FOR WHAT IT'S WORTH with Blake Melnick
FOR WHAT IT'S WORTH with Blake Melnick
Making it Personal: How AI and Knowledge Management Can Transform Canadian Healthcare
What if your doctor knew everything about you—not just your medical history, but your genetics, lifestyle, environment, and social circumstances? Abbas Zavar, a physician and digital health leader with over 20 years of experience, believes this comprehensive approach is the key to fixing Canada's broken healthcare system.
Our conversation dives deep into the crisis facing Canadian healthcare: overcrowded emergency rooms, months-long wait times, physician shortages, and a system that waits for people to get sick instead of preventing illness. Dr. Zavar challenges this reactive model, proposing a revolutionary shift toward personalized, proactive medicine powered by artificial intelligence and knowledge management.
The vision is compelling: imagine AI systems that can gather comprehensive health data across five domains—medical records, genetic information, lifestyle factors, environmental exposures, and social determinants—then transform this information into actionable knowledge for physicians. These systems wouldn't replace doctors but would augment their capabilities, handling administrative burdens that currently consume up to 20 extra hours per week while providing critical insights at the point of care.
We explore real-world applications already emerging, like systems that can analyze a patient's genetic profile to determine which medications will be most effective for their unique biology. We also discuss the barriers to implementation, from data silos and interoperability challenges to the slow pace of policy development in the face of rapidly advancing technology.
Throughout our discussion,Abbas Zavar emphasizes that the goal isn't to remove humanity from healthcare but to enhance it—freeing physicians from administrative tasks so they can focus on providing compassionate care. As he puts it, "AI won't replace physicians, but physicians who use AI will replace those who don't."
Join us for this fascinating glimpse into the future of healthcare, where medicine isn't based on statistics but tailored specifically to you as an individual. Subscribe now to hear more conversations about how technology and innovation are reshaping our world.
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Making It Personal: How AI and Knowledge Management and Transform Healthcare in Canada
Blake Melnick: [00:00:00] Canada's healthcare system has long stood as a pillar of our national identity. Universal accessible and rooted in the belief that healthcare is a fundamental right for Canadians. But today that pillar is under mounting pressure from overcrowded emergency rooms and extensive wait times to a growing shortage of family, doctors and burnout among frontline staff.
The system is stretched to its breaking point. An aging population, chronic underfunding, uneven access to care, especially in rural and remote regions, and a lack of integration of medical data across the provinces have only compounded the challenge. As healthcare needs grow more complex, the system seems increasingly unable to keep up.
But what if the [00:01:00] solution isn't just more funding or more beds or more doctors, but a smarter, more personalized approach to care? My guest for this week's episode is a pioneering physician and digital health leader with over two decades of experience in medicine and health information technology. His career encompasses clinical practice, digital health consulting, and program management, showcasing his tech savvy expertise and unwavering commitment to transforming healthcare.
His research explores how we might reimagine healthcare delivery using personalized medicine, leveraging artificial intelligence to collect and consolidate data from a multitude of sources, and then applying knowledge management methodologies to turn that information into actionable knowledge. The goal to equip physicians with the insights they need to better understand and address the unique medical needs of each patient.[00:02:00]
In doing so, reduce the strain on the system by improving outcomes, efficiency, and patient care and satisfaction. In this episode, we explore the current crisis at Canadian Healthcare and a forward-looking vision into how innovation, data and knowledge might just help us find a way out. Introducing Abba Var MD from the University of Toronto's Institute of Health Policy Management and Evaluation.
abbas nice to have you on the show.
Abbas: Thanks for having me. Blake. Two chapters in my background, my original chapter from my home, Iran. I'm a trained family doctor, with expertise in different capacities. a clinician, as a researcher, as a faculty. My main expertise at that chapter was mental health and addiction [00:03:00] control.
I had several hats at that time, and it was the beginning of my understanding and learning about personalized medicine and digital health. Then I opened 10 years ago, my Canadian chapter came to Canada, more focused on digital health. I started a master of health informatics at University of Toronto. as a consultant, data scientist and digital health consultant, I work with different companies, right time, digital health lead in Interior MD teaching health informatics related courses, knowledge management, personalized medicine and AI in healthcare, at University of Toronto, TMU, former Ryerson and George Brown College. I'm an AI fellowship at a AMS and University of Toronto focusing on human centering of AI perspective. I'm doing my research, personal [00:04:00] research project in my consulting company.
