Google’s artificial intelligence research subsidiary, DeepMind and the Royal Free London NHS Foundation Trust have entered into a five year partnership to develop technologies which can transform patient care.
DeepMind noted that in the UK, National Health Service (NHS) hospitals are still dependent on old technology like pagers, fax machines and paper records.
According to the artificial intelligence arm of Google, the existing IT systems do not meet the clinical needs in a hospital.
The use of outdated technologies are seen as a potential barrier to making clinicians aware of a patient’s condition at the right time.
This can result in the development of serious illnesses and sometimes death of the patient, the British artificial intelligence firm said.
Every year at least 10,000 people in the UK die in hospitals due to preventable causes. And about 40% patients can avoid being admitted to intensive care, had the right clinician was in place at the right time.
According to DeepMind, its partnership with NHS aims to change all of this with a different approach for developing IT for patient care.
Clinicians will be playing a major part in the collaboration to ensure that the right patient information is received by the right clinicians at the right time, thus reducing preventable deaths and illnesses.
Initially, the partnership will build a smartphone app called Streams in collaboration with clinicians which will alert clinicians as soon as the test results show that a patient is at risk of developing acute kidney injury (AKI).
The app will provide nurses and doctors with test results of all of their patients. This feature will be particularly helpful where faster care is needed to treat acute problems such as kidney injury or sepsis.
It will also feature patient’s medical history, which will help doctors to know about the condition of the patient and giving the right care.
Allocation of work will also be done through the app, replacing outdated modes for communication such as the pager or by fax by sending notifications.
DeepMind says that adding these features in one app could save millions of hours every year wasted in manual communication and millions of pounds for the NHS.
DeepMind co-founder Applied AI head Mustafa Suleyman said: “Over the course of the next five years, we’re going to expand Streams to cover other illness where early intervention is key and technology can ensure this happens.
“We think that Streams could also be used to help patients at risk from sepsis and other causes of organ failure, where signs of deterioration are often difficult for clinicians to spot, and where early intervention can be the difference between life and death.”
He continued: “When it’s fully built, we believe that this will speed up the time to alert nurses and doctors to patients in need down from hours to a few seconds.
“And by freeing up clinicians’ time from juggling multiple pager, desktop-based and paper systems, it should redirect over half a million hours per year away from admin and towards direct patient care at the Royal Free alone.”
In addition, DeepMind will also develop a new infrastructure where the Royal Free administrators can easily know when, where, by whom and for what purpose patient information was accessed.
The infrastructure supporting Streams will be built on interoperable standards. This can allow other operators to develop new services which can be easily deployed.
Work on Streams started just over a year ago. It will undergo prototype testing and registered with the Medicines and Healthcare products Regulatory Agency (MHRA).
The first version of Streams is expected to be deployed to clinicians across the Royal Free Hospital sites early in 2017.
Royal Free London CEO David Sloman said: “We are hugely excited by the opportunity this partnership presents to patients and staff. We want to lead the way in healthcare technology and this new clinical app will enable us to provide safer and faster care to patients – which will save lives.
“Doctors and nurses currently spend far too much time on paperwork, and we believe this technology could substantially reduce this burden, enabling doctors and nurses to spend more time on what they do best – treating patients.”