{
  "abstract": "Background Identifying strokes accurately during ambulance calls poses significant challenges, which can lead to low diagnostic accuracy and delays in dispatching appropriate services. Currently, there is limited evidence on methods to enhance stroke recognition by call handlers. This scoping review investigates strategies to improve stroke identification during emergency calls to ambulance control centres (ACCs).Methods Following the Joanna Briggs Institute methodology and PRISMA-ScR guidelines, we conducted a systematic search across five databases: Embase, Medline, Scopus, Web of Science, and CINAHL, along with grey literature sources, covering publications from January 1964 to July 2024. We focused on studies that examined methods for enhancing stroke recognition during emergency calls to ACCs, assessing outcomes such as accuracy of diagnosis, time to diagnosis, the effectiveness of training, and the acceptability of identification techniques. Two reviewers screened, extracted data, and performed thematic analysis to identify key themes.Results Of the 3,619 studies identified, seven met the inclusion criteria. These studies emphasized technology and algorithms (n=3), training programs (n=2), and enhanced triage tools (n=2) for improving stroke identification. Findings revealed that new algorithms increased sensitivity and positive predictive value (PPV), while training improved dispatcher recognition. Furthermore, improved triage tools reduced diagnosis time, facilitating swifter emergency responses.Conclusion This review indicates multiple methods for advancing stroke identification in ACCs. However, obstacles such as a lack of general standards and heterogeneous study populations limit broader applicability. Future research should focus on well-designed studies with standardised benchmarks to enhance prehospital stroke identification strategies.",
  "authors": [
    {
      "affiliations": [
        "University of Edinburgh, Usher Institute, Centre for Population Health Sciences. Edinburgh, UK",
        "King Saud Bin Abdulaziz University for Health Sciences, College of Applied Medical Sciences, Department of Emergency Medical Services, Jeddah, Saudi Arabia"
      ],
      "name": "Areej Almutairi"
    },
    {
      "affiliations": [
        "University of Edinburgh, Usher Institute, Centre for Population Health Sciences. Edinburgh, UK",
        "Universitas Indonesia, Department of Public Health Nutrition, Jakarta, Indonesia"
      ],
      "name": "Fadila Wirawan"
    },
    {
      "affiliations": [
        "Scottish Ambulance Service, Edinburgh, Scotland, UK"
      ],
      "name": "Adam Lloyd"
    },
    {
      "affiliations": [
        "Centre for Clinical Brain Sciences, University of Edinburgh, Scotland, UK"
      ],
      "name": "Tom Moullaali"
    },
    {
      "affiliations": [
        "University of Edinburgh, Usher Institute, Centre for Population Health Sciences. Edinburgh, UK",
        "Scottish Ambulance Service, Edinburgh, Scotland, UK"
      ],
      "name": "Gareth Clegg"
    }
  ],
  "title": "01 Methods for improving the identification of acute stroke during ambulance calls: a scoping review",
  "uid": "ed75d7d6-4768-5ea4-8f0d-4d3a61b2ed58"
}