Medical research never stops. In fact, it is accelerating. According to health industry data, the equivalent of nearly 100 new studies are published around the world every hour, so a clinician would have to spend 21 hours a day reading everything to keep up to date. most recent discoveries in his field of expertise. The startup Pathway was created by three Montrealers who believe that it is possible to sift through all this information to help healthcare professionals do their jobs more efficiently.
Pathway has just completed funding of $ 1.6 million to refine its technology, expand the amount of information it brings back to its service and expand its offering to more areas of medicine. Its application is already used in 180 countries by doctors, pharmacists and medical students. Will technology have the desired effect on this important industry? Jonathan Hershon Saint-Jean, co-founder of Pathway, hopes so.
Medical infobesity
Infobesity is a term that arose early in the general public’s adoption of the web when it was realized how huge the amount of information that can be found on the internet about most subjects is enormous. . This information overload can lead a person to not really know how to distinguish the most recent and relevant information, a phenomenon that continues to be relevant until health, where the level of knowledge about the disease evolves at a speed beyond comprehension. The problem is that this information is often disparate, uses different terms and turns out to be a real headache, notes Jonathan Hershon Saint-Jean.
“The speed at which health research is produced is crazy, and it just keeps accelerating. What we have developed is a tool that summarizes and standardizes all this research, so that the terms used from one to another are the same. We extract information that is clinically useful for specialists who want to make the right diagnosis and suggest the right remedy. It’s a huge time saver. “
Health technology
It was discovered, in the first weeks of the COVID-19 pandemic, that the Quebec health sector was based on at least one technology that we can safely call outdated: the fax machine. At a time when electronic messaging is ubiquitous, it seems obvious that a small enhancement of work tools would help make the system more efficient without changing the way things are done in the sector. Is there room for more health technology?
” Absolutely. Much is still being done manually that could be digitized or even automated. Even in Quebec, there are certain practices that could be improved to speed up the treatment of patients immediately. I am thinking, for example, of the sharing of data between different health establishments, ”says Hershon Saint-Jean.
Resistance to change
Seen from the outside, the Quebec health sector can look like a huge monolith that resists any change or reform aimed at improving its efficiency. The reality is obviously more complex than that. Health is a fairly broad term, which encompasses a very wide variety of care and services that are difficult to define in a single way. Without being optimal, the system functions in its own way, and often solutions that present themselves as innovative encounter resistance that prevents them from being integrated into the system. It’s a challenge Pathway hopes to be able to avoid.
“In general, clinicians are quite open to new ideas, but it varies by age,” says Hershon Saint-Jean. “The youngest professionals are more open to new technologies. It is calculated that they use an average of five specialized applications to do their job. For our application, we offer it directly to clinicians. This helps us validate our service and improve it quickly. We also took this approach bottom-up because we hope that those who are currently using our app will share their experience with their colleagues and that it will therefore be used more and more across the industry. “
Artificial intelligence in health
Artificial intelligence (AI) is a term that encompasses many digital technologies that all have one thing in common: they are based on the automated analysis of such a large volume of data that it would be next to impossible. do the study manually. Another part of AI is machine learning, an application of technology where it gets better as data is submitted to it. This is why early AI systems tend to perform less well than expected: they have to learn first, and then, as they improve, they end up outperforming a human on specific tasks. The volume of data is important, and AI can play a pivotal role, believes Jonathan Hershon Saint-Jean.
“Only in medical research can AI recommend the right information from a large number of studies with a much greater degree of precision and speed than if we were to give the task to physicians. Research centers and laboratories all over the world use around 300 different rating and qualification scales to express their results. AI already allows the base to structure all this information to sort and standardize all these results. But AI is not here to replace specialists, on the contrary: we have a team of doctors who oversee the technology. This is also how we train our AI to become more efficient every day. “