“Smartization” of Medical Devices
Intellectual property, and software, is an ever-larger factor in the cost of our devices and gadgets. A recent study from TechInsights shows that the total cost of all components, testing, and assembly for an iPhone XS Max comes out at $443; meanwhile, that same phone is sold by US retailers for $1,249. Unfortunate, but there is no way around this — an iPhone without iOS is about as useful as a brick. The same can be said for medical devices — they are becoming ever more dependent on software to perform their functions.
Almost every day we see headlines announcing amazing achievements in the field of medicine. But it is understood that these new techniques and discoveries will not be seen in standard medical practices any time soon; first they will have to go through the long and laborious process of clinical trials and certification. Obviously, there is a conflict between the current pace of research and development and the established traditions for introducing new types of treatment and diagnosis into practice. This system clearly needs to change, and the path from the laboratory to the clinic must be shortened; however, this must be done in a way that does not increase risk. There is already more than enough of that in medicine as is.
Are you ready for medical robots?
Ask yourself, for instance, would you be ready to trust a robot surgeon? Not everyone is ready to trust human surgeons — so putting your faith in some kind of machine? Seems unlikely. And yet, robotic surgery has been in development ever since the 1980s. So far though, the use of “robot surgeons” is limited to mechanical “hands” used by doctors; the machines do not make any independent decisions themselves. The currently leader in this market of surgical robots is the US company Da Vinci, which has installed more than three thousand robots around the world. Soon we will also see robot surgeons that are equipped with AI and capable of performing operations independently. Their development is already underway. So it seems that, like it or not, we will have to learn to trust robot surgeons, though not immediately. According to MarketsandMarkets, the global market for surgical robots will grow by 10.4% annually, from 3.9 billion dollars in 2018 to $8.48 billion by 2027.
AI in medicine: good idea but not mature yet
And how about relying 100% on diagnoses made by artificial intelligence? If we feed huge batches of x-rays and test results into a neural network, it will teach itself to work better than our protein-based doctors are capable of, right? Indeed, this would be movement in the right direction, but technology just isn’t there yet. Even IBM’s Watson for Oncology repeatedly issued inaccurate and unsafe cancer treatment recommendations. So long as the project is in its experimental phase, this problem isn’t critical, since all AI diagnoses are rechecked by experienced professionals. But can you imagine what would happen if a system like this was released onto the market? Doctors would very quickly get accustomed to relying on the system, and would stop thinking things over themselves — much like taxi drivers who unthinkingly follow their navigator apps, even when the app suggests a bizarre and circuitous route. So it would probably be best to hold off for now on the widespread implementation of AI diagnostics.
Doubts surrounding AI extend beyond just robots and diagnostic systems. All new, digitally inspired innovations have to undergo a lengthy testing process before they appear in clinics.
Innovate for bringing efficiency into healthcare
But isn’t there some way to make these new technologies, which are ubiquitous everywhere else, provide some quick and tangible results in medicine? Of course, there is! Let’s forget about the actual treatment process for a moment and consider healthcare as an industry. The healthcare industry is an extremely complex ecosystem that includes not only doctors and patients, but also medical equipment suppliers, pharmaceutical companies, regulators, insurance and leasing companies, medical institutions, research institutes and other participants. Unfortunately, this ecosystem does not function nearly as well as it could, because it is being weighed down by inefficient business processes and bloated bureaucracy, which inhibit the flow of investment.
Three waves of innovations
Nonetheless, things have begun to shift. There has already been one wave of movement towards integrating digital technology into healthcare, and it affected even the most routine processes in patient care. Electronic queues appeared in clinics, as did the ability to send remote recordings to a doctor, to access electronic medical records, and so forth. These are all important advancement that increase the efficiency of medical institutions and the availability of medical services. But this is not enough. Devices used by physicians should become more technologically enabled in order to speed up transmission and reception of information. This would both reduce errors in data recorded by hand and increase the automation of clinical processes. Let’s not even talk about providing medical instruments with full-fledged artificial brains. For now it would be enough if they just caught up to smartphones.
MDignum Vision
First wave — implementation of blockchain into EMR/EHR — is almost commodity. Sure, it provides solid basis for the next two waves. MDignum competitive advantage is the unique combination of deep fintech and engineering expertise, so we are to serf on the both waves, second and third.
What’s further? Fourth, fifth waves. AI, robotics, bioprinting, genome technologies and so on. Everything we read about in science fiction books. Certainly, we want to participate in this game.
“Smartization”: process begins
This metamorphosis is already underway — medical devices, ranging from standard thermometers all the way to the most complex MRI machines, are rapidly being digitized. “Smartization” of medical devices means, firstly, ensuring their connection to the internet, and secondly, ensuring the presence of various IoT-sensors. These sensors can measure external parameters and monitor the status of the device itself, and also keep track of time and the device’s operational modes, which will restructure many processes in the healthcare industry. For example, telemedicine is excitedly awaiting smart devices in order to finally launch remote monitoring for patients, instead of simply conducting video consultations.
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