Blake Melnick: Great. Sounds like you have a very busy life
let's just jump right into, the challenge itself. I always like to do a root cause analysis before we talk specifically about your research, and work. But would you agree that the Canadian healthcare system is in a state of crisis
Abbas: Yeah, for sure. Definitely.
It is multifactorial, but the main point is lack of human resource or physician nurses
In different capacities in Canada. And also the Canadian population is to age so they are facing more recurring diseases.
They are seeking more healthcare system services. We have lack of resources. We have increased the demand. And medicine is a knowledge base concept or science
Blake Melnick: right,
Abbas: We [00:05:00] have silo of data, raw data, and lack of knowledge. So , i'm focused on digital health and try to support current and existing physicians and clinicians,
Blake Melnick: It's always good to understand the problem you're trying to advance solutions towards. And clearly, you've touched on one of them, which is the magnitude of data.
But I think what we've been talking about is that it's very difficult with the limited number of physicians available, family, doctors, nurse practitioners, and so forth. It's very difficult to address the individual health needs of each patient.
I've noticed it and I'm sure everybody else has gone to the doctor. It feels like medicine by stats. So in other words, you're 50 years old, you should probably have a colonoscopy, but you might have needed that colonoscopy when you were 30, but if we're not doing the regular testing, we're not getting regular visits with our family doctor, then a [00:06:00] doctor is forced to prescribe treatment based on statistics.
Would you agree?
Abbas: Correct. Yep. Yep.
Blake Melnick: It seems like a very inefficient and ineffective way to treat patients and of course the other thing we haven't touched on is the wait times, the wait times to see a doctor. If you can get a doctor, and then if you require some sort of treatment, if you require something like an MRI, for example, there is a long wait in order to get that
, How do we get people the assessments that they need, in time. Before their illness becomes, too hard to treat.
The other issues, of course are the difference between the medical systems in the various provinces. For example I have a family member who lives in a small town and they're really struggling this particular person lives in a small community that is in one province, but much [00:07:00] closer to a major me major medical center in another province. And yet they can't go to that center because they're not from that province.
Abbas: This is one of those cause of my research project that not only Canadian healthcare system, most international healthcare system, they are reactive.
They are waiting until the person gets sick and then reach out the doctor. We are missing the opportunity of the healthcare system, to be proactive, identify risk factors for each individual and proactively support them before they need for a healthcare system or that emergency you mentioned.
We don't need that long waiting list or crowded emergency rooms. for this reason my current research project is focusing on that.
Blake Melnick: What are the [00:08:00] exact problems you're trying to solve with your research?
Abbas: I really like preventive approach in healthcare system and proactive approach. So this is the missing part in most healthcare systems. I really like to understand why they are not investing, is it political, financial, what is the main reason? But lots of those inefficient health services is because we are reactive. In our system. the other problem I'm focusing in my workshop, and my research project our system. We are collecting many data,
raw data in the silos, lack of interoperability lack of linkage. But we need to extract that knowledge so I really focusing on how this personalized proactive approach [00:09:00] and using all required data point of care. This is my main concern.
Blake Melnick: So is the reason this data is siloed, is it because of the technology being used or the different technologies that are being used across the country, different provinces, different medical system? Is that the problem?
Abbas: Yeah, this is one of the, causes there are lots of legislations or lack of act or policies as you mentioned, why your relative couldn't go' with the other province health services. The system of those provinces are different.
Their healthcare system approach or process is different. two hospital or two healthcare system, they are digitized, but their system following different data standard so they can't communicate to each other.
Lack of interoperability or even. both hospital, they are [00:10:00] using Epic as their data management system. Because of the privacy and policies.
they can't share their data.
All of this came with the silos of data,
Blake Melnick: So that becomes a privacy issue. As well the control of healthcare is at the provincial level rather than the federal level.
Abbas: Correct?
Blake Melnick: I've often thought we should have a federalized system because of this, but I know that, again, that's a, that's a political hot potato.
