The US Department of Veterans Affairs (VA) has formed a medical research partnership with artificial intelligence (AI) research firm DeepMind to address the issues associated with patient deterioration during hospital care.
The firms will leverage AI to develop machine learning algorithms to identify risk factors related to patient deterioration, which is reportedly responsible for 11% of all in-hospital deaths.
To detect the risk factors, the firms plan to analyse patterns from approximately 700,000 historical, depersonalised medical records.
The newly developed AI algorithms are expected to aid in predicting the onset of patient deterioration.
VA Secretary David Shulkin said: “Clinicians need to be able to identify risks to help prevent disease.
“This collaboration is an opportunity to advance the quality of care for our nation’s veterans by predicting deterioration and applying interventions early.”
How well do you really know your competitors?
Access the most comprehensive Company Profiles on the market, powered by GlobalData. Save hours of research. Gain competitive edge.
Your download email will arrive shortly
Not ready to buy yet? Download a free sample
We are confident about the unique quality of our Company Profiles. However, we want you to make the most beneficial decision for your business, so we offer a free sample that you can download by submitting the below formBy GlobalData
The VA and DeepMind will initially focus on improving the existing algorithms used for the detection of acute kidney injury (AKI), one of the most common conditions associated with patient deterioration.
At a later stage, the firms plan to extend the research to other signs of patient deterioration in order to ensure better care for more patients.
DeepMind co-founder Mustafa Suleyman said: “This project has great potential intelligently to detect and prevent deterioration before patients show serious signs of illness.
“Speed is vital when a patient is deteriorating: the sooner the right information reaches the right clinician, the sooner the patient can be given the right care.”