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Prevalence and predictors of hospital prealerting in acute stroke: a mixed methods study
  1. J P Sheppard1,
  2. A Lindenmeyer2,
  3. R M Mellor3,
  4. S Greenfield3,
  5. J Mant4,
  6. T Quinn5,
  7. A Rosser6,
  8. D Sandler7,
  9. D Sims8,
  10. M Ward6,
  11. R J McManus1
  12. on behalf of the CLAHRC BBC investigators
    1. 1Nuffield Department of Primary Care Health Sciences, NIHR School for Primary Care Research, University of Oxford, Oxford, Oxfordshire, UK
    2. 2Primary Care Clinical Sciences, NIHR School for Primary Care Research, University of Birmingham, Birmingham, West Midlands, UK
    3. 3Department of Public Health, NHS Lanarkshire, Bothwell, UK
    4. 4Primary Care Unit, University of Cambridge, Cambridge, Cambridgeshire, UK
    5. 5Faculty of Health, Social Care and Education, St George's, University of London & Kingston University, London, UK
    6. 6West Midlands Ambulance Service NHS Trust, Regional Ambulance Headquarters, Dudley, West Midlands, UK
    7. 7Heart of England NHS Foundation Trust, Birmingham, West Midlands, UK
    8. 8Queen Elizabeth Hospital Birmingham Elderly Care, University Hospitals Birmingham NHS Foundation Trust, Birmingham, West Midlands, UK
    1. Correspondence to Professor R J McManus, Nuffield Department of Primary Care Health Sciences, NIHR School for Primary Care Research, University of Oxford, Oxford, Oxfordshire OX2 6GG, UK; richard.mcmanus{at}


    Background Thrombolysis can significantly reduce the burden of stroke but the time window for safe and effective treatment is short. In patients travelling to hospital via ambulance, the sending of a ‘prealert’ message can significantly improve the timeliness of treatment.

    Objective Examine the prevalence of hospital prealerting, the extent to which prealert protocols are followed and what factors influence emergency medical services (EMS) staff's decision to send a prealert.

    Methods Cohort study of patients admitted to two acute stroke units in West Midlands (UK) hospitals using linked data from hospital and EMS records. A logistic regression model examined the association between prealert eligibility and whether a prealert message was sent. In semistructured interviews, EMS staff were asked about their experiences of patients with suspected stroke.

    Results Of the 539 patients eligible for this study, 271 (51%) were recruited. Of these, only 79 (29%) were eligible for prealerting according to criteria set out in local protocols but 143 (53%) were prealerted. Increasing number of Face, Arm, Speech Test symptoms (1 symptom, OR 6.14, 95% CI 2.06 to 18.30, p=0.001; 2 symptoms, OR 31.36, 95% CI 9.91 to 99.24, p<0.001; 3 symptoms, OR 75.84, 95% CI 24.68 to 233.03, p<0.001) and EMS contact within 5 h of symptom onset (OR 2.99, 95% CI 1.37 to 6.50 p=0.006) were key predictors of prealerting but eligibility for prealert as a whole was not (OR 1.92, 95% CI 0.85 to 4.34 p=0.12). In qualitative interviews, EMS staff displayed varying understanding of prealert protocols and described frustration when their interpretation of the prealert criteria was not shared by ED staff.

    Conclusions Up to half of the patients presenting with suspected stroke in this study were prealerted by EMS staff, regardless of eligibility, resulting in disagreements with ED staff during handover. Aligning the expectations of EMS and ED staff, perhaps through simplified prealert protocols, could be considered to facilitate more appropriate use of hospital prealerting in acute stroke.

    • prehospital care
    • emergency department

    This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See:

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