Standfirst: Tom Mellor, Head of Health & Life Sciences at BJSS, explains how artificial intelligence (AI) is revolutionising healthcare by automating repetitive tasks, enabling predictive analytics for patient management, and enhancing diagnostic accuracy through advanced imaging analysis.
In the UK, the National Health Service (NHS) is facing unprecedented pressure. As of March 14 this year, the waiting list for routine hospital care now stands at 7.58 million, with more than 321,000 people waiting longer than a year. As the strain on healthcare systems intensifies, the imperative for innovation becomes ever more pressing.
Recognising the urgent need to relieve this strain, the healthcare system is increasingly turning to AI to free-up clinician time and improve services. In fact, Chancellor Jeremy Hunt’s Spring Budget announcement included a £3.4 billion commitment to enhancing NHS productivity, primarily through the scaling up of AI utilisation.
Time saved
Amongst other pressures, clinicians and healthcare professionals face a significant administrative burden, with approximately 30% of general practitioners; time spent on paperwork – time that could be better spent on direct patient care. AI can pick up a lot of this slack by automating appointment scheduling, patient triage, and other documentation processes such as medical billing and coding, medication management, and follow-up reminders to patients. By analysing large datasets, AI can also
support GP’s decision-making processes by identifying trends in patient data. The NHS’s plan to roll out AI to reduce missed appointments is a particular focus, as each missed GP appointment costs the NHS an average of £30 per person (Source: NHS). Collectively, this results in hundreds of millions wasted each year. The introduction of AI supported software has shown the potential to predict missed appointments using algorithms and external data, such as weather and traffic reports. It can then offer alternative options ahead of time and rebook appointments to avoid wasting clinician time. The results
of a six-month pilot rollout showed that such AI software prevented 377 missed appointments, and an extra 1,910 patients were seen.
Enhanced patient outcomes
Beyond addressing administration tasks, AI holds even greater power – the immense potential to create and save lives. One such example is the collaborative effort between healthcare provider CARE Fertility and BJSS to develop an AI model to revolutionise embryo selection in fertility treatments. The model developed by BJSS draws on a historic data set of almost 500 million images of embryos to identify the key stages in an embryo’s development and select those most suited for fertilisation. Rather than having to sift through thousands of images, embryologists now only have to verify those selected by the model. This tool drastically reduces expert time spent on embryo assessment, freeing up approximately six
months of an embryologist’s time per year. This enables specialists to spend more time on patient care, research and protocol improvements. But more importantly, this tool increases the reliability of the embryo selection process and the accuracy of predictions to give patients their best chance of becoming pregnant.
Another use case of AI-driven decision support systems includes the AI breast screening tool, MIA. This tool enables doctors to detect 12% more cancer types compared to standard practice and even reduced the number of women recalled for further assessment, resulting in a workload reduction of up to 30%.
Similarly, AI-driven predictive models can identify patients at risk of developing chronic conditions or complications, enabling proactive interventions earlier on in order to reduce the further development of such condition. These AI models typically utilise algorithms which consider a variety of factors including genetics, age, medical history and lifestyle habits to identify at-risk patients.
Overcoming barriers
Despite the huge benefits AI can bring, the successful implementation of such advanced technologies requires overcoming various barriers, including outdated IT infrastructure and employee resistance to change. This is why strategic investment in updating legacy systems, deploying cloud solutions and ensuring proper user adoption is essential. Furthermore, guaranteeing data privacy and security is paramount to fostering trust and acceptance of AI-driven solutions among healthcare professionals and patients.
Collaboration between academic, industry, and regulatory bodies is crucial to establishing robust frameworks for AI governance and ensuring compliance with regulatory standards. AI offers unprecedented opportunities to transform healthcare delivery, from streamlining administrative processes to enhancing patient results. By embracing AI technologies and overcoming implementation barriers, healthcare systems can navigate the challenges they face and emerge stronger, more resilient, and better equipped to meet the evolving needs of patients and communities.
The Importance of AI governance
As AI technologies continue to advance and new challenges emerge, AI governance is pivotal in the responsible implementation of AI technologies. It aims to strike a balance between innovation and responsible use, ensuring that AI benefits society while minimising the potential risks and negative impacts.
To understand the importance of AI governance, BJSS provide a comprehensive overview of the ethical use of AI, the considerations that come with this, and the benefits that can arise
when AI is implemented and governed correctly.
