Mixed methods study exploring factors influencing ambulance clinician decisions to pre-alert emergency departments (EDS) of a patient’s arrival
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Author
Sampson, FionaPilbery, Richard
Herbert, Esther
Long, Jaqui
Coster, Joanne
O'Hara, Rachel
Bell, Fiona
Goodacre, Steve
Rosser, Andy
Spaight, Robert
Millins, Mark
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Aims and Objectives Ambulance pre-alert calls can lead to improved treatment of time-critical patients by enabling Emergency Departments (EDs) to prepare for their arrival but need to be used judiciously to optimise patient care. Despite their importance, there is a lack of research understanding how pre-alert decisions are made. We aimed to understand factors influencing ambulance clinician pre-alert decision-making. Method and Design Using a convergent parallel mixed-methods design we integrated quantitative and qualitative data from three Ambulance Services and six Emergency Departments using: 1) linked routine dataset of 12 months’ (2020/21) electronic patient records (3 Ambulance Services), clinician information and routine hospital statistics 2) semi-structured interviews with 35 ambulance clinicians and 40 ED staff and 156 hours non-participation observation of pre-alerts across six EDs. Lasso regression to identify candidate variables for multivariate logistic regression was undertaken in R(™) to explain variation in pre-alert rates in terms of patient (NEWS2 score, working diagnosis, age, sex), ambulance clinician (experience, role, sex, time to end of shift) and hospital factors (journey time,% ambulances waiting >30 mins). Qualitative data was analysed using thematic analysis in NVivo(™). Findings were integrated using a triangulation protocol. Results and Conclusion Variation in pre-alert practice was not fully explained by casemix. Overall 142,795/1,363,274 conveyances were pre-alerted. Highest overall odds ratios (ORs) for pre-alert were associated with patient factors (working diagnosis OR:4.16,CI:4.05-4.26, NEWS2 OR:1.4,CI:1.39-1.4) but thresholds for pre-alerting varied between ambulance clinicians. Pre-alerts were more likely when there were longer turnaround times at EDs (OR:1.83,CI:1.69-1.98), potentially due to ambulance clinicians’ concerns about their ability to effectively manage deteriorating patients where long handovers were anticipated. There was a significant difference in pre-alert rates between EDs (figure 1) that was not explained by type of hospital (e.g. Major Trauma Centres). Anticipated ED response to pre-alerts had a significant impact on pre-alert decisions due to variation in ED protocols and expectations. https://emj.bmj.com/content/40/12/875 This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ae974a485f413a2113503eed53cd6c53
10.1136/emj-2023-RCEM.28
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