Trigger tool-based description of adverse events in helicopter emergency medical services in Qatar

被引:0
作者
Heuer, Calvin [1 ]
Howard, Ian [2 ]
Stassen, Willem [1 ]
机构
[1] Univ Cape Town, Div Emergency Med, Cape Town, South Africa
[2] Hamad Med Corp, Clin Serv, Ambulance Serv, Doha, Qatar
关键词
Trigger tools; Patient safety; Adverse events; epidemiology and detection; Prehospital care; PATIENT SAFETY; ERROR; HARM;
D O I
10.1136/bmjoq-2023-002263
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
IntroductionAdverse events (AEs) in helicopter emergency medical services (HEMS) remain poorly reported, despite the potential for harm to occur. The trigger tool (TT) represents a novel approach to AE detection in healthcare. The aim of this study was to retrospectively describe the frequency of AEs and their proximal causes (PCs) in Qatar HEMS.MethodsUsing the Pittsburgh Adverse Event Tool to identify AEs in HEMS, we retrospectively analysed 804 records within an existing AE TT database (21-month period). We calculated outcome measures for triggers, AEs and harm per 100 patient encounters, plotted measures on statistical process control charts, and conducted a multivariate analysis to report harm associations.ResultsWe identified 883 triggers in 536 patients, with a rate of 1.1 triggers per patient encounter, where 81.2% had documentation errors (n=436). An AE and harm rate of 27.7% and 3.5%, respectively, was realised. The leading PC was actions by HEMS Crew (81.6%; n=182). The majority of harm (57.1%) stemmed from the intervention and medication triggers (n=16), where deviation from standard of care was common (37.9%; n=11). Age and diagnosis-adjusted odds were significant in the patient condition (6.50; 95% CI 1.71 to 24.67; p=0.01) and interventional (11.85; 95% CI 1.36 to 102.92; p=0.03) trigger groupings, while age and diagnosis had no effect on harm.ConclusionThe TT methodology is a robust, reliable and valid means of AE detection in the HEMS domain. While an AE rate of 27.7% is high, more research is required to understand prehospital clinical decision-making and reasons for guideline deviance. Furthermore, focused quality improvement initiatives to reduce AEs and documentation errors should also be addressed in future research.
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