Pandemic Respiratory Infection Emergency System Triage
Respiratory infections, such as influenza or the corona virus, affect the lungs and airways, causing symptoms including fever, sore throat, coughing and breathing difficulties. If a new strain of the virus becomes widespread across many countries, this can be classified as a pandemic. During a pandemic, more patients attend hospital services and require investigation or admission, which puts a huge strain on the NHS.
Patients who contact emergency services (via NHS 111, emergency ambulance services or emergency departments) with a suspected pandemic respiratory infection need to be rapidly assessed to determine the severity of their illness, and whether they need to be admitted to hospital. This process is called "triage". Triage often uses methods such as scores or decision rules. These have been developed and are ready for use in a pandemic, but we don’t know how well they can correctly predict who needs to be admitted to hospital, and who does not.
We aim to:
- Optimise the triage of people using the emergency care system with suspected respiratory infections during a pandemic
- Identify the most accurate triage method for predicting severe illness among patients attending the emergency department with suspected respiratory infection
Our specific objectives after the pandemic are:
- To determine the discriminant value of emergency department triage methods for predicting severe illness in patients presenting with suspected pandemic respiratory infection
- To determine the discriminant value of presenting clinical characteristics and routine tests for identifying severe illness
- To determine the independent predictive value of presenting clinical characteristics and routine tests for severe illness
- To develop new triage methods based upon presenting clinical characteristics alone or presenting clinical characteristics, electrocardiogram (ECG), chest X-ray and routine blood test results, depending upon the data available and the predictive value of variables evaluated in objective 3
The PRIEST study uses patient data from the early phases of a respiratory infection pandemic, such as for COVID-19, to test how well existing triage methods predict serious complications patients. The study will also Identify cases where the triage methods did not predict serious complications or recommended unnecessary hospital admission, and where possible modify triage methods or develop new triage methods that predict serious complications better than existing methods.
To do this, during a respiratory infection pandemic recording we will be recording medical details in a standardised way from patients with suspected respiratory infection in a standard, using a triage form. We will then using hospital records to follow these patients up to 30 days on to find out if they die or suffer a life-threatening complication.
We will evaluate triage methods used to determine whether a patient suspected to be infected with pandemic respiratory infection should be admitted to hospital or not, and whether they should be admitted to intensive or high dependency care. These may include the CURB-65 score, PMEWS, the swine flu hospital pathway, SMART-COP, the SwiFT score and any new methods developed before the next pandemic. We will also develop two new triage methods based upon (a) presenting clinical characteristics alone and (b) presenting clinical characteristics, electrocardiogram (ECG), chest X-ray and routine blood test results.
The results of this study can be used in the following stages of the pandemic, to produce a guideline or rule to help decide which patients would benefit from being admitted to hospital. The findings can also help doctors and nurses identify which individual patients may go on to develop serious complications. We may also be able to identify which patient characteristics are associated with a higher risk of serious complications, such as age or underlying health conditions. For example, in the 2009 influenza pandemic, it was found that pregnant patients, and those suffering from obesity, were at higher risk of developing complications.
The risks to patients involved in this study are very low, because the project will not involve any change to the way patients are assessed or treated. Information will be gathered in a way that aims to help doctors and nurses, and does not interfere with patient care. The way we collect information about patients has been tested during a winter flu season to confirm this.
Most personal details will be removed from information that leaves a hospital. We are only recording NHS numbers and ambulance incident numbers so that we can track how patients move through NHS services. Identifiable information, such as patient’s names, will only be available to local trained nurses who work alongside the care teams.
We will not be asking patients for written consent to use their data in the study because this could cause delays, which may be harmful in a pandemic. However, we will inform patients of the study, and let them know that they can remove their data if they wish.
Patients can contact one of the hospitals involved in the study to ask for their information to be removed from the study. This approach has worked well in previous studies, and was approved by an independent Research Ethics Committee and the National Information Governance Board. If you are included in the study at a hospital a member of hospital staff will hand you an information leaflet ways you can opt out at the time, either by filling out the leaflet and handing it back or by contacting a local member of the research team.
For more information on your rights in the study, and the locations where the research is being conducted please got to our Privacy notice located at: https://docs.google.com/document/d/e/2PACX-1vTaRqL0fIv1APjVz7YFL8wLuFiYy6SX2ftJXDz4EyvtlrizbHaARoDzqDbxt8eKyVInxK_FH_MStSjZ/pub
Patients contacting NHS 111 or calling 999 with suspected COVID-19 infection need to be rapidly assessed to determine if they need an emergency ambulance. Those attended by an emergency ambulance then need to be quickly assessed to determine who needs to be taken to hospital and who can be advised to look after themselves at home. This process is known as "triage" and may use methods, such as scores or decision rules, which have been developed to assess the severity of illness and predict which patients are at risk of life-threatening complications. It is not currently known whether the triage processes used by NHS 111 and 999 services accurately identify who needs an emergency 999 ambulance and who then needs to be taken to hospital.
