ArticleScandinavian journal of trauma, resuscitation and emergency medicine2022
Artificial intelligence in Emergency Medical Services dispatching: assessing the potential impact of an automatic speech recognition software on stroke detection taking the Capital Region of Denmark as case in point.
Article in Scandinavian journal of trauma, resuscitation and emergency medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 38 citations in OpenAlex.
- Stroke recognition and early care pathways following telephone triage in out-of-hours primary care: a register-based study from the Central Denmark Region.Scandinavian journal of primary health care · 2026Article
- Review
- Behavioral Determinants Potentially Relevant to First-Witness Responses in Prehospital Stroke Care: A COM-B-Based Scoping Review.Healthcare (Basel, Switzerland) · 2026Review
- Stroke detection in medical emergency calls: a retrospective analysis and exploratory evaluation of an AI decision support model.Scandinavian journal of trauma, resuscitation and emergency medicine · 2026Article
- Decision to initiate transport to either Stroke Unit or local emergency department for patients with suspected stroke - a cohort study.BMC emergency medicine · 2026Article
- Current State of the Clinical Applications of Artificial Intelligence in Stroke: A Literature Review.Brain sciences · 2026Review
- Research trends and ethical perspectives on explainable artificial intelligence in emergency medicine: a bibliometric analysis.Scandinavian journal of trauma, resuscitation and emergency medicine · 2026Review
- Use of artificial intelligence in the out-of-hospital care settings: a scoping review.BMJ digital health & AI · 2026Article
- Changes in public perception of artificial intelligence in healthcare after exposure to ChatGPT.NPJ digital medicine · 2025Article
- Clinical trials and advanced MRI techniques with stem cell therapy for ischemic stroke: present and future perspectives.Journal of translational medicine · 2025Review
- Applications of Artificial Intelligence in Out-of-Hospital Cardiac Arrest: A Systematic Review.Cureus · 2025Review
- Strengthening the WHO Emergency Care Systems Framework: insights from an integrated, patient-centered approach in the Copenhagen Emergency Medical Services system-a qualitative system analysis.BMC health services research · 2025Article
- Methods for improving the identification of acute stroke during ambulance calls: A scoping review.PloS one · 2025Article
- Pre-Hospital Stroke Care beyond the MSU.Current neurology and neuroscience reports · 2024Review
- Centennial Collection: Prehospital Stroke Triage.Stroke (Hoboken, N.J.) · 2024Article
- Revolutionizing Radiological Analysis: The Future of French Language Automatic Speech Recognition in Healthcare.Diagnostics (Basel, Switzerland) · 2024Article
- Risk Management and Patient Safety in the Artificial Intelligence Era: A Systematic Review.Healthcare (Basel, Switzerland) · 2024Review
- Artificial intelligence to enhance prehospital stroke diagnosis and triage: a perspective.Frontiers in neurology · 2024Article
- Revolutionizing Neurosurgery with GPT-4: A Leap Forward or Ethical Conundrum?Annals of biomedical engineering · 2023Article
- Blockchain Revolutionizing in Emergency Medicine: A Scoping Review of Patient Journey through the ED.Healthcare (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and purposeStroke recognition at the Emergency Medical Services (EMS) impacts the stroke treatment and thus the related health outcome. At the EMS Copenhagen 66.2% of strokes are detected by the Emergency Medical Dispatcher (EMD) and in Denmark approximately 50% of stroke patients arrive at the hospital within the time-to-treatment. An automatic speech recognition software (ASR) can increase the recognition of Out-of-Hospital cardiac arrest (OHCA) at the EMS by 16%. This research aims to analyse the potential impact an ASR could have on stroke recognition at the EMS Copenhagen and the related treatment.
methodsStroke patient data (n = 9049) from the years 2016-2018 were analysed retrospectively, regarding correlations between stroke detection at the EMS and stroke specific, as well as personal characteristics such as stroke type, sex, age, weekday, time of day, year, EMS number contacted, and treatment. The possible increase in stroke detection through an ASR and the effect on stroke treatment was calculated based on the impact of an existing ASR to detect OHCA from CORTI AI.
resultsThe Chi-Square test with the respective post-hoc test identified a negative correlation between stroke detection and females, the 1813-Medical Helpline, as well as weekends, and a positive correlation between stroke detection and treatment and thrombolysis. While the association analysis showed a moderate correlation between stroke detection and treatment the correlation to the other treatment options was weak or very weak. A potential increase in stroke detection to 61.19% with an ASR and hence an increase of thrombolysis by 5% in stroke patients calling within time-to-treatment was predicted.
conclusionsAn ASR can potentially improve stroke recognition by EMDs and subsequent stroke treatment at the EMS Copenhagen. Based on the analysis results improvement of stroke recognition is particularly relevant for females, younger stroke patients, calls received through the 1813-Medical Helpline, and on weekends.
trial registrationThis study was registered at the Danish Data Protection Agency (PVH-2014-002) and the Danish Patient Safety Authority (R-21013122).
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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.