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Cardiopulmonary Resuscitation III: AED Use01:23

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Introduction to AEDAn Automated External Defibrillator (AED) is a portable medical device that analyzes the heart's rhythm and, if necessary, delivers an electrical shock to help the heart re-establish an effective rhythm during sudden cardiac arrest (SCA). SCA occurs when the heart suddenly and unexpectedly stops beating, leading to a loss of blood flow to the brain and other vital organs. In such emergencies, time is of the essence, and using an AED, combined with Cardiopulmonary...
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Airway management is a key skill in emergency and critical care settings, as maintaining a clear airway is essential for adequate oxygenation and ventilation.Head Tilt-Chin Lift TechniqueThe head tilt-chin lift maneuver is an essential technique primarily used in patients without suspected cervical spine injuries. To perform this maneuver, one hand is placed on the patient’s forehead, and gentle pressure is applied backward to tilt the head. The fingertips of the other hand are positioned...
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Pharmacologic intervention is crucial in treating cardiac arrest patients during ACLS or Advanced Cardiovascular Life Support. The ACLS algorithms guide the administration of specific drugs based on the patient's cardiac arrest rhythm, which includes pulseless ventricular tachycardia (VT), ventricular fibrillation (VF), asystole, and pulseless electrical activity (PEA).EpinephrineIndication: Epinephrine is the first-line drug for all cardiac arrest rhythms.Mechanism of Action: Epinephrine...
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Related Experiment Video

Updated: Aug 19, 2025

Setting Up a Stroke Team Algorithm and Conducting Simulation-based Training in the Emergency Department - A Practical Guide
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Assuring safe artificial intelligence in critical ambulance service response: study protocol.

Mark Sujan1, Harold Thimbleby2, Ibrahim Habli3

  • 1Human Factors Everywhere Ltd. ORCID iD: https://orcid.org/0000-0001-6895-946X.

British Paramedic Journal
|December 1, 2022
PubMed
Summary
This summary is machine-generated.

An artificial intelligence (AI) system aids ambulance call centres in recognizing out-of-hospital cardiac arrests (OHCA). This study explores stakeholder safety perceptions and develops a clinical safety case for the AI decision-support tool.

Keywords:
artificial intelligenceemergency medical servicesout-of-hospital cardiac arrestsafety

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Area of Science:

  • Emergency medical services
  • Artificial intelligence in healthcare
  • Patient safety

Background:

  • Early recognition of out-of-hospital cardiac arrest (OHCA) is crucial for immediate cardiopulmonary resuscitation.
  • Approximately 25% of OHCAs are missed by ambulance call centre operators.
  • An AI system is being developed to assist operators in OHCA detection.

Purpose of the Study:

  • To explore Welsh Ambulance Service stakeholder perceptions of OHCA AI decision support safety.
  • To develop a clinical safety case for the OHCA AI decision-support system.

Main Methods:

  • Qualitative study design utilizing thematic analysis of interview data.
  • Service evaluation involving document analysis and AI model assessment.
  • Informal interviews with the AI technology developer.

Main Results:

  • The study is currently in progress, focusing on gathering data for the safety case and stakeholder perceptions.
  • Analysis of the AI model and its development process is underway.
  • Stakeholder interviews are being conducted to gather insights on safety perceptions.

Conclusions:

  • AI offers significant potential for enhancing ambulance service operations.
  • Understanding and addressing safety assurance requirements is critical for AI implementation in emergency services.
  • The ASSIST project aims to contribute to the knowledge base regarding AI safety in this domain.