Embracing transition with medical technology

Medical technologies, such as artificial intelligence and data analytics, are shifting how physicians make decisions and treat their patients in real time, whether in a specialist’s clinic or an emergency department. Yet, their potential is far from fully realized. In the second episode of this two-part podcast, four physicians – Dr. Chandi Chandrasena, family physician in Ottawa and chief medical officer at OntarioMD; Dr. Amol Verma, physician of general internal medicine at St. Michael’s Hospital and co-lead for Gemini (hospital data and analytics study); Dr. Teodor Grantcharov, professor of surgery at the University of Toronto and Keenan chair at St. Michael’s Hospital; and Dr. Muhammad Mamdani, vice president of data science and advanced analytics at Unity Health Toronto – discuss where resistance to, and challenges in, adopting these technologies reside and the steps that must be taken to break these down.

Transcript

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Georgia Balogiannis: In this podcast the Ontario Medical Association looks at current issues of interest in health care. Spotlight on Health gives you all the straight talk. We're Ontario's doctors and your health matters to us. I'm Georgia Balogiannis for the Ontario Medical Association. 

Balogiannis: The pandemic necessitated a pivot to virtual medical appointments for many patients, and electronic health records, medical apps and digital data have become the norm in Ontario's healthcare system. In part two of a two-part episode, physicians discuss what the future may hold for health care in the province. 

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Balogiannis: Dr. Chandi Chandrasena is a family physician in Ottawa and chief medical officer at OntarioMD.

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Dr. Chandi Chandrasena: We're learning more and more that we need to incorporate all data in order for our patients to have better care. It's not enough to just be the data that's in my electronic medical record when you come and see me, but there's so much other data out there, right? There's hospital data, there's lab data, there's data where — when you had tests done, home care, community data, and then wearables really fits in there too. Like, where do we put that in, right? 

So, part of the issue is, how do we integrate that data and how do we integrate it in a meaningful way? Because we have all these different systems, but they're all on different platforms, and they don't necessarily talk to each other. And this is the same problem we run with different electronic medical records. So, my electronic medical record in my office doesn't talk to the electronical medical record of the specialist that my patient is seeing. So even transferring that data, it's not easy. 

Patients have a lot of information. So, is there a way that we can get that information either through AI, or a validated app or some way that's integrated in my EMR, which auto-populates so that I don't have to spend all that time getting that information out? Like, is there a way that we can collaborate and get that together? So, I feel like technology that allows for that is really where we're going in the future. 

Why is it that, in 2023, I'm still sitting there typing everything you're telling me, and I'm pulling up a requisition, which is now digital as opposed to in my drawer that I had a pen and paper for, but I'm still pulling it out and I'm click, click, click, click, click, click, click, and then I'm sending it to the lab or I'm printing it off and giving it to you to go to the lab? And why is it that I still have to go and find that requisition that I want to give because you need an x-ray, and I still have to find it and click, click, click and then write my little thing and send it to you? 

Like, what I would love is, as I'm talking, why can't it just write my note for me? Why can't it identify specific demands or commands that I'm going to say that will bring out that lab rack, it'll already auto-populate, and it'll have faxed it to the patient through a portal and through the lab. 

If my patient needs access to see a specialist — let's take an example: mental health — it's very hard to get a counselor, it's very hard to get treatment for mental health. So, why can't I seamlessly have access to a service that allows them to do this from the comfort of their home, but it's still integrated with that circle of care with my EMR, all these resources that are there, right? Why can't we do this? And I'm going to answer some of that question.

There's some amazing companies that are doing this, who are developing these, in quote, "AI scribes," where they are going to listen to what I'm saying, and they're typing it along. And then there's other companies that are looking at billing, and looking at automating all this, and sending it, but it's really at the infancy right now.

And then we always run into that problem, and how do we integrate it? How do we take this separate platform and make it talk to the platform that I'm working in? How do they mesh together to make it seamless? And I think that's really where we need to be focusing on because once we can get that integration piece, then the others will come a little bit faster, I feel.

