in urban neighbourhoods may result in increased application and be a cost-effective public health intervention.

Mobile versus fixed automated external defibrillators (AED deployment in a geographically dispersed population: analysis of the girona territori cardioprotegit project

Abstract Introduction/Aim Public defibrillation doubles out-of-hospital cardiac arrest survival. However, the best way to provide public defibrillation coverage to geographically dispersed populations remains unknown. The aim of this study is to compare usage rates and effectivity between mobile versus fixed Automated External Defibrillators (AED). Methods This project is a prospective registry of the usage rate of public AED (542 fixed AED, 241 mobile AED) and the analysis of the electrocardiographic traces, from June 2011 until December 2019. We compared the usage rate, the proportion of shockable rhythms and defibrillation success between fixed versus mobile AED. Results Of 566 registered usages, we obtained 494 electrocardiographic traces, of which 108 (21%) were from fixed AED. The usage rate of fixed and mobile AED were 0.022use/AED-year and 0.177use/AED-year respectively. In Fixed AED group we observed a higher proportion of shockable rhythms (34.2% vs. 20.3%, p=0,01) and higher defibrillation success (79% vs. 63%, p=0,02). The proportion of patients with shockable rhythms who were transferred to a hospital were 62.1% and 50% in Fixed AED and Mobile AED group respectively (p=0,306). Conclusions In Fixed AED group we observed more shockable rhythms and higher defibrillation success rates. Mobile AED were 8 times more used. Funding Acknowledgement Type of funding sources: None.

Strategic Mapping and Optimised Allocation of Automated External Defibrillators in Urban Areas

&lt;p&gt;&lt;strong&gt;Background&lt;/strong&gt;: Out-of-hospital cardiac arrest (OHCA) is a leading cause of death and is regarded as a significant public health issue. Immediate treatment with an automated external defibrillator (AED) increases OHCA patient survival potential. For AEDs to be used and fulfil their lifesaving potential, they need to be in close proximity to the victim and accessible at the time of a cardiac arrest. The current paper sheds light upon an optimized location-allocation method achieving full coverage with immediate accessibility in an urban context given a limited number of available AEDs for deployment using GIS. The case study is the Region of Western Macedonia (RWM) in Greece for a pilot AED placement program for the Governance of RWM. The focus of the current study is the capital city of RWM, Kozani. The initial number of the defibrillators (120) that are needed to be distributed is very small and cannot cover the needs for every major city or rural area in the region. Out of the 120 AEDs, the challenge is to find the minimum required number of AEDs to allocate in the city providing full coverage and accessibility. This paper focuses only on one city, however, the same methodology was applied to allocate AEDs in the other selected cities of the region. The rural dimension and methodology are not in the scope of this paper. &lt;br&gt; &lt;strong&gt;Methods&lt;/strong&gt;: Road network data, spatio-temporal analysis of accessibility network, digital elevation model, land uses, population density, seasonal fluctuations and socio-demographic variables were used. GIS algorithms such as spatial analysis, kernel density, hot spot analysis, maximal covering location problem (MCLP) tests, proximity algorithms, buffer zoning, were a few of the tests made in order to find the most efficient positions and maximize coverage keeping in mind that access to an AED until defibrillation time must not exceed the time range of five minutes. &lt;br&gt; &lt;strong&gt;Results&lt;/strong&gt;: optimised sites and allocated AEDs in urban areas we managed to achieve full city coverage with 17 AEDs. In every part of the city, people can have access to a nearby AED with its critical radius of less than or equal to 250m achieving defibrillation in the critical period of 5 minutes. The results are promising for the establishment and expansion of optimised AED deployment in cities. &lt;br&gt; &lt;strong&gt;Conclusions&lt;/strong&gt;: The progress of the project must be monitored and there are still unresolved problems that need to be tackled to provide a robust allocation of future defibrillators. Further research to enhance our understanding on public access defibrillation and optimize the accessibility and functionality of the medical health care services is needed. A network of engaged and informed citizens ready to act is required for a successful public access defibrillation program.&lt;/p&gt;

An accessibility spatial search algorithm to optimize defibrillator deployment in indoor space

