Digital Hospitals

Funded by the NHS Cambridge University Hospitals, the Digital Hospitals project aims to exploit the potential of digital technologies to address the key challenges in the delivery of effective and efficient healthcare provision at Cambridge University Hospitals (CUH). The project will also provide guidance towards the development of a long-term digital strategy to support its overall objectives of transforming into a world-class provider of healthcare services and maintaining its position as the leading exemplar within the NHS. The aim of this research programme is to enable a step-change to hospital management by devising, implementing, validating and exploiting Digital Hospitals as an integrated concept with the goal of improving hospital performance, combining patient records, processes, equipment monitoring, occupancy and use of the infrastructure. The pilot study is currently being developed with the Histopathology department of the Addenbrooke’s Hospital.

 

 

Objectives of the research include

  • Identify the requirements for digitalisation of hospitals and build the connection between physical hospitals and their digital twins through methods for (i) capturing asset and process data; (ii) using the data to generate/update the Digital Twin, (iii) enabling efficient asset-data and human-data interaction;
  • Leverage data science and process modelling to (i) quantify uncertainty in system and process behaviour; (ii) couple models in the digital twin to live data from the physical twin, (iii) allow the digital twin to dynamically learn and adapt using the data; and (iv) generate insights about the relationship between hospital systems, processes and patient outcomes;
  • Develop a set of digital solutions to demonstrate the benefits of digitalisation and inform future developments at the hospital;
  • Leverage the strengths of the partnership to exploit the outcomes and disseminate them across the UK.

Please contact Nicola Moretti for further information.

 

Date published

31 October 2022

For further information please contact:

Dr Nicola Moretti

E: nm737@cam.ac.uk

 
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