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PP33 Which patients receive a prealert? Analysis of linked data in three ambulance services
  1. Fiona Sampson1,
  2. Richard Pilbery2,
  3. Esther Herbert1,
  4. Fiona Bell2,
  5. Andy Rosser3,
  6. Rob Spaight4,
  7. Steve Goodacre1,
  8. Andy Pountney2,
  9. Mark Millins2
  1. 1The University of Sheffield, UK
  2. 2Yorkshire Ambulance Service NHS Trust, UK
  3. 3West Midlands Ambulance Service NHS Foundation Trust, UK
  4. 4East Midlands Ambulance Service NHS Trust, UK


Background Ambulance clinicians use pre-alert calls to advise Emergency Departments (EDs) about patients who may require immediate assessment on arrival. Despite pre-alerts playing a key role in the transfer of care between ambulance and ED clinicians, there is a lack of understanding about which patients should receive a pre-alert and potential variation in practice.

Methods We created a linked dataset from 3 ambulance services comprising of 999 call, electronic patient record and ambulance staff demographic and shift pattern data for all ED ambulance conveyances between July 2020–June 2021. We also compared pre-alert activity with the AACE/RCEM guidance on pre-alerts. We undertook descriptive analysis using the statistics package R.

Results Pre-alerts were recorded in 10.5% of conveyances (142,795/1,363,274) with significant variation in pre-alert rates between ambulance services (8.2%–15.0%) and between receiving hospitals. Paramedics pre-alerted 10.7% of their conveyances (107,309/1,002,733) with non-registered clinician staff pre-alerting 9.8% of their conveyances (35,486/360,541).

Patients who met the AACE/RCEM pre-alert criteria were more likely to be actually pre-alerted when they met non-physiological criteria (e.g. stroke), compared to physiological criteria (e.g. respiratory rate) (51.9% vs 28.5%). Only a third of cases that met any AACE/RCEM physiological criteria for pre-alert were actually pre-alerted (103,066/323,971). Around 15% (20,522/142795) of pre-alerts were for patients in low priority triage categories (3-5).

Conditions with the highest numbers of pre-alerts included suspected sepsis (21,479/142,795, 15.0%), unspecified medical conditions (16,884, 11.8%) and acute stroke (14,869, 10.4%). Covid-19, respiratory problems and lower respiratory tract infections made up a further 15.4% of pre-alerts. Highest pre-alert rates were found with suspected sepsis (21,749/34,821,62%), acute stroke (14,869/27,783, 54%) and STEMI (3,687/6,207, 59%).

Conclusion There is significant variation in patients who are pre-alerted. Improved clarity of criteria for pre-alert may help. Variation may be partly due to under-documentation of pre-alerts.

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