ABSTRACT Indoor space, where humans spend 80% of their lives, is subject to frequent out-of-hospital cardiac arrest (OHCA). Optimizing the spatial deployment of automated external defibrillators (AEDs) has the potential to improve OHCA survival rate. Complex indoor space is typically divided by hard barriers into multiple discrete subspaces across floors. Commonly used distance measurements, such as Euclidean distance and network distance, are unsuitable for indoor AED deployment. Instead, we propose an accessibility spatial search algorithm (ASSA) to generate accessible areas of candidate facilities, i.e. AEDs, based on an indoor space model, and optimizes the facility deployment subject to three objectives: maximizing the survival rate, maximizing total spatial coverage and maximizing backup coverage. Additionally, improved artificial bee colony (ABC) algorithm is used to solve the optimization problem. We design experiments with simulated and real-world scenarios for AED placements and evaluate the ASSA results. The experiments show that the ASSA can provide helpful guidance in optimizing AED placement in indoor space.

Monitoring chest compression rate in automated external defibrillators using the autocorrelation of the transthoracic impedance.

AimHigh-quality chest compressions is challenging for bystanders and first responders to out-of-hospital cardiac arrest (OHCA). Long compression pauses and compression rates higher than recommended are common and detrimental to survival. Our aim was to design a simple and low computational cost algorithm for feedback on compression rate using the transthoracic impedance (TI) acquired by automated external defibrillators (AEDs).MethodsECG and TI signals from AED recordings of 242 OHCA patients treated by basic life support (BLS) ambulances were retrospectively analyzed. Beginning and end of chest compression series and each individual compression were annotated. The algorithm computed a biased estimate of the autocorrelation of the TI signal in consecutive non-overlapping 2-s analysis windows to detect the presence of chest compressions and estimate compression rate.ResultsA total of 237 episodes were included in the study, with a median (IQR) duration of 10 (6–16) min. The algorithm performed with a global sensitivity in the detection of chest compressions of 98.7%, positive predictive value of 98.7%, specificity of 97.1%, and negative predictive value of 97.1% (validation subset including 207 episodes). The unsigned error in the estimation of compression rate was 1.7 (1.3–2.9) compressions per minute.ConclusionOur algorithm is accurate and robust for real-time guidance on chest compression rate using AEDs. The algorithm is simple and easy to implement with minimal software modifications. Deployment of AEDs with this capability could potentially contribute to enhancing the quality of chest compressions in the first minutes from collapse.

Development of a Novel Framework to Propose New Strategies for Automated External Defibrillators Deployment Targeting Residential Out-Of-Hospital Cardiac Arrests: Application to the City of Milan

Public Access Defibrillation (PAD) is the leading strategy in reducing time to first defibrillation in cases of Out-Of-Hospital Cardiac Arrest (OHCA), but PAD programs are underperforming considering their potentiality. Our aim was to develop an analysis and optimization framework, exploiting georeferenced information processed with Geographic Information Systems (GISs), specifically targeting residential OHCAs. The framework, based on an historical database of OHCAs, location of Automated External Defibrillators (AEDs), topographic and demographic information, proposes new strategies for AED deployment focusing on residential OHCAs, where performance assessment was evaluated using AEDs “catchment area” (area that can be reached within 6 min walk along streets). The proposed framework was applied to the city of Milan, Lombardy (Italy), considering the OHCA database of four years (2015–2018), including 8152 OHCA, of which 7179 (88.06%) occurred in residential locations. The proposed strategy for AEDs deployment resulted more effective compared to the existing distribution, with a significant improvement (from 41.77% to 73.33%) in OHCAs’ spatial coverage. Further improvements were simulated with different cost scenarios, resulting in more cost-efficient solutions. Results suggest that PAD programs, either in brand-new territories or in further improvements, could significantly benefit from a comprehensive planning, based on mathematical models for risk mapping and on geographical tools.