But, in some respects from the perspective of sharing data effectively, it would work a lot better if it was centralized and federalized, how are you proposing to deal with that?
Abbas: Before that one, I just wanna mention that. Canada Health Infoway is the federal agency focusing all this stuff in Canada
Agency under Health Canada. They invested across country as a patient summary project. they are following the standard of data as a [00:11:00] patient summary from all systems, from all provinces.
Blake Melnick: I see.
Abbas: they are creating a specific data. For example, my data in my family doctor EMR system to that dataset database. My summary is there and anytime I go to any hospitals or any other doctor is automatically updated and they have access to it. So they are focusing on that one and hopefully they can launch it
Blake Melnick: if I understand you correctly, basically they're taking the data sets from all the provincial medical systems and then using another technology to standardize it or to combine it. So it's interoperable, that's pretty complex.
Abbas: But it's not all of my information for example, my main diseases, my last medication, my immunization, allergies, some standard patient summary. It's an template. They are following that standard.
Blake Melnick: I [00:12:00] see. Okay. So that makes some sense to me. 'cause I was thinking, British Columbia, , has done a wonderful job managing patient data within the province. It's very accessible. It's on my phone. I can look at every single visit I've had to the hospital to a doctor. Every single test I've had, every single COVID shot I've had immunization. It's all there really accessible as long as people have my thumbprint to get access to it.
Let's talk a little bit about how you define personalized medicine. 'cause I think it's important for listeners to understand your perspective as a researcher and as a medical practitioner,
Abbas: I got familiar with the personalized medicine approach when I was in Iran because I founded the first. Private preventive medicine institute. And at that time I started focusing on how prevention can be more effective in our system. And then I got familiar with personalized medicine approach that sounds very fantastic to [00:13:00] me and create this vision for me.
This is the ideal version of healthcare system. This is my definition borrowing from many organization providing the right clinical intervention, whether it is diagnosis, treatment, or prevention at the right time for the right individual. This is the ideal healthcare system
we are far away of that. three years ago, I. Started a big study with my students to interview executive people in different level of Ontario healthcare system and also literature review. we realized that four data domains are recommended for this holistic approach. all health data, including my hospital data, my family doctor, my lab result imaging, my pharmacy, my dentist, all of them are healthcare. The second one is omics. Data. [00:14:00] Genomics is the most famous
But we have proteomics, metabolomics, or microbiomics biological factors. The third one is a lifestyle about my diet activity, a sleep pattern. Substance use or abuse, mental health status sexual health, all of those information under lifestyle. And then environmental. Everything out of our body, we call it exposome. Could be chemical, air, , toxin. Physical would be radiation, sound, noise or the other physical and biological viruses or bacteria. And occupational health is a sub component of this environmental, most publications four years ago, focusing on four data domains and we realized that , there is a gap. Social determinant of health. So , we publish that [00:15:00] research, as a white paper, we recommended that social determinant of health must be considered as the fifth data domain.
Blake Melnick: What do you mean by that?
Abbas: We came up with the map of data after that project. So for example disabilities or gender and gender identity, food insecurity, access to health services. All of them are important when you wanna make a personalized interaction and they are not under any of those other four data domains. So for this reason, we recommend that this should be considered, as I mentioned, prevention is really important to me. So then I start to, put all these pieces together, how can we provide a personalized preventive plan by collating all of this data and put at the My Family Doctor's EMR system, I'm sure that my family doctor doesn't [00:16:00] know about my occupation right now my focus is on how we can automate it, collected this data with valid assessment tool from the patient. Reaching EMR data and identify potential risk factor, then we proactively have a plan for each people prevention or treatment or diagnosis.
Blake Melnick: So that's a lot of data that you're talking about.
Before we jump into how you're proposing to deal with that, I wanted to talk a little bit about the genetic piece because I can just hear people going, I don't want the government having access to all my genetic data.
And of course, I can't remember what the name of the DNA company that data breach
Abbas: 21 and me, something like
Blake Melnick: That's right. I'm thinking that's a real frightening thing for people that all of that data could be exposed
are you worried about that?
Abbas: Yes and no.