We plan to use patient data from the early phases of the pandemic to:
- Test how accurately the triage methods used by NHS 111 and emergency ambulance responders identify people who need hospital admission,
- Identify cases where the triage methods recommended unnecessary hospital admission or did not predict serious complications,
- Use data collected by ambulance responders during their assessment to determine whether triage scores can improve triage decisions.
In order to assess the triage methods for NHS 111 and the emergency ambulance services, we will collect information that is routinely recorded when someone phones NHS 111 or is attended by a 999 ambulance, and then link this information to hospital records to determine whether the patient dies or suffers life-threatening illness.
The results of our study can be used to produce guidance for NHS 111 and 999 call handlers to help them decide which patients require an emergency ambulance, and guidance for emergency ambulance responders to help decide if patients need treatment in hospital. This guidance can be used in subsequent phases of the pandemic.
The risks to patients involved in the study are very low. The project will not involve any change to the way calls to NHS 111 or 999 are handled, or the way emergency ambulances respond to calls. We will use identifiable information (patient’s NHS number, date of birth, postcode and full name) to link ambulance data to hospital data and death records. We need to do this to find out what happens after someone has had contact with the ambulance service. This is particularly important in allowing us to identify patients who were advised to stay home who later deteriorated or needed to be treated in hospital. We have strict procedures in place to minimise access to the identifiable information. Only specific staff members, who are involved in collecting the ambulance service data, or linking the ambulance data with the hospital data, will see identifiable information. Identifiable data will be stored securely and deleted as soon as possible after the data has been linked. It will not be used for any other purposes or accessed by anyone else at any time.
As we will be using routinely recorded information, which has already been collected by the ambulance service, we will not be able to ask patients for consent to use their data. However, patients can contact the PRIEST study team (firstname.lastname@example.org) to “opt out” of the study and to request that their information is not included in the study. In addition, patients national opt out choices will be respected and data for patients who have opted out will not be included in the study. Further information on the national opt out service is available here: https://www.nhs.uk/your-nhs-data-matters/.
The PRIEST study has collected data from 20508 people attending emergency departments in the UK, as of 02 June 2020. We provide a brief overview of the characteristics of the cohort to date. These are interim data, intended to assist those responsible for delivering emergency department care during the ongoing pandemic. Definitive findings (including outcome data) will be published in due course.
The cohort currently has a mean age of 59.2 years, 10238 (49.9%) are female and 10069 (49.1%) are male. The most common symptoms are shortness of breath 14532 (70.9%), cough 12372 (60.3%) and fever 10479 (51.1%). Some 4209 (20.5%) of the cohort have previous heart disease, 1730 (8.4%) have renal impairment, 3151 (15.4%) have asthma, 3347 (16.3%) have another chronic lung disease, 5770 (28.1%) have hypertension, 3727 (18.2%) have diabetes, 1005 (4.9%) have active malignancy, 576 (2.8%) are immunosuppressed, 498 (2.4%) are receiving steroid therapy and 5555 (27.1%) have no long-term medical conditions recorded.
COVID-19 was considered to be the most likely diagnosis in 13343 (65.1%) of the cohort during emergency department assessment.
This project is funded by the National Institute for Health Research Health Technology Assessment (NIHR HTA) Programme (project number 11/46/07). Any views or opinions expressed are those of the authors and do not necessarily reflect those of the HTA programme, NIHR, NHS or the Department of Health.
|Professor Steve Goodacre||ScHARR||Chief Investigator||+44 114 222 email@example.com|
|Dr Benjamin Thomas||ScHARR||Study Manager||+44 114 22 firstname.lastname@example.org|
|Katie Biggs||ScHARR||CTRU Oversight||+44 114 22 email@example.com|
|Ellen Lee||ScHARR||Statistician||+44 114 222 firstname.lastname@example.org|
|Amanda Loban||ScHARR||Data Management||+44 114 222 email@example.com|
|Katie Ridsdale||ScHARR||Trials Support Officer||+44 114 222 firstname.lastname@example.org|
|Sarah Connelly||ScHARR||Research Assistant||+44 114 222 email@example.com|
|Emma Young||ScHARR||Research Assistant||+44 114 222 firstname.lastname@example.org|