So, right now, technology is not this wonderful solution. Technology is just part of the solution. But it's just not there yet. And we just haven't figured out that integration, that kind of administrative burden part yet. But that's really where we're focusing.

So, in 5-10 years I'm hoping for a seamless integration, decreased administrative load, especially on physicians. We have to have a thoughtful strategic plan on how to get there, and it has to be multi-pronged, and it has to include patients — it really does. And it has to include who the end users. Whether it's physicians, whether it's allied health, whether it's someone else — it has to include the people that have to use it.

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Balogiannis: Dr. Amol Verma is a general internist and health services researcher at St. Michael's Hospital, and an assistant professor at the University of Toronto, as well as the co-lead for GEMINI, a hospital data and analytics network.

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Dr. Amol Verma: We're trying to generate insights from data and then, importantly, make those insights useful for clinicians and also have that new insight that we generate from data analytics actually translate to change in clinical care, and ultimately improve clinical care.

The insights and also the technologies we've developed are certainly translatable, and we'd love to see them spread across Canada. Of course, some of the challenges there relate to interprovincial data sharing, and those are issues that predate our work and will continue to exist, likely, for a long time. But we absolutely are hoping to continue to spread and share the insights that we've developed. And I'm really excited for the future.

I think there are a lot of opportunities and alignment at all levels of decision making, whether it be from the federal government to provincial governments to individual healthcare provider organizations, and increasingly to the people we serve — patients and people whose data it is, at the end of the day. 

I think everyone is kind of aligned around the value of the data, and so, I think, I'm really excited to see the next 10 years of how our regimes around data, including sort of privacy, but also security and innovation, and all the opportunities that will come from what I do really perceive to be a strong alignment throughout the whole system around the need and value of data, but also the importance of using it wisely.

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Dr. Verma: My most hopeful vision for health care 10 to 15 years from now is that clinical decisions will be guided by smart digital technologies, some of which will be based on artificial intelligence tools, that help clinicians access the right information to treat their patient, and put that in context for their specific patient. So, it's a tool or a series of tools and solutions that would say, hey, consider this problem for this patient or this treatment for this patient. And, importantly, those tools would also help reduce the burdensome and time-consuming daily administrative tasks that lead to more burnout — so, things like filling out forms, or excessive clinical documentation or billing, for example. 

Ultimately, this digitally enabled healthcare future would lead to physicians who are unencumbered by the daily grind of administrative, rote activities, so that they can apply their energies to being more humanistic, more compassionate, more caring, and spend more time with their patients, while at the same time be better decision makers because they have access to the right information at the right time.

I think it is centrally important that clinicians and patients and family members and caregivers are centrally involved in the development, design, and deployment of these kinds of new technologies, so that we're more likely to achieve the brighter version of the future where it's a better provider experience, and it's a better care experience. And I think that it is very reasonable right now for doctors to look at the range of the future possibilities with technology and think that we might go down a darker road or we might go down a brighter road because, I think, that option set is wide. And so, you know, I think it's crucially important right now that we have very engaged clinical leaders in this space because I do think the opportunities for a more sustainable, more humanistic, more compassionate healthcare system are at our fingertips if we push in the right direction.

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Balogiannis: Dr. Teodor Grantcharov is a professor of surgery at the University of Toronto and Keenan Chair of surgery at St. Michael's Hospital.

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Dr. Teodor Grantcharov: The output of the black box is deep analytics on things that matter — things like performance, efficiency, compliance to standard operating procedures. The black box today gives us information that can help the patient who will be in the operating room tomorrow. The future of the black box — and the future is almost here, in fact next month we're launching a new product that provides information in near real-time — so we want to help not only the patient who will be in the operating room tomorrow, but the patient who will be in the operating room today.

Getting this information before the patient has left the operating room, information that will guide us in the post-operative management in making the right decisions and making this transition from one size fits all, as far as post-operative management is concerned, to targeted, individualized, precise management, I think will be a fundamental change in surgical practice. So, I think we're all very excited to see the next thing in the development of the black box, which is real-time decision support and real-time information. 

