What factors predict ambulance prealerts to the emergency department? Retrospective observational study from three UK ambulance services

ObjectivesAmbulance clinicians use prealert calls to advise emergency departments (ED) of the arrival of patients requiring immediate review or intervention. Consistency of prealert practice is important in ensuring appropriate ED response to prealert calls. We used routine data to describe prealert...

Full description

Saved in:
Bibliographic Details
Published in:BMJ open Vol. 15; no. 3; p. e097122
Main Authors: Pilbery, Richard, Sampson, Fiona C, Herbert, Esther, Goodacre, Steve, Bell, Fiona, Spaight, Rob, Rosser, Andy, Webster, Peter, Millins, Mark, Pountney, Andrew, Coster, Joanne, Long, Jaqui, O’Hara, Rachel, Foster, Alexis, Miles, Jamie, Turner, Janette, Boyd, Aimee
Format: Journal Article
Language:English
Published: England British Medical Journal Publishing Group 07.03.2025
BMJ Publishing Group LTD
BMJ Publishing Group
Subjects:
ACCIDENT & EMERGENCY MEDICINE
Adolescent
Adult
Aged
Ambulance services
Ambulances - statistics & numerical data
Emergency Departments
Emergency medical care
Emergency Medical Services - statistics & numerical data
Emergency Medicine
Emergency Service, Hospital - statistics & numerical data
Female
Hospitals
Humans
Logistic Models
Male
Medical diagnosis
Middle Aged
Observational studies
Original Research
Paramedics
Patients
Physiology
Regression analysis
Retrospective Studies
Sepsis
STATISTICS & RESEARCH METHODS
Stroke
United Kingdom
Variables
Young Adult
United Kingdom
United Kingdom > UK
England
STATISTICS & RESEARCH METHODS
ACCIDENT & EMERGENCY MEDICINE
Emergency Departments
ISSN:2044-6055, 2044-6055
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:ObjectivesAmbulance clinicians use prealert calls to advise emergency departments (ED) of the arrival of patients requiring immediate review or intervention. Consistency of prealert practice is important in ensuring appropriate ED response to prealert calls. We used routine data to describe prealert practice and explore factors affecting variation in practice.Design and settingWe undertook a retrospective observational study in three UK ambulance services using a linked dataset incorporating 12 months’ ambulance patient records, ambulance clinician data and emergency call data.Outcome measuresWe used least absolute shrinkage and selection operator regression to identify candidate variables for multivariate logistic regression models to predict variation in prealert use, analysing clinician factors (role, experience, qualification, time of prealert during shift), patient factors (National Early Warning Score version 2, clinical working impression, age, sex) and hospital factors (receiving ED, ED handover delay status).ResultsFrom the dataset of 1 363 274 patients conveyed to ED, 142 795 (10.5%) were prealerted, of whom 42 362 (30%) were for conditions with clear prealert pathways (eg, sepsis, stroke, ST-elevation myocardial infarction, major trauma). Prealert rates varied across and within different ambulance services. Casemix (illness acuity score, clinical diagnostic impression) was the strongest predictor of prealert use, but male patient sex, clinician role, receiving hospital and hospital turnaround delay at receiving hospitals were also statistically significant predictors, after adjusting for casemix. There was no evidence that prealert rates are higher during the final hour of shift.ConclusionsPrealert decisions are influenced by factors other than illness acuity and clinical diagnostic impression alone. Variation in prealert practice suggests that procedures and processes for prealerting may lack clarity and improved prealert protocols may be required. Research is required to understand whether our findings are reproducible elsewhere and why non-clinical factors (eg, patient gender) may influence prealert practice.
Bibliography:Original research
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ObjectType-Undefined-3
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.
None declared.
ISSN:2044-6055
2044-6055
DOI:10.1136/bmjopen-2024-097122