Conflict of Interest Declaration
The ILCOR Continuous Evidence Evaluation process is guided by a rigorous ILCOR Conflict of Interest policy. The following Task Force members and other authors were recused from the discussion as they declared a conflict of interest: None Applicable
The following Task Force members and other authors declared an intellectual conflict of interest and this was acknowledged and managed by the Task Force Chairs and Conflict of Interest committees: None Applicable.
Task Force Synthesis Citation
Kollander L, Folke F, Bray J on behalf of the International Liaison Committee on Resuscitation Basic Life Support Task Force.
Drone AEDs Task Force Synthesis of a Scoping Scoping Review [Internet] Brussels, Belgium: International Liaison Committee on Resuscitation (ILCOR) Basci Life Support Task Force, 2023 Jan 9th. Available from: http://ilcor.org
Methodological Preamble and Link to Published Scoping Review
The continuous evidence evaluation process started with a scoping review of AED-delivering drones for out-of-hospital cardiac arrest conducted by the ILCOR BLS Task Force Scoping Review team. Evidence for adult and pediatric literature was sought and considered by the Basic Life Support Adult Task Force.
Kollander L, Folke F. Drone AEDs: A scoping review.
The PICOST (Population, Intervention, Comparator, Outcome, Study Designs and Timeframe)
Population: Adults and children in Out-of-Hospital Cardiac Arrests (OHCA).
Intervention: Drone delivered automated external defibrillators (AEDs).
Comparators: Standard EMS Response times (or time for EMS-delivered AED), AEDs delivered by random bystanders or activated volunteer responders.
Outcomes: Real-world/estimated feasibility, time gain of drone-delivered AEDs (compared to standard EMS delivery), predicted survival, predicted quality-adjusted life years gained, cost-effectiveness, calculated proportion of defibrillation and survival compared to cases where AEDs are brought to the OHCA scene by standard means.
Study Designs: Theoretical feasibility studies, prediction models (e.g., spatial analysis, Geographical Information System (GIS) -models), observational studies, simulation studies, qualitative studies of human-drone interaction, and real-world feasibility studies. All years and all English languages studies were included; unpublished studies (e.g., conference abstracts, trial protocols) were excluded.
Timeframe: Literature search updated to 1 December, 2022.
Developed in liaison with Connie Skrubbeltrang, Information Specialist at Aalborg University Hospital, Denmark. Articles for review were obtained by searching PubMed, EMBASE and Cochrane, for all entries from database inception to December 1, 2022.
Key terms are “drone” OR "Unmanned Aerial Vehicle*" AND (“out-of-hospital cardiac arrest (OHCA)” OR “automated external defibrillator (AED)”). All terms are included with synonyms and MESH terms.
Searches run: April 12, 2022
Updated search: December 1, 2022
Medline/Pubmed updated search:
((Drone[Text Word] OR drones[Text Word] OR "Unmanned Aerial Vehicle*"[Text Word] OR UAV[Text Word] OR PRAS[Text Word] OR "unmanned aircraft*"[Text Word]) OR (UAS[Text Word])) AND (((OHCA[Text Word]) OR ("out of hospital cardiac arrest"[Text Word])) OR ((("Defibrillators"[Mesh]) OR ("Electric Countershock"[Mesh])) OR (Defibrillat*[Text Word] OR AED[Text Word] OR aeds[Text Word] OR "aed’s"[Text Word])))
Inclusion and Exclusion criteria
Inclusion: Drone delivery of AEDs: mathematical prediction models, simulation studies/test flights, qualitative studies on human-drone interaction and real-world studies. Gray literature in the format of Editorials and Letters were included.
Exclusion: Use of medical drones for other purposes than AED delivery. Gray literature in the format of abstracts. Previous reviews were included as background knowledge, but not included in the final review.
Data tables attached
Task Force Insights
1. Why this topic was reviewed.
This topic was chosen for scoping review by the BLS Task Force because of increasing worldwide interest in drone-delivered AEDs for OHCA. No previous ILCOR review/scoping review existed to give an overview and status of this emerging field.
