Embracing AI in healthcare
By Katriona Brooksbank, Research and Innovation Lead for the West of Scotland Innovation Hub
Artificial Intelligence has developed rapidly and is changing many aspects of the modern world.
In healthcare, the use of AI has the potential to transform patient pathways and outcomes by improving care and making diagnostic processes faster and more sophisticated.
Last month, the Prime Minister announced plans for an AI revolution, pitching the UK as a future world leader on Artificial Intelligence.
At the West of Scotland Innovation Hub (WoSIH), hosted by NHS Greater Glasgow and Clyde and funded by the Chief Scientist Office, we are beginning to witness its impact on the management of long-term illnesses, diagnoses and tackling health inequalities.
The way healthcare is delivered is changing in response to the demands placed on our NHS, with technology and the at-home management of conditions a huge part of that.
AI algorithms are being trialled to help speed up diagnoses of certain conditions. These can analyse images from X-rays and CT scans with remarkable accuracy – flagging issues for quicker investigations by clinicians.
One example is the RADICAL (Radiograph Accelerated Detection and Identification of Cancer of the Lung) AI-assisted X-ray analysis research study sponsored by the WoSIH, in collaboration with Qure.ai and the University of Glasgow.
Routine outpatient chest X-rays are checked in real-time by AI to identify possible lung cancer, prioritising radiologist workflow for clinician reporting. This can result in potentially earlier detection and treatment.
Another trial, ACCEPT (Assess the Clinical Effectiveness in Prioritising CT Heads), which has been taking place at Queen Elizabeth University Hospital, looks at the use of AI to improve turnaround times for head trauma CT scans, with the aim of reducing pressures on A&E departments.
AI also has the potential to help clinicians make early interventions using analytics to better predict disease progression, identify at-risk populations and personalise treatment plans.
For example, AI models have been used to predict the likelihood of patients developing conditions such as diabetes or heart disease based on their medical history and lifestyle factors.
This could allow medics to intervene at an earlier stage, potentially preventing these diseases from progressing.
Early interventions, and the better management of illnesses, can reduce unscheduled attendances at hospital, allowing patients with the most urgent need for care to be prioritised.
The use of AI in healthcare – within a trusted regulatory framework – may offer opportunities to streamline patient pathways and address deeply entrenched inequalities. by using routinely collected data to identify social determinants of health.
AI can also enable improved use of healthcare data to personalise treatment and may allow for better workflow prioritisation by staff.
There have been legitimate and understandable concerns around the introduction of AI in different professions.
But AI cannot operate in isolation. Clinicians must review AI-generated results before diagnosis or treatment decisions are made, ensuring patient care remains safe and effective.
It does not replace healthcare professionals and should instead be looked upon as a powerful, well-tested tool.
We must embrace these new technologies and ensure our healthcare system, patients and staff can benefit from the safe, well-researched and ethical improvements AI can offer.