Medical Education Needs To Be Reformed K Moidu
What is the future of medical education in the digital age?
We have all dodged a very serious bullet, one that came in the shape of a pandemic and in dodging that we had a great amount of assistance in better data and information management. So essentially, we are now in a state where we see the need for reforming medical education. Our doctors learn and manage the data much better and at a faster pace now. Medical knowledge has grown, the human population has grown and so have the demands of the clinicians. With everything growing, we need to act — medical education needs to be reformed so we can train better physicians for the future.
When you say that, what are the challenges that there could be for a country like India?
With regard to medical education, for a country like India, with the population and the living conditions be-ing what they are — we need to be able to have uniform education across the nation, and create lifelong learners. In that direction, the government has already started the National Medical Council (NMC), which is a replacement for the old Medical Council of India. And they have defined the guidelines for medical education to progress forward.
The key thing that digital technology allows us is a whole host of resources to enable a uniform platform to learn, so that the grasp on the subject is much better. I would also like to add that knowing the vagaries of technology, in India we would have to work a little harder than the rest of the world because of our geographic spread and the dispersal of resources across the country. We must be able to create not one layer, but two and three layers of technical back-up to ensure that there is no shortcoming in the delivery of knowledge resources to the student.
When we talk about the benefits, there is, of course, a unified programme and learning from various experts. What are some of the other benefits that you see this would provide?
For a country like India, where we have the tradition of “gurukul” with its emphasis on the “guru-shishya” relationship – there needs to be “jagriti” or awareness about it.
We need to realise that our teachers should not just ‘tell’ us, we need our teachers to ‘educate’ us. By ‘educate’ it means that we should be able to learn, understand and, more importantly, apply that learning. It is a form of effort that requires a whole shift in the paradigm — from the paradigm of activity to a paradigm of uniform reactivity.
As medical professionals, you have to be lifelong learners, which is more important than anything else. The one message I would like to give everybody is that you have to unlearn to relearn.
Given that AI and big data are such an important aspect of medical education today, where are we with them currently with regard to the curriculum, and where will we be in 2025?
I like the way you want to see the future. For me, when I began in the field of medical computing, back in the early 80s, what I live today is a future that I hadn’t even dreamt of then. Let me begin by saying that AI and digital technologies, machine learning and big data management are an integral part of our knowledge blocks as we build them. When we are taking care of our patients, these digital technologies tell us the possibilities of what will happen and what may not happen. The rules and roles that we develop, get formalized into priority generating rules or algorithms. These algorithms are integrated in electronic medical records.
So if we were to create a medical education system by beginning the education with a clear understanding of the vocabulary of medical conversation, we would certainly be able to produce better physicians. Not only will we have greater accuracy in the acumen of the people collecting the data, but we will also get better accuracy in the data that is stored for us to generate new knowledge.
What are the challenges of medical education becoming data centric?
I wish to inform you that it’s not the technology that matters- it is how we process the data.
The elaborate verbal descriptions used in clinical reports of abnormalities or body changes observed dur-ing a patient assessment are the foundation of clinical decisions. A specific vocabulary set is used to describe the various parts of an encounter record: starting from symptoms, the history of onset, the past medical history, the investigations ordered, and the treatment plan laid out. This, a student learns over the long years of clinical apprenticeship, as the vocabulary is delineated and cross-mapped library resources exist to support extraction of terms and strings from a clinical document. Soon we shall see contextual search get full information from clinical data repositories.