Project management group
|Dr Kirsty Challen||Lancashire Teaching Hospitals NHS Foundation Trust||Consultant in Emergency Medicineemail@example.com|
|Dr Andrew Bentley||University Hospital of South Manchester||Critical Care Expertise||+44 161 291 firstname.lastname@example.org|
|Dr Darren Walter||University Hospital of South Manchester||Expert in Pandemic Emergency Planning||+44 161 291 email@example.com|
|Dr Ian Maconochie||St Mary's Hospital, London||Expert in Paediatric Emergency Medicine||+44 207 886 firstname.lastname@example.org|
|Dr Chris Fitzsimmons||Sheffield Children's Hospital||Expert in Paediatric Emergency Medicine||+44 114 271 email@example.com|
|Andrew Lee||ScHARR, The University of Sheffield||Senior Clinical University Teacher||+44 114 222 firstname.lastname@example.org|
|Fiona Lecky||ScHARR, The University of Sheffield||Principle Investigator||+44 114 222 email@example.com|
|Tim Harris||Barts Health NHS Trust||Principle Investigatorfirstname.lastname@example.org|
|Sheffield Teaching Hospitals NHS Foundation Trust, Northern General Hospital||Professor Steve Goodacre|
|Sheffield Children's NHS Foundation Trust, Sheffield Children's Hospital||Chris Fitzsimmons|
|Salford Royal NHS Foundation Trust, Salford Royal Hospital||Fiona Lecky|
|York Teaching Hospital NHS Foundation Trust, York Hospital||Joanne Ingham|
|York Teaching Hospital NHS Foundation Trust, Scarborough General Hospital||Dr Richard Smith|
|King's College Hospital NHS Foundation Trust, King's College Hospital||Fleur Cantle|
|Barnsley Hospital NHS Foundation Trust, Barnsley Hospital||Professor Suzanne Mason|
|University Hospitals Plymouth NHS Trust, Derriford Hospital||Dr Simon Horne|
|Royal Berkshire NHS Foundation Trust, Royal Berkshire Hospital||Dr Liza Keating|
|Dorset County Hospital NHS Foundation Trust, Dorset County Hospital||Dr Tamsin Ribbons|
|Gloucestershire Hospitals NHS Foundation Trust, Gloucestershire Royal Hospital||Tanya De Weymarn|
|The Royal Wolverhampton NHS Trust, New Cross Hospital||Jagtar Pooni|
|The Shrewsbury & Telford Hospital NHS Trust, Princess Royal Hospital and Royal Shrewsbury Hospital||Dr Adrian Marsh|
|University Hospital North Midlands NHS Trust, Royal Stoke Hospital||Dr Mark Harrison|
|Southend University Hospital NHS Foundation Trust, Southend Hospital||Bernard Hadebe|
|Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital||Dr Melanie Darwent|
|NHS Lothian, Royal Infirmary of Edinburgh||Dr Alasdair Gray|
|Mid and South Essex NHS Foundation Trust, Broomfield Hospital||Dr Steve Jenkins|
|Newcastle upon Tyne Hospitals NHS Trust, Royal Victoria Infirmary||Dr John Wright|
|Manchester University NHS Foundation Trust, Manchester Royal Infirmary and Royal Manchester Children's Hospital||Dr Rick Body|
|Liverpool University Hospitals NHS Foundation Trust, Aintree University Hospital||Dr Abdo Sattout|
|Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital||Adrian Boyle|
|Nottingham University Hospitals NHS Trust, Queen's Medical Centre||Dr Frank Coffey|
|Northern Ireland, Craigavon Area Hospital||Lesley Ann Funston|
|Aneurin Bevan University Health Board, Royal Gwent Hospital and Nevill Hall Hospital||Dr Ashkok Vaghela|
|The Queen Elizabeth Hospital King's Lynn NHS Foundation Trust, Queen Elizabeth Hospital||Dr Nam Tong|
|Kings College Hospital NHS Foundation Trust, King's College Hospital||Dr Rob Pinate|
|Ashford and St Peter's Hospital NHS Foundation Trust, Ashford Hospital and St Pater's Hospital||Dr Jessica Law|
|Lancashire Teaching Hospitals NHS Trust, Royal Preston Hospital||Dr Kirsty Challen|
|North Tees and Hartlepool Foundation Trust||Ignacio Cardona|
|Epsom and St Helier University Hospitals NHS Trust, Epsom Hospital and St Helier Hospital||Rebecca MacFarlane|
|Bart's Health NHS Trust, St Bartholomew's Hospital||Ben Bloom|
|Hull University Teaching Hospitals NHS Trust, Hull Royal Infirmary||William Townend|
|Great Western Hospitals NHS Foundation Trust, Great Western Hospital||Suzannah Pegler|
|County Durham and Darlington NHS Foundation Trust||Amanda Cowton|
|St George's University Hospital NHS Foundation Trust, St George's Hospital||Heather Jarman|
|South Tees Hospitals NHS Foundation Trust, The James Cook University Hospital||David Chadwick|
|The Royal Bournemouth and Christchurch Hospitals NHS Foundation Trust, Royal Bournemouth Hospital||Laura Purandare|
|Sherwood Forest Hospital NHS Foundation Trust||Jill Woodhead|
|East Sussex Healthcare NHS Trust||Shaymau Habeeb|
|Bolton NHS Foundation Trust, Royal Bolton Hospital||Richard Parris|
|Surrey and Sussex Healthcare Foundation Trust, East Surrey Hospital||Christine Dixon|
|Lewisham and Greenwich NHS Trust||Hannah Kelly|
|East Lancashire Hospital NHS Trust, Royal Blackburn Teaching Hospital||Raj Garlapati|
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