Abstract 148: Installation and Deployment of Automated External Defibrillators in New York State Schools

Introduction: AHA recommends that automated external defibrillators (AEDs) be made available in public areas with high likelihood of a sudden cardiac arrest (SCA). Only 18 US states have regulations requiring AEDs in schools and the legislation varies. There is no comprehensive evaluation of the epidemiology of sudden death in schools. School nurses are often the only healthcare providers within a school. New York State (NYS) enrolls almost 3.5 million students with New York City (NYC) being the largest school system in the US; legislation requires AEDs in all public but not in private schools. Purpose: Our aims were threefold: to gain epidemiologic data on SCAs in NYS schools, to evaluate the availability and utilization of AEDs, and to identify factors affecting deployment of AEDs. Methods: Electronic surveys were sent to school nurse members of the NYS Association of School Nurses and NYC school nurses. We also conducted structured interviews with a representative sample of NYS school nurses. Results: Nurses representing 750 public schools and 116 private schools responded, a response rate of 36.4%. There were 71 SCA events, with majority affecting adults on school grounds 41 (58%). AEDs were deployed in 59 (73%). Short term survival occurred in 50 (69%) with 40 (56%) returning to regular activity. While not required to have AEDs available, most private schools had them 69(60%). There were 21 (30%) SCA events in private schools with 8 (11%) occurring in private schools with no AEDs. Of these, 6 (75%) had a negative outcome. Interviews revealed that staff attitude, fear, and training adequacy were factors influencing AED utilization. Conclusions: AEDs in schools improve survival outcomes. There has been no comprehensive evaluation of SCA events in US schools and no uniformity in AED legislation among states. While focus is on students, NYS data suggests that attention should also encompass adult SCAs in schools. Comparisons of AED utilization and SCA outcomes in states with and without AED legislation will be of interest, and may have health policy implications.

Public location and survival from out-of-hospital cardiac arrest in the public-access defibrillation era in Japan

BackgroundThe use of public-access automated external defibrillators (AEDs) has become common in Japan. To provide a strategy for appropriate public-access AED deployment, we assessed public-access defibrillation (PAD) by laypersons and the outcomes following out-of-hospital cardiac arrest (OHCA) among adult patients by location of arrest. MethodsFrom a nationwide, prospective, population-based registry of patients after OHCA in Japan, we enrolled adult patients with bystander-witnessed OHCA of medical origin in public locations between 2013 and 2015. The primary outcome measure was one-month favorable neurological outcome defined by cerebral performance category 1 or 2. Factors associated with favorable neurological outcome after ventricular fibrillation (VF) were assessed by multivariable logistic regression analysis. ResultsA total of 20,970 adult bystander-witnessed OHCAs of medical origin occurred in public locations. Of those, the proportions of PAD by location were: 13.1% (757/5761) in public areas, 15.9% (333/2089) at workplaces, 26.0% (544/2095) in recreation/sports areas, 36.1% (112/310) in educational institutions, and 5.8% (241/4151) on streets/highways. In a multivariable analysis of VF arrests, both bystander cardiopulmonary resuscitation [adjusted odds ratio (AOR), 1.78; 95% confidence interval (CI), 1.54–2.07] and PAD (AOR, 2.33; 95% CI, 2.05–2.66), and emergency medical service (EMS) response time (AOR, 0.89; 95% CI, 0.87–0.90) were associated with improved outcomes. Earlier PAD initiated by bystanders before EMS arrival was also associated with better outcomes after OHCA. ConclusionsIn Japan, where public-access AEDs are well-disseminated, the PAD program worked effectively for adult OHCA of medical origin occurring in public locations. Notably, the proportions of PAD differed substantially according to specific public locations.

