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PP32 What factors affect pre-hospital pre-alerts? Analysis of routine ambulance data
  1. Richard Pilbery1,
  2. Fiona Sampson2,
  3. Esther Herbert2,
  4. Fiona Bell1,
  5. Andy Rosser3,
  6. Rob Spaight4,
  7. Andy Pountney1,
  8. Mark Millins1,
  9. Steve Goodacre2
  1. 1Yorkshire Ambulance Service NHS Trust, UK
  2. 2The University of Sheffield, UK
  3. 3West Midlands Ambulance Service NHS Foundation Trust, UK
  4. 4East Midlands Ambulance Service NHS Trust, UK


Background Ambulance clinicians can use pre-alerts calls to advise emergency departments (EDs) of the imminent arrival of a patient who may require immediate senior clinical review or intervention. Consistency of pre-alert practice is important in ensuring that EDs can respond to pre-alerts appropriately. We sought to understand what factors might affect variation in pre-alerting practice.

Methods We explored variation in pre-alert use by analysing clinician factors (role, experience, qualification, time of pre-alert during shift), patient factors (NEWS2 score, clinical working impression, age, sex) and hospital factors (receiving ED, ED handover delay status). We created a linked data set containing patient, 999 call and human resource records for all ambulance conveyances from three UK Ambulance Services for one year (July 2020 to June 2021). We used lasso regression to identify candidate variables for three (one per service) multivariate logistic regression models to explain variation in pre-alert rates in terms of clinician, patient and hospital factors.

Results Patient factors (NEWS score and specific clinical conditions) were the most significant variables associated with pre-alert use. In addition, male patients were more likely to be pre-alerted than females.

Pre-alert rates were also affected by clinician role, receiving hospital (including several hospitals that were not tertiary centres for major trauma, stroke or myocardial infarction) and anticipated handover delay at receiving hospitals. There was no evidence of higher pre-alert rates in the final hour of shift.

Conclusion We identified variation in pre-alert practice that was not explained by the patient’s clinician presentation. Further qualitative work with ED and ambulance staff is required to explore other factors that influence decisions to pre-alert.

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