Why shouldn't we fear the use of AI in healthcare? How is Dialogue at the forefront of innovation with its use of technology?

Dr. Julien Martel explores the numerous applications of AI in healthcare and telemedicine in this 5-part video series!

 


Myth #1:

Starting a patient interaction with a human is THE best approach. Chatbots are scary.


We know that about 40% of physicians’ and nurse practitioners’ time is used to gather data. So you ask questions, you wait for the patient to answer. And most of the time, these questions come up over and over again at each encounter. It's more or less around the same themes, always. 

If we know that we can automate most of that data gathering, it leaves more space in the consultation to actually hear out other questions that the patient may have, whether it's concerns or really go a little bit deeper into the care plan, and have at the end of the day, more meaningful interaction with the patients. I think that's a great opportunity with AI and healthcare, especially when you use chatbots. Because you will either improve efficiency, quality or the patient satisfaction. Any win or gain in either of those three objectives is really something that can transform healthcare.


Myth #2:

Technology can't make decisions about someone’s health. Humans are more dependable.


At Dialogue, we use the AI agent as a data aggregator. This allows us to gain a more insight into what the patient's problem might be, and actually to know where we might be going with this. So we'll never use AI to actually make a diagnosis, but we'll use the algorithms really to put forward some insight to the care team, and the care team at the end that they will decide what's best for the patient. Because we really have to understand the diagnosis part, it's something we don't want to anchor or have an anchor bias on from the beginning. We want to keep this wide to be able to evaluate all the possibilities. And at the end, you have the practitioner or the healthcare professional, that really takes the decision. And that decision puts into context so many more things that are unique to the patient's situation. The way I think AI should be used is to augment the intelligence of the care team by providing additional insight to take better decisions at the end of the care journey.


Myth #3:

Dialogue is just a tech company, not focused on the patient.

 

What I like about Dialogue is that there's this strong medical expertise that is used to deliver high-quality care to the patients. And what makes it even stronger is that we're able to have engineers that we can work hand in hand with, and provide this kind of unique environment to develop clinical tools that are really useful and meaningful for the patient and the providers.

Along with our medical team and our medical committee, we do a lot of quality audits, and we make sure that we use the best practices, we can really tailor that software to those clinical applications. Whereas, usually, the ownership of the tech is somewhere else, and there's a service company that's delivering the healthcare services. But working in these two separate silos sometimes makes it harder to make relevant technologies. At dialogue what I really love about it, is that we can actually in the same day, make a modification and really improve our care flow with that. I think it's a unique combination of skills under the same roof and it makes it very special.


Myth #4:

There is no place for AI in healthcare.


AI and healthcare is huge. There's around 50% of all the budget devoted to AI research and application in healthcare. And why it's in healthcare? It's because it has the potential to really transform that industry for the better, whether it's from patient orientation to helping in diagnosis, to streamlining care journeys where we can have smart screening and smart follow-ups. There are endless applications for artificial intelligence and healthcare. At Dialogue, we're really at the forefront of using AI in all our clinical workflow, whether it is for gathering data to output smart recommendation to the care team, identify high risk patients, for example, in mental health to see how they would evolve in the near future, these are all simple example of how we can use AI to really improve the overall efficiency and delivery of care. And always putting at the center the patient to make sure that the overall experience is always augmented with it, and it's improved.

We know that healthcare is costing more and more. And that's in part because on one end, you have an aging population that has more chronic disease, and they live longer with those diseases. So the spending costs just increases. And on the other hand, you have all the personalized aspect of medicine or precision medicine, where you can integrate all that big data and information we have about those patients take really tailored recommendations and care paths for those patients. So without AI, these kind of challenges where we're trying to really target who will benefit from one treatment versus who will probably not benefit as much really allows for improved efficiency, in care journeys of patients to make sure that we spend every dollar in a diligent way and make sure that every patient gets the best treatment that they can have for their very unique situation.


Myth #5:

It's perfectly fine not to have an AI or automation strategy in healthcare.


In order to be able to deliver high quality and scalable healthcare to patients and making sure that you really focus on the patient in front of you, you will need to have a data strategy and an AI strategy to be able to achieve that goal. Without this, it's going to be extremely hard to scale all this innovation to a larger population, it will be extremely hard to be able to provide these kind of very specific recommendations and treatment to individual patients. So why use AI-driven healthcare and why use AI in pretty much all aspects of healthcare is really, at the end of the day, the only thing we want to improve is patient outcome, safety and quality of care.

 

 

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