Hello, Welcome to our first Article of 2022! We hope you all had a lovely Christmas and New Year. It’s great to be back writing an Article to share with you. Over the past few weeks we touched a lot on the subject of short staff which has led to busy hospitals especially during COVID. This week, we will be talking about Improving hospital bed allocation using AI. 

NHSx recently posted about improving hospital bed allocation using AI. A case study by Kettering General Hospital reached out to the NHS AI Lab Skunkworks team to request support exploring their Al to improve bed management.  The NHS Al Lab Skunkworks team run short-term projects to investigate the use of AI for improving efficiency and accuracy in health and care.

Their vision is that organisations in the health and care system will be able, through practical experience, to understand, build, buy, deploy, support and challenge AI solutions. Their vision was to use AI to achieve the “Right patient in the right bed receiving the right care at the right time”. In this 14-week project, researchers explored how artificial intelligence (AI) techniques can be used to generate options for moving patients in a way that supports the human team in making the best possible choices. 

Admitting patients into hospitals is a difficult task as it is. The current way of admitting patients to beds is managed by a human team that depend on individual expertise which can be difficult. The challenges of this task include:

  • Demands and capacity is complex 
  • not all patients or hospital beds are the same
  • Staff are overwhelmed with options and expertise of staff. 

The NHS AI lab Skunkworks funded and supported an Al investigation with the team at Kettering General Hospital. Using a tool that predicts patient flow and provides bed allocation options for human decision makers, researchers examined whether AI could facilitate better, faster decision-making. The potential benefits included: high-quality, consistent bed allocation, improved patient experience, improved workforce efficiency and staff satisfaction, reductions in inpatient length of stay and many more. 

The results of all the investigations and trials that were made in 14 weeks provided staff with the ability to visualize a virtual hospital. Along with including occupancy rates and demand for beds. It gives them an explanation and demonstration of what a fully developed allocation model could offer. The investigation’s suggestions to the user and the model can be tested on a wide range of patients with a variety of attributes and constraints, and its performance can be validated.

To read a more indepth exploration of improving hospital bed allocation using AI, visit NHSX.


We at SQ heavily support using AI as we do too, we wouldn’t be where we are today without it! 


Next week we will be interviewing our new Business Development Manager, Samantha Heley. So stay tuned for that!

Meg Wheller
Media Marketer, Spatial Quotient