From theory to therapy: AI’s journey in personalising patient care

Artificial intelligence in health and social care has moved from the realm of theory into real-world applications. They are now solving complex, often life-threatening problems for patients.

AI is impacting one area in particular: personalised care. In this article, we’ll look at AI's current uses and how you can implement them in your organisation. We’ll also explore what’s in store for the future.

AI in daily healthcare operations

AI-driven personalised services have seen an array of applications, from diagnosis to treatment selection and implementation.

Diagnostic imaging: The Transformation Directorate, responsible for driving transformation in the NHS, says, “AI is already helping doctors and other healthcare workers to screen more efficiently for some diseases, including cancer.”
Patient management systems: The Mid and South Essex NHS Foundation Trust predicts that integrating AI into its systems will, among other benefits, will make space for up to 100,000 extra appointments every year.

Virtual chatbots: AI-led chatbots have seen adoption in both private and public healthcare settings, with applications in mental health, patient triaging and patient-facing services like appointment booking.
Predictive analytics: Healthcare organisations including the NHS are using AI to process large volumes of data to identify risk factors and tailor preventative plans accordingly.

Benefits of AI in patient care

AI is enhancing personalisation across the board, from prevention right through to end-of-life palliative care.

Prevention: AI is being used to predict chronic diseases, allowing for targeted interventions.
Mental health care: AI-driven apps, especially chatbots, provide continuous support and monitoring, helping patients manage conditions like depression and anxiety and limiting the likelihood of relapse.
Treatment: The NHS has been adopting AI to personalise treatment plans, for example, using IBM Watson to help oncologists at Alder Hey Children's Hospital.
Palliative care: AI has seen early-stage applications in tailoring pain management and end-of-life therapies to individual needs, although this area is ethically complex.

Challenges and considerations

Integrating AI into existing healthcare systems, many of which rely on legacy systems, presents challenges. There are also significant ethical concerns.

AI supervision: AI requires substantial professional oversight to ensure systems perform reliably and to prevent misdiagnosis.
Professional accountability: Healthcare professionals are accountable for patient outcomes, even when AI tools support decision-making processes.
Patient consent: Answering the question, “Can patients consent to the use of AI in their care?” is difficult given the complexity of the technology.
Ongoing training: AI evolves quickly and healthcare staff require costly, time-consuming training to use technology effectively.
Fast rate of AI Innovation: The rapid pace of AI development can outstrip providers’ ability to integrate new technologies effectively.

The future of AI in healthcare

At Waymark, we believe that the role of AI in practically all healthcare settings will continue to grow.

In the UK, the NHS is leading the way with initiatives like the AI Lab, where it is exploring not just the integration of cutting-edge technology for measurable patient outcomes but also the ethical components of AI.

For patient outcomes, we think three key areas will see the most innovation in the coming years: early detection of high-risk diseases like cancer and Alzheimer's, highly personalised treatment plans and mental health treatment and monitoring.

We are also particularly excited about how AI will drive operational efficiency. Early applications, such as the DrDoctor app, have proven immensely promising.

Conclusion

It’s difficult to understate the impact AI will have on healthcare in the UK. The NHS is already implementing AI-based solutions, with significant interest from governance teams in emerging tech.

Healthcare leaders who embrace the AI revolution are poised to realise benefits in all major areas, from operational efficiency right through to patient diagnosis and treatment.