Emergency in A&E
The NHS’s Accident and Emergency service is one of the most significant sectors in the NHS, where patients depend on the performance of A&E for life-or-death situations. In A&E, there are 3 types of departments which get progressively less acute from type 1 to 3. Type 1 consists of major emergencies where doctors lead a 24-hour service. Type 2 departments have consultant-led facilities for specific conditions, and type 3 departments treat minor injuries and illnesses, such as fractures and infections.
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Many consider A&E waiting times as a barometer for the overall performance of the NHS and social care system because it compounds the state of the NHS, as its quality reflects a multitude of other departments like the ambulance service, primary care, community-based care and social care services.
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A&E service is in a dire state. As highlighted by Lord Darzi’s report, it is evident something needs to be done to alleviate the backlog of patients and the waiting times they face. The report shed light on the rapid decline of A&E’s productivity. In 2010, 94% of patients needing type 1 or type 2 services were seen within 4 hours. However, by 2024, this percentage decreased to just 60%. The report highlighted that as of 2024, 10% of patients needing A&E services are having to wait for over 12 hours, which has been suspected to cause an extra 14000 deaths annually, according to the Royal College of Emergency Medicine.
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These graphs from The King’s Fund highlight that the NHS has been unable to meet the four-hour standard for the past decade, leading to NHS satisfaction plummeting significantly by 14% from 2019 to 2022.
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The reason for these concerning statistics is prevalently due to the rising number of emergency admissions to hospitals. With more people going to the hospital for various reasons, like the ageing population demographic, or the increase in chronic health conditions, more pressure has been applied on the NHS, leading to bed shortages and a massive strain on staff. One of the clearest indications of the link between A&E waiting times and hospital bed occupancy is the number of patients who experience trolley waits- the time between a decision being made in A&E to admit the patient and the patient being admitted to a hospital bed. These waits have substantially increased from less than 150 in 2014 to 150,000 in 2024. This is due to an increase in delayed discharge, where patients who are ready to be released from the hospital are unable to leave for external reasons, primarily due to a lack of social care, signifying the importance of improving social care as it has a direct impact on the healthcare system. Therefore, the government must not only invest in the NHS, but also extend their investments to social services to strengthen the integration between different sectors to improve patient centred care.
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Another key aspect of seamless movement through A&E is the efficiency of ambulances. The Addendum to the NHS Constitution requires all ambulance trusts to respond to Category 1 calls in 7 minutes, which are time-critical emergencies and life-threatening events where immediate intervention is required.
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The graph above from Nuffield Trust displays that the last time the 7-minute target was met was in April 2021. Longer ambulance wait times can have a serious effect on A&E as more time waiting leads to patient deterioriation, leading to a more intensive action plan on their arrival to the hospital, meaning more time-consuming, complex procedures and treatment will be required.
A potential solution to ambulance times is the implementation of AI into ambulance dispatch systems. Though this would require lots of money and time for training, it could be a great tool if used effectively. An article on Artificial Intelligence in prehospital emergency Canadian healthcare emphasised how this technology could be utilised. New Brunswick introduced a computer-aided dispatch system which was able to recognize 36% of out-of-hospital cardiac arrest emergencies within the first minute of the call, compared to 25% for human dispatchers, and the AI was able to identify the OHCA (out-of-hospital cardiac arrest) an average of 28 seconds faster, which is a critical amount of time that could determine the difference between life or death for a patient. AI was also instrumental in translation and interpretation. The technology was able to detect calls in foreign languages and translate the call to the operator, meaning details were conveyed accurately and swiftly, decreasing the detrimental effects of language and communication barriers.
The integration of AI to improve A&E could be a viable future solution. However currently, to tackle the A&E crisis, the NHS’ Long Term Plan has announced the introduction of Same Day Emergency Care (SDEC) centres in every hospital with A&E services. This will ensure patients receive care on the same day as their hospital arrival. SDEC centres have specialists available to assess, diagnose and treat patients who do not have critical conditions and who do not need to stay overnight. Once treated, patients are discharged the same day and can be offered follow up appointments, either virtually or in person. This is not only beneficial for the patients who have the comfort of going home, but also for hospitals as it means more beds are accessible for those who need them most.
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References:
https://www.kingsfund.org.uk/insight-and-analysis/data-and-charts/patient-waiting-times
https://www.england.nhs.uk/urgent-emergency-care/same-day-emergency-care/
https://www.ncbi.nlm.nih.gov/books/NBK596747/
https://www.nuffieldtrust.org.uk/resource/ambulance-response-times