Simulating Public Buses as a Mobile Platform for Deployment of Publicly Accessible Automated External Defibrillators

Introduction: Public access defibrillation (PAD) programs seek to optimize locations of automated external defibrillators (AEDs) to minimize the time from out-of-hospital cardiac arrest (OHCA) recognition to defibrillation. Most PAD programs have focused on static AED (S-AED) locations in high traffic areas; pervasive electronic data infrastructure incorporating real-time geospatial data opens the possibility for AED deployment on mobile infrastructure for retrieval by nearby non-passengers. Performance characteristics of such systems are not known. Hypothesis: We hypothesized that publicly accessible AEDs located on buses would increase publicly accessible AED coverage and reduce AED retrieval time relative to statically located AEDs. Methods: S-AED sites in Pittsburgh, PA were identified and consolidated to 1 AED per building for analysis (n = 582). Public bus routes and schedules were obtained from the Port Authority of Allegheny County. OHCA locations and times were obtained from the Pittsburgh site of the Resuscitation Outcomes Consortium. Two simulations were conducted to assess the characteristics and impact of AEDs located on buses. In Simulation #1, geographic coverage area of AEDs located on buses (B-AEDs) was estimated using a 1/8th mile (201 m) retrieval radius during weekday, Saturday and Sunday periods. Cumulative geographic coverage across each period of the week was compared to S-AED coverage and the added coverage provided by B-AEDs was calculated. In Simulation #2, spatiotemporal event coverage was estimated for historical OHCA events, assuming constraints designed to reflect real world AED retrieval scenarios. Event coverage and AED retrieval time were compared between B-AEDs and S-AEDs across periods of the week and residential/nonresidential spatial areas. Results: Cumulative geographic coverage by S-AEDs was 23% across all periods, assuming uniform access hours. B-AEDs alone versus B-AEDs + S-AEDs covered 20% vs. 34% (weekday), 14% + 30% (Saturday), and 10% + 28% (Sunday). There was no statistically significant difference in 3-minute historical AED accessibility between only B-AEDs and only S-AEDs in standalone deployments (12% vs. 14%). However, when allowing for retrieval of either type of AED in the same scenario, event coverage was improved to 22% (p < 0.001). Conclusion: Deployment of B-AEDs may improve AED coverage but not as a standalone deployment strategy.

Abstract 185: Optimization of Public Access Defibrillators Compared to Actual Deployment: An In Silico Trial

Introduction: Unguided placement of automated external defibrillators (AEDs) often leads to placements in low risk areas and locations with limited temporal availability. Mathematical optimization may improve AED placements and increase AED use in out-of-hospital cardiac arrests (OHCAs). Aim: To conduct the first in silico public AED location trial to determine whether optimization models (interventions) trained on historical OHCA data will recommend AED locations that significantly improve OHCA coverage on prospective OHCAs, compared to locations of actually deployed AEDs (control). Methods: We identified all public OHCAs of presumed cardiac cause (1994-2016) and already deployed AEDs (2007-2016) in Copenhagen, Denmark. We computed the number of OHCAs that occurred within 100m of a temporally available AED after it was deployed (“OHCA coverage”). We then divided 2007-2016 into 30-day intervals and determined the number of AEDs deployed in each interval. Using previously validated optimization models, we determined an equal number of optimal AED locations in each time interval, either indoor locations with actual availability (intervention #1) or outdoor locations with 24/7 availability (intervention #2). OHCA coverage was calculated for the interventions similarly to the already deployed AEDs. Finally, we repeated the analysis 25 times to evaluate sensitivity and generate confidence intervals, by randomizing the location and time of the OHCAs. Results: A total of 2,149 public OHCAs (744 between 2007-2016) and 1,573 registered AEDs were identified. OHCA coverage of actually deployed AEDs was 22.3% (166 of 744 OHCAs). For optimally located indoor AEDs, mean OHCA coverage was 32.6% (mean: 242.5 OHCAs; 95% CI: 239.7 - 245.3). For optimally located outdoor AEDs, mean OHCA coverage was 43.9% (mean: 326.6 OHCAs; 95% CI: 324.0 - 329.2). Conclusions: Optimizing AED locations in a real-time deployment approach mimicking the time horizon of actual AED deployment in Copenhagen, Denmark results in significantly higher OHCA coverage compared to the actual AEDs deployed. Between the two interventions, optimal locations that are 24/7 available significantly outperform optimal indoor locations with more limited temporal availability.

