31 July 2019
Detection of one of the biggest killers in the NHS has been cut from hours to minutes at the Royal Free Hospital in London thanks to the introduction of a new mobile app.
That is one of the key findings of an evaluation of Streams – a secure alerting tool which has been developed by technology experts at DeepMind Health in collaboration with clinicians at the Royal Free London NHS Foundation Trust (RFL) to help identify patients at risk of acute kidney injury (AKI).
According to the evaluation led by UCL, the findings of which were published today in Nature Digital Medicine and the Journal of Medical Internet Research, the app improved the quality of care for patients by speeding up detection and preventing missed cases. Thanks to Streams, clinicians were able to respond to urgent AKI cases in 14 minutes or less - a process which, using existing systems, might otherwise have taken many hours.
It also concluded that the app reduced the cost of care to the NHS – from £11,772 to £9,761 for hospital admission for a patient with AKI.
According to the evaluation, the app has improved the experience of clinicians responsible for treating AKI, saving them time which would previously have been spent trawling through paper, pager alerts and multiple desktop systems.
One clinician who was interviewed for the study said the app ‘has definitely saved people’s lives’, another added ‘it must save at least a couple of hours in a day’ and one respondent said the app sped up the time taken for a specialist review.
Dr Chris Streather, Royal Free London chief medical officer and deputy chief executive, said: “The findings of the Streams evaluation are incredibly encouraging and we are delighted that our partnership with DeepMind Health has improved the outcomes for patients.
“Digital technology is the way forward for the NHS. In the same way as we can receive transport and weather alerts on our mobile devices, doctors and nurses should benefit from tools which put potentially life-saving information directly into their hands.
“In the coming months, we will be introducing the app to clinicians at Barnet Hospital as well as exploring the potential to develop solutions for other life-threatening conditions like sepsis.”
Acute Kidney Injury – known as a silent killer because it can often be diagnosed late and is often hard to predict – contributes to nearly 20% of all hospital admissions, accounts for 100,000 deaths every year in the UK, and costs the NHS £1.2 billion annually.
Clinicians at the RFL worked closely with experts at DeepMind Health who developed Streams with the aim of improving outcomes for patients by getting the right data to the right clinician at the right time. Like breaking news alerts on a mobile phone, the technology notifies nurses and doctors immediately when test results show a patient is at risk of becoming seriously ill with AKI, and provides information they need to take action.
Clinicians face real challenges when it comes to detecting conditions like AKI – patients deteriorate rapidly and, without the app, it could be hours before this was picked up due to the limitations of current NHS technology and the reliance on manual observations and intuition. Approximately one in three deaths from AKI may be preventable if clinicians are able to intervene earlier and more effectively.
The service evaluation and qualitative study compared data from four months after implementation of Streams to data from an eight month period prior to the implementation of Streams. Data was also included from a comparator site at RFL that did not implement Streams. Over the cumulative 12 months, the study evaluated 11,840 AKI alerts.
- Recognition of AKI improved from 87.6% to 96.7 % for emergency cases
- The average time from blood test results being available suggesting AKI to an in-application case review by a specialist was 11.5 minutes for emergency patients with AKI and 14 minutes for admitted patients. Previously it was not possible for specialists to review AKI cases arising across the hospital in real time and it could have taken several hours to identify
- Key treatment was delivered faster
- Healthcare costs reduced by just over £2,000 for AKI patients treated (from £11,772 to £9,761)
- For emergency patients there were significant improvements in the outcome trend of renal recovery and admissions to critical care and the kidney unit after AKI. There was also a significant reduction in the global hospital cardiac arrest rate. These improvements at the implementation site were not, however, statistically different from the parallel improvements seen at the comparator site.
Dr Dominic King, lead at DeepMind Health, said: “We’re proud to see these findings demonstrate how modern digital technologies can support nurses and doctors in delivering faster, better care at the same time as delivering cost savings for the hospital. We’re excited to now explore how earlier warnings of patient deterioration could improve outcomes for more patients at the Royal Free London.”
Positive feedback from clinicians interviewed by researchers for the qualitative evaluation related to the speed with which clinical data was available, the ease of it being accessed on a mobile device, efficiencies in care and communication enabled by the app and the clinical impact of detecting sick patients earlier and being able to intervene.
- ‘The speed at which it happened was impressive. I happened to be in A&E and got the alert of someone with severe AKI. The patient was admitted to a specialist ward within two or three hours which I don’t think would have happened without the app. I think it streamlines care and speeds up the time in which they get specialist renal review.’
- ‘I have personally noticed that when patients are flagged up on the application…when we get involved management changes. It has definitely saved people’s lives.’
- ‘Being able to look up the results for anyone in the hospital wherever you are is unparalleled. As a doctor you have to integrate what you know about patients at the time of seeing them. So if you could literally have this phone, look at the results, go and see the patient…or even look at it while seeing them…it must save at least a couple of hours in a day.’
Dr Chris Laing, consultant nephrologist, who clinically led the implementation of the Streams project and co-led the evaluation, said: “AKI is common, harmful, costly and may present across multiple clinical settings. It is often an early sign that a patient is becoming gravely Ill.
“Thanks to Streams we are able to monitor the kidney function of patients through real-time analysis of blood tests 24/7. If a potential change in kidney function in a patient is detected, at any time or anywhere at the Royal Free Hospital, a specialist will be notified and the case will be reviewed, in-application, in a matter of minutes, with follow-up bedside assessment as required.”
Mary Emerson, lead nurse specialist for the RFL patient at risk and resuscitation team, said: “The Streams app has made a huge difference to clinicians’ ability to respond rapidly to patients who are developing acute kidney injury. This means we can deliver treatment more quickly, and also identify deteriorating patients much earlier. The mobile technology is easy to use and fits with the way healthcare is delivered today. I’m excited about the possibilities this approach to alerting might have for other conditions and clinical teams.”
Picture caption: Mary Emerson, lead nurse specialist for the patient at risk and resuscitation team, with patient Edgar Ferrante.