Title: Emergency Medical Services Streaming Enabled Evaluation In Trauma: The SEE - IT trial
Funder: Department of Health and Social Care

Abstract: A ‘trauma incident’ is when someone suffers injuries that may cause death or leave them with a long-term disability. Trauma incidents are the biggest killer of people aged under 45 in the UK: most often road traffic accidents. Following a trauma incident, most people will be taken to a hospital emergency department by an ambulance that has responded to a 999 call. Ambulances usually attend an incident by road, but in serious cases, an air ambulance (helicopter) may be sent. The aim is to get the patient to the best hospital for treating their injuries without delay to improve their chances of survival, recovering from their injuries and not having long term problems._x000D_ _x000D_ When a 999 call is made, the person in the ambulance service who answers (the dispatcher) asks the caller to describe what they can see and how serious the injuries appear. This is so the dispatcher can decide how urgently, and what type, of help is required (e.g. whether a helicopter is needed). The caller may give incomplete or wrong information so sometimes too few or too many ambulances are sent. This can delay getting the right help to patients, or mean that ambulances are not available for others who need them. It is also costly for the NHS if ambulances or helicopters are sent when not needed._x000D_ _x000D_ We want to test a system called GoodSAM that allows the dispatcher to send a link in a text message to the smartphone of 999 callers. When the caller clicks on the link it uses the camera in their phone to send live images to the dispatcher (without recording it). This lets the dispatcher see what is happening at the scene, rather than just being told by the caller. This might help the dispatcher make quicker and more accurate decisions about which and how many ambulances to send, so that patients get the best help in the fastest possible time._x000D_ _x000D_ In this study, we will ask one ambulance dispatch centre to test GoodSAM for six weeks spread out over six months (to cover different periods when trauma incidents are higher/lower), so we can check how well it works in practice. We will count the number of calls when video might help the dispatcher decide what ambulances to send. We will check that the link works, and the dispatcher can see the images. After an incident is over, our researchers will look at the reports and assess if the right number and type of ambulances were sent to the scene. We will do this for incidents when GoodSAM was used, and when it was not (control group). This will help us to understand if film footage helped dispatchers send the right ambulances. _x000D_ _x000D_ We will learn if members of the public are willing to allow their camera to be used and if dispatchers find it useful. An important part of this initial study will be to find out whether using live streaming upset the members of the public or dispatchers in any way. We will do this through interviews and a survey with members of the public and staff who did and did not use GoodSAM. Sources of support will be provided. We will also explore these issues in a second ambulance service located in a city so we can see if GoodSAM works in a similar way in an area where callers may not speak English for example._x000D_ This study will help us plan a larger study that will explore more fully the possible benefits of using film footage at trauma incidents. A panel of lay people will be set up to work with the research team throughout the project to make sure the views of patients and the public are fully represented.

Lay abstract: BACKGROUND: Timely dispatch of appropriate emergency resources after traumatic incidents is critical to prevent death and improve outcomes. Dispatch priorities mostly rely on verbal 999-caller information and up to 50% air/25% road ambulance deployments are inappropriate. Video from scene is recommended but lacks evidence. GoodSAM enables video streaming to dispatchers using callers’ smartphone cameras._x000D_ _x000D_ RESEARCH QUESTION: Is it feasible to conduct a future RCT to assess the clinical and cost effectiveness of using GoodSAM to improve targeting of emergency resources?_x000D_ OVERALL AIM: To assess the feasibility of implementing and evaluating GoodSAM in a definitive RCT._x000D_ OBJECTIVES:_x000D_ 1. To obtain data to design a definitive RCT (e.g. event & screening rates, effect size/precision for outcomes, health economic data)_x000D_ 2. To test trial processes including randomisation and data collection_x000D_ 3. To conduct a process evaluation to test acceptability, feasibility and outcomes of use of GoodSAM from provider and public perspectives (e.g. training, video feasibility and acceptability, psychological harm to callers and/or dispatch staff)._x000D_ _x000D_ DESIGN/SETTING: Feasibility RCT in one Emergency Operations Centre in SE England_x000D_ METHODS:_x000D_ INCLUSION: All 999 calls involving Category 1 or 2 trauma; All calls screened by Helicopter Emergency Medical Services dispatchers involving trauma._x000D_ EXCLUSION: All emergencies of a suspected medical origin._x000D_ RANDOMISATION: Calls in 6 observation weeks (42 days; 84 shifts) allocated 1:1 by shift._x000D_ CONTROL: Standard care NHS Pathways dispatch protocol with a 999-caller (verbal only)_x000D_ INTERVENTION: As per control group until call handler has determined dispatch priority and ambulance dispatched without delay. GoodSAM streaming will then begin (via SMS text link) and ambulance dispatch may be adjusted._x000D_ PRIMARY OUTCOME: Decision regarding feasibility of undertaking a definitive RCT based on pre-defined criteria (willingness/ability to stream footage, signal of effect; and risk of psychological harm in callers/staff). _x000D_ SECONDARY OUTCOMES: Speed of appropriate emergency dispatch (using time-stamped data from 999 call to appropriate deployment; appropriateness based on expert consensus criteria and using data up to 3 months post-incident), stand-down rate, missed jobs, further resources requested from scene._x000D_ SAMPLE SIZE: Conservative event rate = 250 trauma incidents (125 allocated to intervention) allowing estimate of true rate within precision of +/-0.75 events/day; and of appropriateness of response with a standard error of <5%._x000D_ A health economic analysis will be undertaken to inform design of a subsequent full economic evaluation. The process evaluation will include analysis of streaming usage data; observation of control room processes (e.g. fidelity to study protocol); and survey and interviews with staff and 999 callers. A sub-study in an inner-city site will examine acceptability of GoodSAM in a population with greater diversity._x000D_ ANALYSIS: estimates and confidence intervals of key rates. A framework approach will be used to analyse qualitative data._x000D_ TIMELINE: 18 months._x000D_ _x000D_ IMPACT/DISSEMINATION: This study will determine if a subsequent definitive trial is feasible; and produce novel data about psychological harm associated with witnessing/viewing trauma incidents. We will disseminate findings via academic and lay outputs. If effective, GoodSAM could be scaled up nationally/used for other incidents e.g. multi-agency.

Research activity codes: 8.1 ORGANISATION AND DELIVERY OF SERVICES
Health categories: INJURIES AND ACCIDENTS