In the UK, as of August 2024, more than 250,000 patients had waited for over a year for a procedure; in the NHS, 15 weeks is a typical waiting time for a procedure.1 An understaffed NHS and high patient load, coupled with outdated technology & processes, has contributed to these delays.
Working through the challenges
Based on the current trends and needs of the healthcare system, artificial intelligence (AI) and digital tools can be utilised to bridge this gap. However, while the UK government acknowledges the potential of scaling digital and AI technologies to transform healthcare, concerns remain about cost, security implications and need for significant investment in infrastructure and training.
Scaling AI and digital tools in healthcare presents a number of challenges:
- NHS data can be fragmented, inconsistent, and subject to strict privacy regulations such as GDPR, which limits the availability of suitable data for AI tool development.
- A lack of interoperability between different systems and technologies exists. Many organisations still rely on outdated legacy systems, with some existing digital systems and a lack of standardised data actively blocking new solutions from integrating.
- Data privacy and technical security are major concerns, especially given the reliance of AI models on large datasets and numerous data breaches in the past.2
- Technologies must ensure they do not pose a risk to patient safety.
The Digital Technology Assessment Criteria (DTAC) framework issued by NICE, is designed to address many of the challenges faced, through national standards. It will not address adoption, scaling or budget.3
Focusing on user experience and patient safety can help address these challenges and support population health needs whilst ensuring:
- In the AI/digital tool development phase, it is important to include diverse groups of community members, healthcare professionals (HCPs), and patients to ensure the tool reflects real-world needs and cultural nuances. This could also help identify gaps or biases early.4
- Prioritise diverse and representative datasets, ensuring data from various demographics is included to reduce bias.5
- Ensure equitable access to digital / AI tools is available for all and not determined by patients’ socio-economic status.
- Inclusive AI tools should offer user-friendly interfaces with clear navigation and accessibility features to cater to diverse language and ability needs and enhance overall user experience.
Using digital/AI tools to support equality and equity
The UK faces significant health inequalities linked to socioeconomic factors and demographic factors, with disparities in access to quality healthcare.6 Digital/AI tools can play a key role in bridging this divide, and shifting care closer to home and underserved communities:
- Predictive analytics using AI can be critical for health risks; AI-enabled screening in clinics/remote locations and a precision health approach can be employed to risk-stratify or identify high-risk individuals in underrepresented groups and ensure early detection.
- Pharmacy automation technologies, enabled by digital infrastructure, can reduce medication error and reduce medication spend, which supports health outcomes.
BD’s Connected Medication Management leverages technology to streamline and digitally connect the entire medication management process, from prescription to administration.
- Digital health platforms can provide access to HCPs and personalised treatment plans regardless of geography, ensuring rural and underserved communities can access the same level of care as urban populations.
- Automation and digital connectivity outside of labs and pharmacies, can reduce human error, enhance efficiency, and allow for rapid processing; they can perform high-volume tests quickly, shortening patient pathways, allowing for earlier treatment and particularly benefiting underserved areas. BD Synapsys™ helps streamline workflows, reduce errors, and standardise results, empowering lab staff and prescribing clinicians with actionable information to enhance performance, turnaround times and patient care.7
Population Health Equality - Making it Happen
Already two thirds of HCPs are ‘Digital Natives’ - people who have grown up under the influence of digital technology from a young age, and in 5 years that figure will increase to roughly 75%.8
In the UK, we are an enabled workforce; we have the technologies today and a pipeline of innovation for tomorrow. A long-term view, investment in capital funding and the resource to allow change can offer healthcare the same productivity transformation for our workforce, and patients that we have seen in other sectors.
On 27 November 2024, I will be joining the panel discussion on AI and digital health along with community leaders from health and social care across the UK at the Centre for Population Health’s first ever conference, where we discuss and start to plan practical steps, driving action for prevention, improving quality and safety, tackling inequalities.
Visit www.centreforpopulationhealth.co.uk/2024-conference for more information.
