The challenges facing medicine in the near future
I’ve just taken part in eCardio 2019, the virtual congress developed by the Spanish Society of Cardiology (SEC) now in its third year, and an organization I’ve collaborated with on several occasions already.
I was asked to give my views on the challenges medicine faces in the near future (video in Spanish, my part starts in 34:40). This is a subject I have written about here on a number of occasions and that I can sincerely say is close to my heart: in September I had my first atrial fibrillation, and after a few more episodes, in December I underwent a procedure called pulmonary vein isolation, which was followed by post-operative complications and a blanking period that is still underway (hence my recent change of look, thank the beard to anticoagulants 🙂
Needless to say, I took the opportunity to experiment with all kinds of monitoring devices (Apple Watch 4, Wiwe, Kardia, etc.) and to acquire some experience in the subject, as well as to talk with manufacturers and practitioners about their use and possibilities, adding this to my previous impressions about the possibilities of personal quantification, wearables, etc., and their role in the future of science and medical research.
I kicked off my presentation with an attempt to help medics understand that, today, they fall into two types, those that believe — wrongly — that a smartwatch has nothing to contribute to research or medical treatment because it lacks the accuracy of a medical device; and those who have already realized that wearing such devices, preferably connected at all times, increases the sample range and, therefore, reduces standard error. Basically, this comes down to those who understand statistics and those who don’t: a smartwatch that measures heart rate by photoplethysmography — a technology now widely accepted for many years, and whose accuracy has improved significantly as sensors keep improving— will never be as accurate as 12 electrodes attached to different parts of the body, but while most of us undergo a conventional electrocardiogram only occasionally, we wear an Apple Watch all the time and it records the heart rate continuously. Seeing it as a fashion item with nothing to offer research is to have understood nothing.
Consumer electronics companies like Apple, Google and many others now offer the means to carry out ambitious clinical studies, with never-before-seen sample sizes. Sure, hypochondriacs love them, but they also offer a wide range of possibilities for medical care and, above all, research. Health professionals able to understand the importance of millions of people suddenly wearing a heart monitor on their wrist or carrying a smartphone for which they can create apps capable of evaluating a wide range of parameters or that can store their health data can now contact Apple and participate in their research and carry out their own medical research, based in many cases on impressive sample sizes and that are relatively easy to obtain.
In other words, it would appear that the future of healthcare is, as I have commented on many occasions, moving from a reactive to a proactive model, to one based on increased monitoring of more parameters that with the assistance of machine learning algorithms, will make it much easier to keep track of our health and provide our doctors with much more information about any problems we may face. Obviously, this will have to be accompanied by measures to keep doctors in business, as well as designing processes to enable the progressive advance of medical science as a whole. In the near future, rather than going to the doctor when something hurts, the doctor who will call us when an algorithm detects an abnormality based on information obtained from our devices.
Understanding that this change is fundamental to greater efficiency, as well as improved quality of service and cost will be the key factor when considering whether these types of care — which will first be used in private medicine — will be available in public medical centers, essential if we do not want to avoid a two-tier system. Likewise, the role of consumer electronics companies and their regulation is also important: some devices will be made by companies that guarantee privacy, while others will be the products of companies that exploit the analysis of data or may have less reliable security protocols.
Where to begin? From my point of view, this revolution must start with the field of research. Only companies born with a vocation to develop a particular specialty can guarantee the seriousness necessary. Creating a consumer product that warns you of an arrhythmia and that assesses it better than your doctor is not simple, but is technically feasible. Using data transparently to warn people in time or to detect previously undetectable problems where the differential lies for me.
Pharmaceutical companies will also have a fundamental role to play in all this, and in many cases will go from being mere suppliers of drugs to service providers that monitor whether people are following their course of treatment, for example, through means such as progressive sensorization and the development of monitoring apps or other elements, in addition to a simple pill.
Will technology take over from doctors? No, but we will can expect to see a similar process in medicine to that in advertising, where the Mad Men were defeated by the math men. To paraphrase Erik Brynjolfsson, as I have done on numerous occasions, machine learning will not replace doctors, but doctors who understand machine learning will possibly replace those who do not. We’re going to see more and more algorithms used in the diagnosis and treatment of more and more conditions in which adequate data analytics will provide the necessary answers. Combining machine learning and medicine is a huge opportunity and medics need to understand that.
Which will we see the fastest progress? In Cardiology, which is deeply analytical and highly dependent on data already; others include endocrinology, specifically diabetes, where data can also be generated relatively simply. But we can expect to see medical science use analytics across a wide range of fields.
(En español, aquí)
The challenges facing medicine in the near future
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