Harnessing AI in healthcare to address health inequities, enhance accessibility, and improve patient care
The National Health Service (NHS) is a huge asset to society in the UK, yet it faces significant challenges that demand innovative solutions. Among the most pressing issues are health inequalities, operational inefficiencies, accessibility and the varying quality of patient care across different communities. As technology advances, AI stands poised to tackle these issues head-on, and immediate action is crucial to harness its full potential.
Addressing health inequalities with AI
Health inequalities in the NHS contribute to poor outcomes, particularly for vulnerable populations. Patients discharged from acute care often face challenges in accessing community or mental health services due to resource shortages and poor care coordination, straining hospital resources and perpetuating poor health. Additionally, disparities manifest in access to preventive care, treatment quality, and health literacy, with lower socioeconomic groups and rural communities facing significant barriers to essential services and specialist care.
AI can play a crucial role in addressing these disparities by:
-
Predictive analytics for preventive care: AI identifies at-risk individuals, enabling targeted interventions and reducing care disparities.
-
Optimising resource allocation: AI predicts provider shortages and deploys resources to underserved areas, improving service access.
-
Enhancing care coordination: AI integrates data across care settings, ensuring continuity and reducing gaps in transitions.
-
Boosting health literacy: AI offers tailored health education, empowering patients to manage their health and make informed decisions.
Promoting digital inclusion and accessibility
Digital inclusion is crucial in ensuring that all patients benefit from AI-driven healthcare innovations. However, many patients face barriers to accessing digital health services, such as telemedicine, due to language barriers, digital poverty or a lack of digital literacy. This can exacerbate health inequalities, as those who are unable to engage with digital services may miss out on timely care.
To address this, AI can be used to create more accessible and user-friendly digital health platforms. For instance, AI can tailor digital interfaces to accommodate different levels of digital literacy, ensuring that patients can easily navigate telemedicine platforms or hospital apps. Additionally, AI-driven tools can assist in providing translation services in real-time, breaking down language barriers and ensuring that non-English speaking patients receive the same level of care as others.
AI can enhance accessibility within healthcare facilities through digital wayfinding tools. These tools assist patients by guiding them through every step of their visit, from finding the best parking spots to choosing the most convenient entrance. They provide door-to-door navigation through complex hospital layouts, ensuring patients reach their appointments punctually. This is especially valuable for patients with disabilities or those unfamiliar with the hospital, as it minimises stress, improves their overall experience and streamlines patient flow.
Moreover, AI can support chronic disease management through digital platforms. For example, several NHS Trusts in the UK have deployed AI-driven virtual health assistants to support patients with chronic conditions such as diabetes. These virtual assistants can provide personalised reminders for medication, offer dietary advice, and monitor patient glucose levels through connected devices. This has the potential to improve chronic disease management, leading to fewer hospital admissions and reducing strain on the health service.
Enhancing operational efficiency for better patient care
Operational inefficiencies are another critical issue that impacts both patient care and hospital revenue. Elective procedures and outpatient clinics often fall behind schedule, leading to delayed care and financial losses for Trusts. For instance, the concept of elective recovery—bringing elective care activities back to pre-COVID levels—is currently hindered by staff fatigue, patient backlog, and poor scheduling practices.
AI can enhance booking and scheduling by analysing patterns in patient no-shows, wait times, and clinic delays, enabling real-time adjustments. For example, if a patient arrives early, AI can assess whether to move their appointment up or adjust schedules based on other patient delays, ensuring clinics start and end on time and that procedures proceed as planned. By automating tasks like updating patient notes and managing prescriptions, AI reduces the administrative burden on clinicians, leading to smoother patient journeys and shorter wait times. This increased efficiency not only improves hospital operations but also boosts revenue through better resource utilisation and allows clinicians to spend more time on direct patient care.
Moreover, AI can optimise theatre utilisation through better prediction of patient flows and surgical schedules, improving patient experiences, and maximising hospital capacity for elective surgeries. Additionally, AI can play a transformative role in diagnostics; for example, at several NHS Trusts, AI has improved breast cancer detection in mammograms, leading to earlier diagnoses and better patient outcomes. These advancements demonstrate AI's potential to enhance both operational efficiency and patient care.
