The Magnificent Free Hospital
Healthcare professionals can now detect one of the National Health Service’s (NHS) “biggest killers” in minutes to a certain extent than hours due to the use of a new app.
The app, which has been developed by Alphabet’s DeepMind Health together with the Royal Free London NHS Basis Trust (RFL), is used to help identify patients who are at risk of something called “acute kidney injury”, or AKI.
The RFL described severe kidney injury as a “silent killer” because it could “often be diagnosed late” and was hard to predict.
In an announcement Wednesday the RFL declared the goal of the app, which is called Streams, was to provide “the right data to the right clinician at the right time.”
When examination results indicate that a patient is in danger of becoming very ill with AKI, doctors and nurses get immediate notifications on their phones.
The RFL weighted that an evaluation of the Streams app, conducted by University College London, found that clinicians using it could “react to to urgent AKI cases in 14 minutes or less”. With existing systems, this could take “many hours.”
This is significant, because speed is crucial when diagnosing conditions such as AKI, which accounts for 100,000 deaths per year in the U.K. and bring ins the NHS £1.2 billion ($1.45 billion).
In a statement Wednesday Chris Laing, a consultant nephrologist involved in the project and its approximation, said the app enabled the monitoring of patients’ kidney function “through real time analysis of blood tests 24/7.”
“If a likely change in kidney function in a patient is detected, at any time or anywhere at the Royal Free Hospital, a specialist will be intimated and the case will be reviewed, in-application, in a matter of minutes, with follow-up bedside assessment as required,” Laing united.
The NHS has been running since 1948. It’s guided by principles that also underpinned its launch — that it should go through the needs of all, be free at the point of delivery, and based on clinical need rather than a person’s ability to pay.