I'm particularly excited about the opportunity to bring data to clinical practice, to change our approach of making decisions based on traditions and dogmas and replacing this with decisions based on data. Data-driven decisions are the future of clinical practice, not only in surgery but many other specialties. I think this fundamental shift to data-driven decision-making will help us provide better quality of care. I have no doubt that this will be the case. But also, it will help us make this shift from reactive safety, which is what we practice today, to proactive safety. And that will be the moment where we make this transition in health care from safe to ultra-safe.

A lot of device manufacturers, including robotic companies and others, are trying us, to make us believe that it's about the technology, that technology is going to solve all the problems of modern health care. That's not the case. We need to remember that technology, including AI, is just a tool — it's not the goal. The goal is still to build the right environment for teamwork, the right principles and processes and system factors that make it easy to do the right thing and difficult to do the wrong thing.

And again, the overall goal is, how do we provide the best possible care to our patients and the lowest possible cost? Whether technology can play a role, absolutely, but the role of technology is as a tool. And we also need to remember that technology needs a very robust evaluation because things that are developed to make us safer and more efficient often bring new risks that need to be evaluated prior to implementation. 

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Balogiannis: Dr. Muhammad Mamdani is the vice president of data science and advanced analytics at Unity Health Toronto, and the director of the University of Toronto Temerty Faculty of Medicine Centre for Artificial Intelligence, Research and Education. 

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Dr. Muhammad Mamdani: There has been significant federal and provincial interest and financial investment in the artificial intelligence strategy. So, for example, there's a renewal of funding for the artificial intelligence strategy in Canada and a major component of this is health AI. Now that fuels a lot of research, retention of top-notch data scientists, but when we go to the area of application it is quite different. 

It's a very different mindset; It's a very different set of problems that we work on. To really realize the benefits of academic AI, the applied AI needs a different angle. I'm not quite sure we've figured that out. What it takes is not simply, 'I've created a wonderful algorithm,' but I understand health care, I understand process, I understand workflows of clinicians, I understand human behavior, and how we can adapt these algorithms to what people need rather than what machines tell us to do. That's critical, and I don't think we've done enough thinking about it.

One of the core fundamental things we need is for hospitals to say, 'this is the priority for us. These technologies will help us provide much better care to our patients.’ So, we're going to ensure that we invest the right resources, time and effort to make this a reality. Not simply the research, but the application of these tools into clinical practice, and they can be resource intensive.

Personally, I would love to see many more hospitals commit to this sort of a strategic priority, and to be able to resource these sorts of activities, because we're certainly seeing considerable benefits that I hope other hospitals can see as well. 

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Dr. Mamdani: We need the academic advancements, for sure, but I think what's going to be transformative is how we collect, capture, use, and treat data. There continue to be significant and vast advancements in how we automate data collection and how we clean it in real-time and how we get it ready for machine learning algorithms and how we rapidly do compute. Significant advancements that are coming down the pipe, that is going to make the ability to be able to leverage data much easier — that's the foundation for AI.

Something that troubles me is that we often ignore the infrastructure part and the data part and jump right to the algorithms because that's the cool, flashy stuff. Uh, no. I think we're really shortchanging ourselves. We need to work on the infrastructure in the environment first and set the foundation to enable cutting edge AI. 

In the future, how do we manage our flow better in the emergency department where we're able to more accurately look at patient acuity, what their needs are in real-time? Can we actually say, hey, this patient, they're going to be waiting for eight hours, and it's not as though they're magically going to get much better. Maybe they can go home, come back in the morning? We can schedule them in at 9 am, and we can actually save them the stress and the anxiety of being in the emergency department when they don't need to be. 

But you need a lot of really good data for that — accurate timestamps, assessments of when they came in — and that data tends to be quite messy. So, I think as we progress to more structured, modern EPRs, as we refine our methods on how we collect data, we get people to change their behaviour in terms of 'we could do this if you collected A, B or C.' I think we could actually really change how we manage patients in the emergency department. 

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Balogiannis: This podcast is brought to you by the Ontario Medical Association and is edited and produced by Jodi Crawford Productions. To learn more about the Ontario Medical Association, please visit oma.org.

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