Spatiotemporal AED optimization is generalizable

AimsMathematical optimization of automated external defibrillator (AED) placements has the potential to improve out-of-hospital cardiac arrest (OHCA) coverage and reverse the negative effects of limited AED accessibility. However, the generalizability of optimization approaches has not yet been investigated. Our goal is to examine the performance and generalizability of a spatiotemporal AED placement optimization methodology, initially developed for Toronto, Canada, to the new study setting of Copenhagen, Denmark. MethodsWe identified all public OHCAs (1994–2016) and all registered AEDs (2016) in Copenhagen, Denmark. We calculated the coverage loss associated with limited temporal accessibility of registered AEDs, and used a spatiotemporal optimization model to quantify the potential coverage gain of optimized AED deployment. Coverage gain of spatiotemporal deployment over a spatial-only solution was quantified through 10-fold cross-validation. Statistical testing was performed using χ2 and McNemar’s tests. ResultsWe found 2149 public OHCAs and 1573 registered AED locations. Coverage loss was found to be 24.4% (1104 OHCAs covered under assumed 24/7 coverage, and 835 OHCAs under actual coverage). The coverage gain from using the spatiotemporal model over a spatial-only approach was 15.3%. Temporal and geographical trends in coverage gain were similar to Toronto. ConclusionsWithout modification, a previously developed spatiotemporal AED optimization approach was applied to Copenhagen, resulting in similar OHCA coverage findings as Toronto, despite large geographic and cultural differences between the two cities. In addition to reinforcing the importance of temporal accessibility of AEDs, these similarities demonstrate the generalizability of optimization approaches to improve AED placement and accessibility.

Robust Defibrillator Deployment Under Cardiac Arrest Location Uncertainty via Row-and-Column Generation

Sudden cardiac arrest is a significant public health concern. Successful treatment of cardiac arrest is extremely time sensitive, and use of an automated external defibrillator (AED) where possible significantly increases the probability of survival. Placement of AEDs in public locations can improve survival by enabling bystanders to treat victims of cardiac arrest prior to the arrival of emergency medical responders, thus shortening the time between collapse and treatment. However, since the exact locations of future cardiac arrests cannot be known a priori, AEDs must be placed strategically in public locations to ensure their accessibility in the event of an out-of-hospital cardiac arrest emergency. In this paper, we propose a data-driven optimization model for deploying AEDs in public spaces while accounting for uncertainty in future cardiac arrest locations. Our approach involves discretizing a continuous service area into a large set of scenarios, where the probability of cardiac arrest at each location is itself uncertain. We model uncertainty in the spatial risk of cardiac arrest using a polyhedral uncertainty set that we calibrate using historical cardiac arrest data. We propose a solution technique based on row-and-column generation that exploits the structure of the uncertainty set, allowing the algorithm to scale gracefully with the total number of scenarios. Using real cardiac arrest data from the City of Toronto, we conduct an extensive numerical study on AED deployment public locations. We find that hedging against cardiac arrest location uncertainty can produce AED deployments that outperform an intuitive sample average approximation by 9%–15% and cuts the performance gap with respect to an ex post model by half. Our findings suggest that accounting for cardiac arrest location uncertainty can lead to improved accessibility of AEDs during cardiac arrest emergencies and the potential for improved survival outcomes.The electronic companion is available at https://doi.org/10.1287/opre.2017.1660 .

Optimizing the Deployment of Public Access Defibrillators

Out-of-hospital cardiac arrest is a significant public health issue, and treatment, namely, cardiopulmonary resuscitation and defibrillation, is very time sensitive. Public access defibrillation programs, which deploy automated external defibrillators (AEDs) for bystander use in an emergency, reduce the time to defibrillation and improve survival rates. In this paper, we develop models to guide the deployment of public AEDs. Our models generalize existing location models and incorporate differences in bystander behavior. We formulate three mixed integer nonlinear models and derive equivalent integer linear reformulations or easily computable bounds. We use kernel density estimation to derive a spatial probability distribution of cardiac arrests that is used for optimization and model evaluation. Using data from Toronto, Canada, we show that optimizing AED deployment outperforms the existing approach by 40% in coverage, and substantial gains can be achieved through relocating existing AEDs. Our results suggest that improvements in survival and cost-effectiveness are possible with optimization. This paper was accepted by Dimitris Bertsimas, optimization.