Integrating AI across care pathways for better outcomes
One of the most promising applications of AI in healthcare is its ability to integrate across care pathways, ensuring continuity of care from acute settings to the community. For example, in an acute setting like an NHS Trust, AI can be integrated into Electronic Patient Records (EPR) systems to ensure that all relevant information is available across different care settings—whether it’s a GP practice, community care facility, or social care service.
This integration can improve the coordination of care, as healthcare professionals across different settings have access to the same patient data. It allows for better planning and execution of care plans, reducing the likelihood of errors or omissions that could negatively impact patient outcomes. Furthermore, AI can automate the creation of discharge summaries, ensuring that they are completed accurately and promptly. This automation is crucial for seamless transitions from hospital to home or community care and improves patient flow across care settings.
AI’s role in future-proofing healthcare
As the NHS evolves, integrating AI into healthcare is essential for tackling current challenges and preparing for the future. AI enhances operational efficiency, boosts accessibility, and promotes health equity, enabling the NHS to deliver high-quality care to all patients.
To fully realise AI’s full potential, the NHS must shift from traditional IT systems to digitally-enabled workflows. This transformation will optimise patient care and outcomes, making AI a core component of the healthcare ecosystem. By embracing AI, we can create a more equitable, accessible, and effective healthcare system that benefits everyone in society.
Dive deeper with more AI insights:
If you're interested in AI adoption you can find more insights on our AI Campaign Week page, here:
Stay up to date with techUK AI Adoption work:
To help promote greater levels of responsible AI adoption, techUK is working alongside its members and key stakeholders across the AI ecosystem to demonstrate the significant benefits of this technology for both the economy and society. The best way to stay up to date with our work is to visit our AI Adoption Hub.
Call for AI Adoption case studies:
As part of techUK’s 2024 AI Campaign Week, we are launching a call for techUK member case studies, to demonstrate how organisations are tackling the barriers to AI adoption to maximise AI's potential. These case studies will be showcased to UK organisations that are also embarking on their AI adoption journeys, providing them with practical examples and insights to guide their Putting AI into Action efforts. Learn more here.
techUK - Putting AI into Action
techUK’s Putting AI into Action campaign serves as a one stop shop for showcasing the opportunities and benefits of AI adoption across sectors and markets.
During this campaign, techUK will run a regular drumbeat of activity, including events, reports, and insights, to demonstrate some of the most significant opportunities for AI adoption in 2024, as well as working with key stakeholders to identify and address current barriers to adoption.
Visit our AI Adoption Hub to learn more, or find our latest activity below.
Upcoming AI Adoption events
Latest news and insights
Get our tech and innovation insights straight to your inbox
Sign-up to get the latest updates and opportunities from our Technology and Innovation and AI programmes.
Contact the team
Usman Ikhlaq
Usman Ikhlaq
Usman joined techUK in January 2024 as Programme Manager for Artificial Intelligence.
His role is to help techUK members of all sizes and across all sectors to adopt AI at scale. This includes identifying the barriers to adoption, considering solutions and how best to maximise AI's potential.
Prior to joining techUK, Usman worked as a policy, government affairs and public affairs professional in the advertising sector. He has also worked in sales and marketing and FinTech.
Usman is a graduate of the London School of Economics and Political Science (MSc), BPP Law School (GDL and LLB) and Queen Mary University of London (BA).
When he isn’t working, Usman enjoys spending time with his family and friends. He also has a keen interest in running, reading and travelling.
Learn more about our AI Adoption campaign:
Authors
Larry Murphy
Larry has been in IT since he was a child, his first real job was as a trainee programmer right out of school, and he’s stuck with IT ever since. His career has taken him abroad, to Canada and the USA for almost eight years, then to the UK and thanks to COVID is now taking the stairs to work at home in Ireland.
Jonathan Hincliffe
Jonathan’s career is anything but ordinary. He’s travelled the globe with the British Army, taken on leadership roles within the Armed Forces, and held strategic positions at the Ministry of Defence. His journey then led him to drive digital transformation first at NHS Digital and later at Manchester University NHS Foundation Trust (MFT).