Association Between Number of Volunteer Responders and Interventions Before Ambulance Arrival for Cardiac Arrest

Gregers, Mads Christian Tofte; Andelius, Linn; Kjoelbye, Julie Samsoee; Grabmayr, Anne Juul; Jakobsen, Louise Kollander; Christensen, Nanna Bo; Kragh, Astrid Rolin; Hansen, Carolina Malta; Lyngby, Rasmus Meyer; Væggemose, Ulla; Torp‐Pedersen, Christian; Ersbøll, Annette Kjær; Folke, Fredrik

doi:10.1016/j.jacc.2022.11.047

Cited by 19 publications

(9 citation statements)

References 32 publications

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“…The demonstrated importance of considering multiple factors in volunteer demographics and behavioral characteristics and the insights from the models we have tested are applicable wherever volunteer dispatch optimization is important. Such challenges are found in areas as diverse as food rescue operations [ 53 ], OHCA response [ 54 , 56 ], and mass casualty events [ 57 ]. Following our approach, these domains and more may find value in testing different sets of demographic and behavioral factors.…”

Section: Discussionmentioning

confidence: 99%

“…The challenge of improving volunteer dispatch speed and response rates is recognized in fields ranging from food rescue operations [ 53 ] to OHCA response in which the optimization of the responder network is now taking center stage [ 54 , 55 ]. Studies such as the one by Gregers et al [ 56 ] have attempted to determine the optimal number of responders to dispatch, yet such studies base response viability solely on current ETA with no consideration of responder history or other characteristics that could improve responsiveness. Currently used dispatch algorithms that select volunteers based on their ETA without considering the likelihood of response may be suboptimal owing to a large percentage of alerts wasted on VFRs with shorter ETA but a low likelihood of response.…”

Section: Introductionmentioning

confidence: 99%

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Predictive Dispatch of Volunteer First Responders: Algorithm Development and Validation

Khalemsky,

Lankenau

et al. 2023

JMIR Mhealth Uhealth

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Background Smartphone-based emergency response apps are increasingly being used to identify and dispatch volunteer first responders (VFRs) to medical emergencies to provide faster first aid, which is associated with better prognoses. Volunteers’ availability and willingness to respond are uncertain, leading in recent studies to response rates of 17% to 47%. Dispatch algorithms that select volunteers based on their estimated time of arrival (ETA) without considering the likelihood of response may be suboptimal due to a large percentage of alerts wasted on VFRs with shorter ETA but a low likelihood of response, resulting in delays until a volunteer who will actually respond can be dispatched. Objective This study aims to improve the decision-making process of human emergency medical services dispatchers and autonomous dispatch algorithms by presenting a novel approach for predicting whether a VFR will respond to or ignore a given alert. Methods We developed and compared 4 analytical models to predict VFRs’ response behaviors based on emergency event characteristics, volunteers’ demographic data and previous experience, and condition-specific parameters. We tested these 4 models using 4 different algorithms applied on actual demographic and response data from a 12-month study of 112 VFRs who received 993 alerts to respond to 188 opioid overdose emergencies. Model 4 used an additional dynamically updated synthetic dichotomous variable, frequent responder, which reflects the responder’s previous behavior. Results The highest accuracy (260/329, 79.1%) of prediction that a VFR will ignore an alert was achieved by 2 models that used events data, VFRs’ demographic data, and their previous response experience, with slightly better overall accuracy (248/329, 75.4%) for model 4, which used the frequent responder indicator. Another model that used events data and VFRs’ previous experience but did not use demographic data provided a high-accuracy prediction (277/329, 84.2%) of ignored alerts but a low-accuracy prediction (153/329, 46.5%) of responded alerts. The accuracy of the model that used events data only was unacceptably low. The J48 decision tree algorithm provided the best accuracy. Conclusions VFR dispatch has evolved in the last decades, thanks to technological advances and a better understanding of VFR management. The dispatch of substitute responders is a common approach in VFR systems. Predicting the response behavior of candidate responders in advance of dispatch can allow any VFR system to choose the best possible response candidates based not only on ETA but also on the probability of actual response. The integration of the probability to respond into the dispatch algorithm constitutes a new generation of individual dispatch, making this one of the first studies to harness the power of predictive analytics for VFR dispatch. Our findings can help VFR network administrators in their continual efforts to improve the response times of their networks and to save lives.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Predictive Dispatch of Volunteer First Responders: Algorithm Development and Validation

Khalemsky,

Lankenau

et al. 2023

JMIR Mhealth Uhealth

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“…Gregers et al presented data from Denmark where at least one volunteer responder arrived before the ambulance in 58% of all included cardiac arrests. The results suggested that arrival of any volunteer responder increased the number of patients receiving bystander CPR, and that there was a positive gradient with the number of volunteers on scene and the odds ratio of bystander defibrillation [23]. A study from the United Kingdom found that when a volunteer accepts an alert in the Good Sam application, the survival to hospital discharge was higher compared to OHCAs where the volunteers did not accept the call [24].…”

Section: Volunteer Respondersmentioning

confidence: 99%

Automated external defibrillators and the link to first responder systems

Jonsson,

Berglund,

Müller

2023

Current Opinion in Critical Care

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Purpose of review Automated external defibrillators are a very effective treatment to convert ventricular fibrillation (VF) in out-of-hospital cardiac arrest. The purpose of this paper is to review recent publications related to automated external defibrillators (AEDs). Recent findings Much of the recent research focus on ways to utilize publicly available AEDs included in different national/regional registers. More and more research present positive associations between engaging volunteers to increase the use of AEDs. There are only a few recent studies focusing on professional first responders such as fire fighters/police with mixed results. The use of unmanned aerial vehicles (drones) lacks clinical data and is therefore difficult to evaluate. On-site use of AED shows high survival rates but suffers from low incidence of out-of-hospital cardiac arrest (OHCA). Summary The use of public AEDs in OHCA are still low. Systems focusing on engaging volunteers in the cardiac arrest response have shown to be associated with higher AED usage. Dispatching drones equipped with AEDs is promising, but research lacks clinical data. On-site defibrillation is associated with high survival rates but is not available for most cardiac arrests.

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“… 62 Volunteer responder (VR) programs, where dispatched laypersons arrive to a patient prior to EMS and initiate early CPR and defibrillation, have been implemented by EMS agencies around the world. 63 , 64 However, these programs vary widely by locations, level of participation, and the amount of training and have not yet been studied in the context of AED-drone integration. Currently, VR programs are not integrated with the drone programs in Sweden, US, nor Canada.…”

Section: Challenges To Progressmentioning

confidence: 99%

Challenges & barriers for real-time integration of drones in emergency cardiac care: Lessons from the United States, Sweden, & Canada

Zègre-Hemsey,

Cheskes,

Johnson

et al. 2024

Resuscitation Plus

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Association Between Number of Volunteer Responders and Interventions Before Ambulance Arrival for Cardiac Arrest

Cited by 19 publications

References 32 publications

Predictive Dispatch of Volunteer First Responders: Algorithm Development and Validation

Predictive Dispatch of Volunteer First Responders: Algorithm Development and Validation

Automated external defibrillators and the link to first responder systems

Challenges & barriers for real-time integration of drones in emergency cardiac care: Lessons from the United States, Sweden, & Canada

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