National Health Executive Podcast
Jun 9, 2026 · 45 min · 10 segments
The NHS stands at a crossroads. With rising demands, workforce shortages, and a stretched budget, the question of whether technology can save the NHS is more pressing than ever. In the latest episode…
Eleanor WicksGuest
Daniel GardnerGuest
Mark ToussaintGuestWhat are we actually working with at the moment? What's the present day landscape like?


Um, examples include opportunities in clinical decision support and triage, uh, diagnostics in detailed, um, phenotyping, which is kind of deep assessment of someone's presentation, risk stratification, remote care delivery, admin automation, data an- analytics.

But actually, from a practical perspective, there are quite a few specific examples, um, that people may not be as well aware of.

So for example, we're trying to digitize some care pathways, particularly in heart failure and cardiometabolic disease.

Um, and some of the work that we've been doing in Oxford and in primary and secondary care, uh, along with LifeYear, has been trying to look at the benefits of remote monitoring tools to detect disease in an earlier setting, to try and detect decompensation early, and to try and think how we can integrate scalable, low-cost solutions that empower patients also in self-care, which is obviously a critical component.

But there are many different aspects, so we have virtual wards, we have hospital at home, um, we have digital twins that can try and integrate complex big data, AI ECG analysis, so the electrical tracing of someone's heart.

We now can use AI to try and detect the disease before it even arises and someone becomes symptomatic.

Um, we can analyze images using AI approaches, and we have other kind of really cool avatars and, um, we have this European Society of Cardiology kind of chat now that tries to help support healthcare workers in using clinical guidelines to improve the care of patients.

I mean, the reality is, is tech is enabling us to do a lot more, but we really need to think about how we best embed it, uh, into practice on a day-to-day basis.
What are we actually working with at the moment? What's the present day landscape like?


Um, examples include opportunities in clinical decision support and triage, uh, diagnostics in detailed, um, phenotyping, which is kind of deep assessment of someone's presentation, risk stratification, remote care delivery, admin automation, data an- analytics.

But actually, from a practical perspective, there are quite a few specific examples, um, that people may not be as well aware of.

So for example, we're trying to digitize some care pathways, particularly in heart failure and cardiometabolic disease.

Um, and some of the work that we've been doing in Oxford and in primary and secondary care, uh, along with LifeYear, has been trying to look at the benefits of remote monitoring tools to detect disease in an earlier setting, to try and detect decompensation early, and to try and think how we can integrate scalable, low-cost solutions that empower patients also in self-care, which is obviously a critical component.

But there are many different aspects, so we have virtual wards, we have hospital at home, um, we have digital twins that can try and integrate complex big data, AI ECG analysis, so the electrical tracing of someone's heart.

We now can use AI to try and detect the disease before it even arises and someone becomes symptomatic.

Um, we can analyze images using AI approaches, and we have other kind of really cool avatars and, um, we have this European Society of Cardiology kind of chat now that tries to help support healthcare workers in using clinical guidelines to improve the care of patients.

I mean, the reality is, is tech is enabling us to do a lot more, but we really need to think about how we best embed it, uh, into practice on a day-to-day basis.
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