2. Narrative summary of evidence identified
- The literature search identified 96 full-text articles (after removal of duplicates). After screening titles and abstracts, 28 studies were identified for full-text review (Bauer 2021 e04379, Baumgarten 2022 139, Bogle 2019 204, Boutilier 2017 2454, Cheskes 2020 e016687, Choi 2021 4195, Chu 2021 127, Claesson 2016 124, Claesson 2017 2332, Derkenne, 2021 259, Kim 2021 e11761, Lancaster 2020 38, Lancaster 2021 100153, Leung 2022 24, Mackle 2020 1900410, Pulver 2016 378, Pulver 2018 9, Rees 2021 e0259555, Ryan 2021 532, Rosamond 2020 1186, Röper 2022, Sanfridsson 2019 40, Schierbeck 2022 1953, Schierbeck 2022 1478, Schierbeck 2021 136, Sedig 2020 100033, Wankmüller 2020 785, Zègre-Hemsey 2020 83).
- 28 studies were distributed into three main categories:
- Computer/prediction models: 17 studies use different strategies to localize optimal sites for placement of AED-drone bases and estimate time gain compared to EMS response time (Bauer 2021 e04379, Bogle 2019 204, Boutilier 2017 2454, Choi 2021 4195, Chu 2021 127, Claesson 2016 124, Derkenne, 2021 259, Lancaster 2020 38, Lancaster 2021 100153, Leung 2022 24, Mackle 2020 1900410, Pulver 2016 378, Pulver 2018 9, Röper 2022, Ryan 2021 532, Schierbeck 2021 136, Wankmüller 2020 785). In these studies, the data input varied according to geographical areas, quality and accessibility of historical OHCA data, drone type and input of diverse drone-flight details, existing EMS system, and volunteer responder programs. Three studies evaluated a drone being occupied by multiple incidents happening at the same time (Boutilier 2017 2454, Derkenne, 2021 259, Pulver 2018 9). Three studies included topography in their calculations (Choi 2021 4195, Leung 2022 24, Wankmüller 2020 785). Two studies included weather, visibility, and time of day in their prediction models (Choi 2021 4195, Derkenne, 2021 259,). One study (Wankmüller ) discussed possible obstacles in alpine terrain (e.g., slow vertical speeds of drones, missing power supply at shelter huts, more difficult weather conditions etc.)
- Test flights/simulation studies and qualitative analysis: 9 studies (Baumgarten 2022 139, Cheskes 2020 e016687, Claesson 2017 2332, Kim 2021 e11761, Rees 2021 e0259555, Rosamond 2020 1186, Sanfridsson 2019 40, Sedig 2020 100033, Zègre-Hemsey 2020 83). In these studies, the specific aims, geography and testing area of the studies differed. One simulation study compared drone-delivery of an AED to a ground search of the nearest publicly accessible AED and found the drone-delivered AED to arrive first in 4/5 scenarios (Rosamond et al). One simulation study found increased hands-off time interval when having a single bystander to perform CPR and fetch and attach the drone-delivered AED (Sanfridsson 2019 40).
- Real-life drone AED-delivery for OHCA: 2 studies (Schierbeck 2022 1953, Schierbeck 2022 1478) One was a feasibility study (Schierbeck 2022 1478): Of 14 suspected OHCAs eligible for drone take-off, 12 drone flights were performed, and successful AED delivery was achieved in 11/12 suspected OHCA incidents (92%). The drone AED arrived before the ambulance in 64% of cases. The success rate was 90% among 61 additional test flights with AED delivery. The other study was a case report with the first-ever person reported to survive after OHCA and defibrillation with a drone-delivered AED (Schierbeck 2022 1953).
- All included studies (from all three categories) found drone delivery of AEDs to be feasible.
- 27/28 included studies that estimated or predicted a time gain compared to different standard EMS AED-delivering systems (Bauer 2021 e04379, Baumgarten 2022 139, Bogle 2019 204, Boutilier 2017 2454, Cheskes 2020 e016687, Choi 2021 4195, Chu 2021 127, Claesson 2016 124, Claesson 2017 2332, Derkenne, 2021 259, Kim 2021 e11761, Lancaster 2020 38, Lancaster 2021 100153, Leung 2022 24, Mackle 2020 1900410, Pulver 2016 378, Pulver 2018 9, Rees 2021 e0259555, Ryan 2021 532, Rosamond 2020 1186, Röper 2022, Sanfridsson 2019 40, Schierbeck 2022 1953, Schierbeck 2022 1478, Schierbeck 2021 136, Wankmüller 2020 785, Zègre-Hemsey 2020 83).
- One study assessed the qualitative input to gain insights into the public perception of using drones to deliver AEDs to OHCA (Sedig 2020 100033). This study highlights the importance of assessing a community’s cardiac arrest literacy levels, information needs, and readiness for innovation to ensure successful uptake in smaller communities.
