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Setting Up a Stroke Team Algorithm and Conducting Simulation-based Training in the Emergency Department - A Practical Guide
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Medical practitioner perspectives on AI in emergency triage.

Beverley A Townsend1, Katherine L Plant2, Victoria J Hodge3

  • 1York Law School, University of York, York, United Kingdom.

Frontiers in Digital Health
|December 21, 2023
PubMed
Summary

NHS Emergency Department (ED) practitioners are positive about AI triage systems like DAISY, citing reduced wait times and improved efficiency. However, trust, ethical concerns, and empathy remain key considerations for successful AI adoption in healthcare.

Keywords:
Diagnostic AI System for Robot-Assisted A & E Triage (DAISY)attitudesemergency department triagemedical practitionersperceptions

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Area of Science:

  • Artificial Intelligence in Healthcare
  • Medical Informatics
  • Emergency Medicine

Background:

  • Emergency Departments (EDs) face overcrowding and staff shortages globally, impacting patient care.
  • A Diagnostic AI System for Robot-Assisted Triage (DAISY) is being developed to alleviate these pressures.
  • Understanding healthcare practitioners' perspectives on AI in triage is crucial for successful implementation.

Purpose of the Study:

  • To explore National Health Service (NHS) health practitioners' attitudes towards AI-supported triage technologies.
  • To identify potential benefits and challenges associated with deploying AI in ED triage.
  • To understand the factors influencing the adoption of AI in emergency care settings.

Main Methods:

  • A qualitative-exploratory study using semi-structured interviews with nine NHS healthcare practitioners.
  • Thematic analysis of transcribed interviews, employing both inductive and deductive approaches.
  • Quantitative analysis of participant vocabulary and sentiment regarding current practices versus AI systems.

Main Results:

  • Practitioners expressed positive attitudes towards AI triage, anticipating reduced patient wait times and streamlined processes.
  • Key themes identified include trust, current practice integration, socio-legal-ethical concerns, and the importance of empathetic practice.
  • Trust was highlighted as a significant driver for AI adoption, while ethical and cultural factors presented potential barriers.

Conclusions:

  • AI-supported triage systems like DAISY show promise in augmenting human performance in EDs.
  • Addressing concerns related to trust, ethics, and maintaining empathy is vital for successful AI implementation.
  • Findings offer insights for developing and implementing future AI healthcare solutions in triage settings.