Beyond the Fog contributes to computational medicine university course
“What you have to understand about doctors is that we are basically data analysts. Patients present with symptoms and we listen to their words and check them out physically; we do tests to get more data; and we compare what we find with other data that we have amassed and internalised. What’s going to change is that we’ll potentially have exponentially more data and as analysts, we’ll need to know how to use it.”
This was what a senior consultant at the Royal Free told us in one of our first interviews at the beginning of the Beyond the Fog journey; and it has been at the heart of much of our thinking. So, it was a great pleasure for us to be asked to be part of a morning of lectures at Leicester University to build interest in a new “Computationally Intensive Medicine” course being developed by the inspiring Dr. Ron Hsu and Dr. Julian Barwell.
The course is based, according to Dr. Hsu, on:
“1. the premise that computational machines will impact on the practice of medicine during the medical students’ professional lives exponentially and at scale, i.e. be transformative in a disruptive way not in an evolutionary way
2. the assumption that the impact of computational machines will be in a numerical form, i.e. the output from computational machines will be based on numerical concepts and provided in numerical form
3. the prediction that the numerical concepts and numerical output will change the practice of medicine from a biological narrative to a numerical narrative, i.e. the focus becomes more on how to influence numerical probabilities rather than whether there is a biological explanation with pharmacological, surgical and radiological solutions
4. the anticipation that practitioners of medicine will need to differentiate themselves from recipients of the practice of medicine (aka ‘patients’) by being able to:
- at least work with and understand the numerical form of outputs from computational machines in their practice of medicine
- preferably be able to use the outputs from computational machines effectively and appropriately in their practice of medicine
- ideally be able to critique the basis for and exercise judgement on the use of computational machines in their practice of medicine
5. the concern that medical students will not be able to differentiate themselves from other healthcare professionals (as well as potentially the ‘recipients of the practice of medicine’) in their practice of medicine as the computational machines dominate the diagnostic process, prognostic prediction and therapeutic prescription functions of medical practitioners that other healthcare professionals currently do not undertake universally.”
Dr Hsu recognises that these are potentially controversial statements; and indeed that they would be disputed by many. However, we believe them to be self-evident when you look at what is coming down the line.
Indeed, if the potential for technology and medical advances that take advantage of the huge amount of data that is starting to flow from all points along our Cells to Cities landscape (see graphic below) is to be realised, it’s vital that medical education accelerates how it integrates this into the curriculum.
Today’s medical undergraduates are likely to face an entire career of rapidly changing essential knowledge; and one look at Beyond the Fog vision by the junior doctors with whom we ran workshops during the development of Beyond the Fog led to a common realisation that: “we’re not being taught what we’ll need”.
The students attending the introductory lectures for the course clearly had a similar understanding. Of the 290 or so who were attracted to the morning of lectures, 40 signed up to attend the course next year despite it offering no course credits — presumably because they see how important it will be to their future.
This is not to say that the experience-driven intuition of today’s senior consultants will become obsolete any time soon — and, wonderfully, the course will be delivered by retired clinicians, none of whom have had experience of artificial intelligence in clinical practice in their 40–50 years of experience.
And nor does it diminish the importance of empathetic human care (which , if anything will become a more important role of the doctor in working with data-rich patients).
But as the top data analysts (aka consultants) have access to exponentially more data, the knowledge and understanding of how to parse it and use it will become ever more critical at all levels within the medical profession — even as it changes the roles of different kinds of healthcare professionals.
Universities should be moving rapidly to integrate computational medicine into their curriculum; and so should other academic medical institutions working with medical professions through their careers. Doctors are data analysts; they are about to be deluged with data; they need the skills to successfully interpret and integrate this into the new emerging practice of 21st Century medicine.
We applaud Leicester Medical School for making its first tentative steps towards doing so.