Project overview
Summary
Over time, health systems face changes. Population grows older or hospitals can perform new treatments. It is difficult to match the resources of hospitals with population needs. If they do not match, waiting times for treatment increase and hospitals become fuller. Hospitals being too full can result in worse care for patients. For example, hospitals might need to cancel surgeries.
Aim(s) of the research
When the usual demand for hospital resources changes, it becomes difficult for hospitals to provide care. We call this turbulence. Our first objective is to define how turbulence can be measured from data. Then, we will use artificial intelligence to understand the causes of turbulence. We will also create models for short-term prediction of turbulence. This will help hospital plan better.
Design and methods used
This project will look at the records of patients in hospitals to understand what resources they use. The data will give us an understanding of how long certain activities take. For example, the recovery from surgery. We will predict when these times are changing using artificial intelligence. This can help hospitals be alert of upcoming changes, so they choose the best way to react.
Patient, public and community involvement (PPCI)
We will engage with the views of public, patients and communities during the project execution phase. We will hold workshops with patient groups that have been to hospital. We will understand their views on the planning services. We will also take into account their ideas when defining turbulence.
Dissemination
This project was co-designed and will be supported by University Hospital Southampton (UHS) and Salisbury Hospital. The results will be disseminated and championed within the partnering institutions, and further presented in workshops involving neighbouring NHS Trusts in Wessex and in the south east and south west of England. We will also publish papers and reports to disseminate the work to a larger audience within the UK and internationally.
Over time, health systems face changes. Population grows older or hospitals can perform new treatments. It is difficult to match the resources of hospitals with population needs. If they do not match, waiting times for treatment increase and hospitals become fuller. Hospitals being too full can result in worse care for patients. For example, hospitals might need to cancel surgeries.
Aim(s) of the research
When the usual demand for hospital resources changes, it becomes difficult for hospitals to provide care. We call this turbulence. Our first objective is to define how turbulence can be measured from data. Then, we will use artificial intelligence to understand the causes of turbulence. We will also create models for short-term prediction of turbulence. This will help hospital plan better.
Design and methods used
This project will look at the records of patients in hospitals to understand what resources they use. The data will give us an understanding of how long certain activities take. For example, the recovery from surgery. We will predict when these times are changing using artificial intelligence. This can help hospitals be alert of upcoming changes, so they choose the best way to react.
Patient, public and community involvement (PPCI)
We will engage with the views of public, patients and communities during the project execution phase. We will hold workshops with patient groups that have been to hospital. We will understand their views on the planning services. We will also take into account their ideas when defining turbulence.
Dissemination
This project was co-designed and will be supported by University Hospital Southampton (UHS) and Salisbury Hospital. The results will be disseminated and championed within the partnering institutions, and further presented in workshops involving neighbouring NHS Trusts in Wessex and in the south east and south west of England. We will also publish papers and reports to disseminate the work to a larger audience within the UK and internationally.
