Determining the optimal method of triage for the UK major incident setting

Malik, Nabeela Shabbir (2024). Determining the optimal method of triage for the UK major incident setting. University of Birmingham. Ph.D.

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Abstract

Major incidents are characterised by a mismatch between the immediate needs of patients and the resources available to treat them. In the UK, man-made major incidents comprising blast and penetrating trauma have occurred with increasing frequency in recent years and continue to constitute the greatest threat to national security (Chapter 1). Triage tools have a crucial role in ensuring that finite healthcare resources are allocated to maximise overall survival. Existing tools have largely been developed based on expert opinion and implemented without formal validation. A major challenge in furthering the science of major incident management is the lack of consensus and standardisation of end-points which best define Priority 1 (P1) status and other triage categories. In this thesis, the literature surrounding major incident triage was reviewed and modern, evidencebased definitions of triage categories were validated amongst adults and children from the UK national trauma registry (Chapters 1 and 2). This system developed by Lerner et al defined P1 patients as those requiring any one of eight time-critical life-saving surgical and major resuscitative interventions, directly reflecting patient resource requirements, and correlates well with casualty distribution within UK regionalised systems of trauma care. Hence it is recommended that Lerner’s criteria should become the gold standard in reporting triage tool performance in future UK major incidents. These intervention-based triage category definitions were compared with the triage category assignments of ten existing international triage tools. This comparative analysis demonstrated that the current UK national triage tool, the NARU Triage Sieve, is poorly sensitive in identifying P1 patients who require time-critical, life-saving interventions, and was surpassed in sensitivity by several tools, the best of which was the UK military’s BCD Triage Sieve (Chapter 2, publication number 1). Similarly, in children from the national trauma registry, the current UK tools, the Paediatric Triage Sieve and JumpSTART, demonstrated suboptimal performance and were substantially outperformed by several tools, with the BCD Triage Sieve again demonstrating the greatest sensitivity (Chapter 2, publication number 2). This has directly informed national policy, resulting in the removal of previous existing tools and a recommendation for the NHS Major Incident Triage Tool (MITT), the civilian adaptation of the BCD Triage Sieve, to become a single tool for NHS first responders to apply to all adults and children in future UK major incidents. Subsequently, using tree-based machine learning methodology, a novel primary triage tool, Quick Triage, as well as a secondary triage tool that is applicable via a portable device, have been developed (Chapter 3). Both tools outperform the BCD Triage Sieve amongst TARN patients, with reduced associated over-triage rates. The app-based secondary triage tool has withstood external validation amongst injured patients from the UK military’s Joint Theatre Trauma Registry (JTTR); however, a paucity of pre-hospital data precluded external validation of Quick Triage amongst JTTR patients, necessitating further work. Quick Triage has balanced, favourable performance amongst adults, children and elders with blunt and penetrating trauma from the UK national trauma registry, with lower over-triage rates than the NHS MITT (Chapter 4). This offers the possibility of a single tool for use amongst patients of all ages by all NHS and non-NHS first responders, allowing complete interchangeability, simplification of the prehospital triage process and likely more rapid and accurate triage of major incident casualties in future UK and international major incidents.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):