- Three studies specifically estimated increased survival from different drone setups (Bauer 2021 e04379, Bogle 2019 204, Lancaster 2021 100153).
- Five studies evaluated the cost-effectiveness (Bauer 2021 e04379, Bogle 2019 204, Lancaster 2021 100153, Pulver 2018 9, Röper 2022). All five studies predicted the cost-effectiveness of a drone AED system to supplement existing systems to secure early defibrillation.
- Five simulation studies qualitatively evaluated the human-drone interaction and reported overall positive feedback from participants regarding the use of drones in OHCA (Baumgarten 2022 139, Kim 2021 e11761, Rosamond 2020 1186, Sanfridsson 2019 40, Zègre-Hemsey 2020 83).
3. Narrative Reporting of the task force discussions
- A limited evidence base was identified, with most studies focused on theoretical drone base placement and estimated AED drone delivery times compared to standard EMS times. In contrast, only one pilot and one case study reported on the drone delivery of AEDs to real-world OHCAs.
- Air Traffic Control and regulatory aspects concerning SORA (Specific Operations Risk Assessment) are the major obstacles towards the widespread use of AED-delivering drones beyond line of sight.
- The heterogeneity of the studies and the lack of data on patient outcomes do not support the need for a specific systematic review or a meta-analysis at this time.
Future studies should examine the delivery AEDs to real-world OHCA patients and document the impact on patient outcomes.
No RCTs were identified concerning AED delivery by drones.
Bauer J, Moormann D, Strametz R, Groneberg DA. Development of unmanned aerial vehicle (UAV) networks delivering early defibrillation for out-of-hospital cardiac arrests (OHCA) in areas lacking timely access to emergency medical services (EMS) in Germany: a comparative economic study. BMJ Open. 2021;11(1):e04379
Baumgarten MC, Röper J, Hahnenkamp K, Thies KC. Drones Delivering Automated External Defibrillators-Integrating Unmanned Aerial Systems into the Chain of Survival: A Simulation Study in Rural Germany. Resuscitation. 2022;172:139-145.
Bogle B, Rosamond WD, Snyder KT, Zègre-Hemsey JK. The Case for Drone-assisted Emergency Response to Cardiac Arrest: An Optimized Statewide Deployment Approach. N C Med J. 2019;80(4):204-212
Boutilier JJ, Brooks SC, Janmohamed A, Byers A, Buick JE, Zhan C, Schoellig AP, Cheskes S, Morrison LJ, Chan TCY, on behalf of the Rescu Epistry Investigators Optimizing a drone network to deliver automated external defibrillators. Circulation. 2017;135(25):2454-2465.
Cheskes S, Mcleod S, Nolan M, Snobelen P, Vallencourt C, Brooks S, Dainty K N, Chan TCY, Drennan IR. Improving Access to Automated External Defibrillators in Rural and Remote Settings: A Drone Delivery Feasibility Study. J Am Heart Assoc. 2020;9(14):e016687.
Choi DS, Hong KJ, Shin SD, Lee CG, Kim TH, Cho Y, Song KJ, Ro YS, Park JH, Kim KH. Effect of topography and weather on delivery of automatic electrical defibrillator by drone for out-of-hospital cardiac arrest. Sci Rep. 2021;11(1):24195.
Chu J, Leung KHB, Snobelen P, Nevils G, Drennan JR, Cheskes S, Chan TCY. Machine learning-based dispatch of drone-delivered defibrillators for out-of-hospital cardiac arrest. Resuscitation. 2021;162:120-127.
Claesson A, Fredman D, Svensson L, Ringh M, Hollenberg J, Nordberg P, Rosenqvist M, Djarv T, Österberg S, Lennartsson J, Ban Y. Unmanned aerial vehicles (drones) in outof-hospital-cardiac-arrest. Scand J Trauma Resusc Emerg Med. 2016;24(1):124
Claesson A, Bäckman A, Ringh M, Svensson L, Nordberg P, Djärv T, Hollenberg J. Time to Delivery of an Automated External Defibrillator Using a Drone for Simulated Out-of-Hospital Cardiac Arrests vs Emergency Medical Services. JAMA 2017;317(22):2332-2334.
