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Identification of the Sick Patient in the ED

Lancashire Teaching Hospitals NHS Foundation Trust · 2017
ClinicalTrials.gov · Datasets · License: Public Domain · 2017
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early-warning-systememergenciestriage
This non-interventional study will test scoring systems used to identify high risk patients when they are triaged upon presentation in the Emergency Department (ED) in a single hospital in the Northwest of England between May and July 2017.E The study will involve collecting data only from a cohort of 500 consecutive patients who arrive at the ED. Patients who have a traumatic, purely obstetric or purely psychiatric condition will be excluded. Patients will be triaged as is routine by nursing and medical staff using various scoring methods determine whether they are high risk and need urgent, life-saving treatment. In addition the impression (yes/no) of the triaging nurse and the treating clinician as to whether the patient will need a life-saving intervention will be collected. Patients will be followed up for 48 hours to see whether they needed any life-saving treatment, such as admission to ICU, life-saving surgery, cardiopulmonary resuscitation (CPR), or death. Each patient's Manchester Triage category, NEWS at presentation, nurse and treating clinician impressions and a novel score calculated from NEWS data will be collected together with the outcome data in order to compare the predictive power of the five scoring systems. In this way the study will test which is the best scoring system for identifying high risk patients in a timely manner. This is important as it can allow life saving treatment to be delivered quickly to those patients who need it most and can prevent inappropriate interventions on patients who do not immediately need them. The study will collect minimal patient information and will not interfere with or alter their treatment in any way. Only patient data recorded as part of routine practice is required, which will be collected by members of the direct care team and will be anonymised prior to analysis.
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