Scientists have developed a new artificial intelligence (AI) model that can predict how long a person with a learning disability needs to stay in hospital, which could help improve care and reduce health inequality.
The model was developed by computer scientists at Loughborough University as part of the DECODE project, which aims to offer valuable insights that could improve resource planning and tackle healthcare challenges for people with a learning disability and multiple health problems.
The findings of the artificial intelligence analysis, published in Frontiers in Digital Health, found that cancer is the leading cause of hospital admissions, and epilepsy is the most frequent inpatient-treated condition for people with learning disabilities and multiple health conditions.
On average, people with learning disabilities and multiple health conditions stay in hospital for three days and stays exceeding 129 days are often linked to mental illness.
Patients with stays of four or more days are more likely to be over 50 years old, live in more deprived areas, have obesity or are less physically active. They are also more likely to have more health conditions, a history of long hospital stays, or previous treatment for long-term conditions.
The researchers used GP and hospital data from over 9,600 patients with learning disabilities and multiple health conditions to develop an artificial intelligence model capable of predicting hospital stay lengths within the first 24 hours of admission.
The AI model was tested using the dataset it was trained on and was 76% effective in distinguishing between patients likely to have prolonged hospital stays and those who would be discharged sooner.
Professor Georgina Cosma, an expert in AI for healthcare at Loughborough University and DECODE co-investigator, said: “The model generates predictions by assessing factors such as a patient’s age, medication history, lifestyle, and existing health conditions. With early and accurate predictions, hospitals can plan better and provide more personalised care, ensuring fair treatment for all patients.”
The insights from this study and the wider DECODE project will be used to support the NHS in developing risk prediction algorithms to assist clinicians in decision-making.
Dr Satheesh Gangadharan, Consultant Psychiatrist with the Leicestershire Partnership NHS Trust and the DECODE Co-Principal Investigator, added: “We are in the process of applying this knowledge into practice as well as sharing it widely.
“While hospital care is an important part of healthcare provision, we are exploring ways to minimise the need for hospitalisation by exploring where health interventions could be delivered earlier and people with learning disabilities could be engaged in their care better.”
The data used to train the artificial intelligence model came from GPs and hospitals in Wales. As part of their next steps, the researchers are applying the model to datasets from hospitals in England to assess whether similar patterns emerge across different populations.
