Review of 25 years reveals AI healthtech is beginning to listen to patients
Patients experiences of their health conditions are slowly being integrated into AI studies, a review of 25 years of healthcare publications has found.
Published in the Lancet Digital Health, the new study saw experts from BHP members the University of Birmingham and University Hospitals Birmingham look at more than 600 interventional studies on AI healthcare technologies.
While the team, funded by the National Institute for Health and Care Research (NIHR), found that only 24% of studies have a patient reported outcome element included in their study, there has been an increase in the number in recent years with 2021 and 2022 seeing nearly two thirds of all studies included.
Dr Samantha Cruz Rivera from the Centre for Patient Reported Outcomes Research at the University of Birmingham said: “The opportunities for AI to revolutionise healthcare are only going to make patients’ lives better if those models consider how patients actually feel and respond to healthcare interventions. Our review shows that patient reported outcomes, such as measures of symptom burden and quality of life, are increasingly being incorporated into AI studies which is very encouraging.
“The future could see AI healthcare tech analysing and raising an alert if a patient’s health is declining, but such a future is going to depend on having large-scale patient reported outcome datasets so that AI can support or drive care in a specific condition, and incorporate patient experience. Integrating PROs within AI can support the humanisation of AI for health and ensure that the patient’s voice is not lost in a rush to digitise and automate health care.”
Melanie Calvert, Professor of Outcomes Methodology at the University of Birmingham said: “Managing long term health conditions places a huge burden on patients and their families, but also the NHS and social care system. AI systems can help support patients and healthcare systems to aid decision-making, improve workflow and lead to more efficient care with improved outcomes.
“Encouragingly, we are seeing more research into AI tech solutions for chronic conditions incorporating patient reported outcomes.
“It’s clear that having technology that can analyse and predict patient outcomes to help prioritise care is going to be a part of healthcare’s future. However, we must ensure that the patient reported outcome data used to train the AI systems are applicable to the population they are intended to serve. If we don’t do this, the gaps between advantaged and disadvantaged populations will only get worse.”