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Kim HJ, Kim JH, Park D. Comparing audio- and video-delivered instructions in dispatcher-assisted cardiopulmonary resuscitation with drone-delivered automatic external defibrillator: a mixed methods simulation study. South Korea. PeerJ. 2021;9:e11761.
Lancaster G, Hermann JW. Simulating cardiac arrest events to evaluate novel emergency response systems. IISE Trans. Health Syst. Eng. 2020;11:38–50.
Lancaster G, Hermann JW. Computer simulation of the effectiveness of novel cardiac arrest response systems. Resus Plus. 2021;7:100153.
Leung KHB, Grunau B, Al Assil R, Heidet M, Liang LD, Deakin J, Christenson J, Cheskes S, Chan TCY. Incremental gains in response time with varying base location types for drone-delivered automated external defibrillators. Resuscitation.2022;174:24-30.
Mackle C, Bond R, Torney H, Mcbride R, Mclaughlin J, Finlay D, Biglarbeigi P, Brisk R, Harvey A, Mceneaney D. A Data-Driven Simulator for the Strategic Positioning of Aerial Ambulance Drones Reaching Out-of-Hospital Cardiac Arrests: A Genetic Algorithmic Approach. IEEE J Transl Eng Health Med. 2020;8:1900410
Pulver A, Wei R, Mann C. Locating AED Enabled Medical Drones to Enhance Cardiac Arrest Response Times. Prehosp Emerg Care. 2016;20(3):378-89.
Pulver A, Wei R. Optimizing the spatial location of medical drones. Applied Geography. 2018; 20:9-16.
Rees N, Howitt J, Breyley N, Geoghegan P, Powel C. A simulation study of drone delivery of Automated External Defibrillator (AED) in Out of Hospital Cardiac Arrest (OHCA) in the UK. PLoS One. 2021;16(11):e0259555.
Ryan JP. The feasibility of medical unmanned aerial systems in suburban areas. Am J Emerg Med. 2021 Dec;50:532-545.
Rosamond WD, Johnson AM, Bogle B, Arnold E, Cunningham CJ, Picinich M, Williams BM, Zègre-Hemsey JK. Drone Delivery of an Automated External Defibrillator. N Engl J Med. 2020;383(12):1186-1188.
Röper JWA, Fischer K, Baumgarten MC , Thies KC, Hahnenkamp K, Flessa S. Can drones save lives and money? An economic evaluation of airborne delivery of automated external defibrillators. Eur J Health Econ.2022;online ahead of print (https://doi.org/10.1007/s10198...).
Sanfridsson J, Sparrevik J, Hollenberg J, Nordberg P, Djärv T, Ringh M, Svensson L,Forsberg S, Nord A, Andersson-Hagiwara M, Claesson A. Drone delivery of an automated external defibrillator – a mixed method simulation study of bystander experience. Scand J Trauma Resusc Emerg Med. 2019;27(1):40
Schierbeck S, Svensson L, Claesson A. Use of a Drone-Delivered Automated External Defibrillator in an Out-of-Hospital Cardiac Arrest. N Engl J Med. 2022;386(20):1953-1954.
Schierbeck S, Hollenberg J, Nord A, Svensson L, Nordberg P, Ringh M, Forsberg S, Lundgren P, Axelsson C, Claesson A. Automated external defibrillators delivered by drones to patients with suspected out-of-hospital cardiac arrest. Eur Heart J. 2022;43(15):1478-1487
Schierbeck S, Nord A, Svensson L, Rawshani A, Hollenberg J, Ringh M, Forsberg S, Nordberg P, Hilding F, Claesson A. National coverage of out-of-hospital cardiac arrests using automated external defibrillator-equipped drones — A geographical information system analysis. Resuscitation.2021;163:136-145
Sedig K, Seaton MB, Drennan IR, Cheskes S, Dainty KN. “Drones are a great idea! What is an AED?” novel insights from a qualitative study on public perception of using drones to deliver automatic external defibrillators. Resus Plus 2020;4:100033.
Wankmüller C, Truden C, Korzen C, Hungerländer P, Kolesnik E, Reiner G. Optimal allocation of defbrillator drones in mountainous regions. OR Spectrum 2020;42;785–814.
Zègre-Hemsey JK, Grewe ME, Johnson AM, Arnold E, Cunningham CJ, Bogle B M, Rosamond W. Delivery of Automated External Defibrillators via Drones in Simulated Cardiac Arrest: Users' Experiences and the Human-Drone Interaction. Resuscitation. 2020;157:83-88.