Emergency medical admissions to NHS hospitals place a significant strain on the NHS, affecting planned services, such as operations, with many procedures being cancelled, especially in winter. It can lead to patients being cared for in inappropriate areas in hospital, and this is associated with poor patient outcomes and causes considerable distress to patients and their families/carers.

Same Day Emergency Care (SDEC) has been proposed to reduce hospital admissions, with patients attending hospital with an acute medical problem being reviewed in SDEC (usually a seated area) where investigations and treatments are started. Patients are sent home that day, but they can return to SDEC for further investigations or treatments, if needed on following days. This all happens without admission to a hospital bed.

In the UK, SDEC has been highlighted as a priority to reduce hospital admissions but appropriate patient selection to SDEC is vital; moving patients from SDEC to a hospital bed, or vice versa, negatively affects patient care and flow through the hospital. However, there are challenges in delivering an effective SDEC service:

  1. Currently, it is unclear how best to choose patients for SDEC. Two scoring systems have been suggested for SDEC patient selection: the Amb score (Ambs) and Glasgow Admission Prediction Score (GAPS). These tools were developed in rural Wales and Glasgow, respectively, mainly on White males. We have tested their performance in a diverse, urban population and found their ability to identify appropriate SDEC patients is only 50% – the same as flipping a coin.
  2. Patients do not understand what SDEC is or why it might be more appropriate for their care. This can lead to patient dissatisfaction. Patientshave reported seeing SDEC as being a “lower priority” service or “another waiting room”, which is not the case.

A team including healthcare professionals, senior hospital leaders and national representatives from the Society of Acute Medicine (SAM) will develop a scoring system – based on a diverse patient population – to identify patients that could benefit from SDEC. Using highly detailed hospital data, the team will apply traditional statistical methods and machine learning (where a computer learns to predict outcomes by testing the data) to build a model that better identifies patients for SDEC.

The model will be designed to use data which would be routinely available to the clinical staff within 4 hours of patients arriving at hospital. This includes information about the patient, their medical conditions and medications, initial blood pressure, pulse and point of care tests (tests carried out by the bedside) such as ECGs, X-rays and blood test results which can be analysed in the emergency department.

Patients and carers will play a key role throughout the project, working alongside the research team, to co-create suitable patient materials that explain what SDEC is to increase patient confidence in this service. It is hoped that this project will lead to improved processes that reduce unnecessary bed moves for patients and support better bed planning.