Evidence map›Paper›PMID 34815722›Full record

ReviewOpen access emergency medicine : OAEM2021

Impact of Using Drones in Emergency Medicine: What Does the Future Hold?

Anna M Johnson, Christopher J Cunningham, Evan Arnold, Wayne D Rosamond, Jessica K Zègre-Hemsey

Abstract readReview
In one paragraph

Review in Open access emergency medicine : OAEM, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

  1. Review
  2. Article
  3. Observational
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Lessons Learned from Natural Disasters around Digital Health Technologies and Delivering Quality Healthcare.International journal of environmental research and public health · 2023
    Review
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Anna M JohnsonDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.ORCID 0000-0002-4914-8001
Christopher J CunninghamDepartment of Emergency Medicine, Henry Ford Hospital, Detroit, MI, USA.ORCID 0000-0001-6889-9962
Evan ArnoldInstitute for Transportation Research and Education, North Carolina State University, Raleigh, NC, USA.ORCID 0000-0002-7725-9067
Wayne D RosamondDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.ORCID 0000-0001-5271-074X
Jessica K Zègre-HemseySchool of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.ORCID 0000-0002-5650-0464

Funding

Re-Entry Supplement: Investigation of Oral Microbial Enzymes for the Detection and Treatment of Periodontal DiseaseUL1TR002489 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BUSE, JOHN BERNARD, SHAHEEN, NICHOLAS J · 2018 to 2022
$48.6M
North Carolina Translational & Clinical Sciences Institute (NC TraCS)UL1TR001111 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BUSE, JOHN BERNARD, CAREY, TIMOTHY S · 2013 to 2017
$43.9M
Epidemiologic Case-control Study of Barrett's EsophagusK23DK059311 · NIDDK · UNIVERSITY OF NORTH CAROLINA CHAPEL HILL · PI SHAHEEN, NICHOLAS J · 2001 to 2005
$626k
NCATS NIH HHS UL1 TR001111NCATS NIH HHS UL1 TR002489NIDDK NIH HHS K23 DK059311
6 · The paper itself

Abstract

The use of unmanned aerial vehicles or "drones" has expanded in the last decade, as their technology has become more sophisticated, and costs have decreased. They are now used routinely in farming, environmental surveillance, public safety, commercial product delivery, recreation, and other applications. Health-related applications are only recently becoming more widely explored and accepted. The use of drone technology in emergency medicine is especially promising given the need for a rapid response to enhance patient outcomes. The purpose of this paper is to describe some of the main current and expanding applications of drone technology in emergency medicine and to describe challenges and future opportunities. Current applications being studied include delivery of defibrillators in response to out-of-hospital cardiac arrest, blood and blood products in response to trauma, and rescue medications. Drones are also being studied and actively used in emergency response to search and rescue operations as well as disaster and mass casualty events. Current challenges to expanding their use in emergency medicine and emergency medical system (EMS) include regulation, safety, flying conditions, concerns about privacy, consent, and confidentiality, and details surrounding the development, operation, and maintenance of a medical drone network. Future research is needed to better understand end user perceptions and acceptance. Continued technical advances are needed to increase payload capacities, increase flying distances, and integrate drone networks into existing 9-1-1 and EMS systems. Drones are a promising technology for improving patient survival, outcomes, and quality of life, particularly for those in areas that are remote or that lack funds or infrastructure. Their cost savings compared with ground transportation alone, speed, and convenience make them particularly applicable in the field of emergency medicine. Research to date suggests that use of drones in emergency medicine is feasible, will be accepted by the public, is cost-effective, and has broad application.

Indexed as

droneemergency medical servicesemergency medicineunmanned aerial vehicle

Identifiers

PMID34815722
PMCPMC8605877

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.