What factors predict ambulance pre-alerts to the emergency department? Analysis of routine data from three UK ambulance services.

Abstract

Objective Ambulance clinicians use pre-alert calls to advise emergency departments (ED) of the arrival of patients requiring immediate review or intervention. Consistency of pre-alert practice is important in ensuring appropriate ED response to pre-alert calls. We used routine data to describe pre-alert practice and explore factors affecting variation in practice. Methods We undertook an observational study using a linked dataset incorporating 12 months’ ambulance patient records, ambulance clinician data and emergency call data for three UK ambulance services. We used LASSO regression to identify candidate variables for multivariate logistic regression models to predict variation in pre-alert use, analysing clinician factors (role, experience, qualification, time of pre-alert during shift), patient factors (NEWS2, clinical working impression, age, sex) and hospital factors (receiving ED, ED handover delay status). Results From the dataset of 1,363,274 patients conveyed to ED, 142,795 (10.5%) were pre-alerted, of whom only a third were for conditions with clear pre-alert pathways (e.g. sepsis, ST-elevation MI, major trauma). Pre-alert rates varied across and within different ambulance services. Casemix (illness acuity score, clinical diagnostic impression) was the strongest predictor of pre-alert 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 pre-alert rates are higher during the final hour of shift. Conclusions Pre-alert decisions are determined by factors other than illness acuity and clinical diagnostic impression. Variation in pre-alert practice suggests that procedures and processes for pre-alerting may lack clarity and improved pre-alert protocols may be required. Research is required to determine whether our findings are reproducible elsewhere and why non-clinical factors (e.g. patient gender) may influence pre-alert practice.