Current visiting times

After suspending visiting earlier in the year, we are now able to offer limited visiting to some wards at the discretion of the nurse in-charge.”

Read more on visiting times...


Messages for loved ones and keeping in touch

We recognise the impact that a long stay in hospital can have on families and the importance of maintaining strong communication.  Our ward staff are keeping in touch with patients’ next of kin directly and our Patient Advice and Liaison Service (PALS) can help pass on personal messages from family and friends.

Read more information about messages for loved ones…

Current visiting times

After suspending visiting earlier in the year, we are now able to offer limited visiting to some wards at the discretion of the nurse in-charge.”

Read more on visiting times...


Messages for loved ones and keeping in touch

We recognise the impact that a long stay in hospital can have on families and the importance of maintaining strong communication.  Our ward staff are keeping in touch with patients’ next of kin directly and our Patient Advice and Liaison Service (PALS) can help pass on personal messages from family and friends.

Read more information about messages for loved ones…

During your stay in hospital you will meet a number of different members of staff.  All members of staff wear name badges, but if you are not sure who someone is or what they do, please feel free to ask them to introduce themselves and explain what they do. 

If you have any questions about your treatment, please ask a doctor or a nurse.

There are lots of opportunities for you to get involved with the Trust, from volunteering to attending our public meetings, our Annual General Meeting or our hospital open day which is held every year.

Latest trials and news

New algorithm will improve bowel-cancer patient care

Date: 12 April 2022

An algorithm which can predict how long a patient might spend in hospital if they’re diagnosed with bowel cancer could save the NHS millions of pounds and help patients feel better prepared.

Experts from Portsmouth Hospitals University NHS Trust (PHU) and University of Portsmouth have used artificial intelligence and data analytics to predict the length of hospital stay for bowel cancer patients, whether they will be readmitted after surgery, and their likelihood of death over a one-month or three-month period.

The intelligent model will allow healthcare providers to design the best patient care and prioritise resources.

Bowel cancer is one of the most common types of cancer diagnosed in the UK, with more than 42,000 people diagnosed every year.

Jim Khan, consultant surgeon at PHU, was involved in the research and said: “The new algorithm will allow surgeons to predict the outcomes using artificial intelligence and the scope is very big, ranging from cancer survival to length of stay and complications. We aim to provide clinics a simple tool in the palm of their hands to get this valuable information.”

Professor of Intelligent Systems, Adrian Hopgood, is another lead author on the new paper. He said: “It is estimated that by 2035 there will be around 2.4 million new cases of bowel cancer annually worldwide. This is a staggering figure and one that can’t be ignored. We need to act now to improve patient outcomes.

“This technology can give patients insight into what they’re likely to experience. They can not only be given a good indication of what their longer-term prognosis is, but also what to expect in the shorter term.

“If a patient isn’t expecting to find themselves in hospital for two weeks and suddenly they are, that can be quite distressing. However, if they have a predicted length of stay, they have useful information to help them prepare.

“Or indeed if a patient is given a prognosis that isn’t good or they have other illnesses, they might decide they don’t want a surgical option resulting in a long stay in hospital.”

Bowel cancer (also known a colorectal cancer) affects the large bowel, which is made up of the colon and rectum. The cost of diagnosing and treating patients is significant and the economic impact on healthcare systems is immense.

The study used data taken from a database of over 4,000 bowel cancer patients who underwent surgery between 2003 and 2019. It looked at 47 different variables including age, weight, fitness, surgical approaches, and mortality.

“If we could attract funding, we would love to get together with other bowel cancer centres so we have access to even bigger datasets. With machine learning, the simple rule is the more data the better,” Professor Hopgood said.

“Everyone I’ve spoken to in the health domain thinks that artificial intelligence will help them do a better job and we hope this research will do exactly that – by providing more accurate predictions, the health service can allocate the best resources to each patient and improve patient care.”

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