Yes. Because if [00:17:00] information act or access to any people, they can
it for any reason. So that would be the concern of the system or those healthcare system, governmental, how can make it secure. Data and any other information we are concerned about, our bank information may
Blake Melnick: Sure. Yeah.
Abbas: other thing. that would be another one. This is my personal genetic bank information.
This is a concern, but that information is the most personalized information I can share with my family doctors to provide, customize treatment or prevention
Blake Melnick: the importance of it is evident. But again, I think that you're gonna have a lot of people that'll say, wait a second that's way too much personal information, and data, being held in a government database and I'm not really confident that the security [00:18:00] is robust enough, and I'm not really sure there is such a thing as a robust enough security system to protect that kind of data.
I think it's an ongoing battle between the hackers and, and the cybersecurity people.
Abbas: we have that.
Blake Melnick: That's a huge corpus of data that you're after there and almost impossible to collect without some form of assistance.
And I think that's where we're gonna talk about the role of artificial intelligence which is another a difficult topic. A lot of people have their thoughts about how much we should be invested in artificial intelligence. But before we do that, I think it's important to point out to people listen to the show and they hear your comments about how you propose to use ai to help collect and sort this data, that the goal, and this is where the knowledge management piece fits is to actually create more knowledgeable physicians and better practitioners.
I come from a family of doctors. My grandfather, who was a doctor used to say , it's about treating the patient. As much as it is about treating the illness,
Abbas: [00:19:00] yes, correct. You mentioned About the huge data. We have a specific terminology in data science. We call it big data. One third of all generated data globally is healthcare data. And based on the recent statistic one exabyte is equal with 1 billion gigabyte. And by 2025, we have created 10,000 exabytes data. It means one, one with 19 zeros, just health data,
We created that much and excluding omics data, lifestyle, my smart watch, a smartphone variables, environmental, not just that health data.
If we wanna, transform the raw data to information, the knowledge and clinical insight. This is out of human mind capability.
[00:20:00] All this data that any physicians or clinicians at the point of care at the moment, connected all this information. They are siloed.
Even they have it in the EMR. They should connect all of it, , and also connect it with most recent publication articles updated clinical guidelines. All of them together in five minutes make the best decision for you.
Blake Melnick: right.
Abbas: So it's a tough task. And this is the reason for the burnout of physicians right our system. So this is why . I love ai, call it not artificial intelligence, call it, augmented intelligence
Blake Melnick: Sure.
Abbas: can support physicians at that point of care to connect it all dots, find the patterns, match with clinical guideline updated with published articles, and offer all decision suggestion [00:21:00] to the physician to make the best decision for me.
Blake Melnick: Yeah, it's almost like a decision support system.
Abbas: Exactly.
Blake Melnick: I think,
Abbas: manage.
Blake Melnick: Walk me through this, in an ideal world, I know we're not there yet, I'm sure there are firms, companies, individuals beyond yourself that are working on an ai an augmented reality capability in healthcare and medicine is that true? There are a lot of companies working on this.
Abbas: Yeah, definitely. Right now it's a hot topic around the world and also in the healthcare system. We are a little behind other industries because of the silos of data. are very restricted privacy and security sensitivity of the health data. But this is my job in Ontario md focusing on how we can evaluate AI enabled solutions and fuctions and make sure that they have enough benefits for physician and make a good [00:22:00] role of augmented intelligence.
So in OntarioMD, we have for the first time evaluated AI scribe. a solution that can listen to the patient and physician conversation, understand it, transcribe it, and make it. Standard medical note. So it's reduced the time of documentation for physicians, and the most important thing, improve the relationship between patient and physicians because usually physician focusing on taking note in the computer, not facing to the patient, right now they are free. They are communicating face to face and they are sure that an AI is taking note carefully.
Blake Melnick: That makes sense. It'd be the same as copilot ai which, works on the corpus of data that you are creating. So putting the creator, or in this case the physician and the patient at the center and the AI is actually, scribing or transcribing that [00:23:00] conversation and making notes that they're seeing connections between areas that might suggest a particular problem or an issue that the physician needs to look at. It's what I would call old AI where you create a knowledge base with data from a subject matter expert, which allows a newly minted technician to draw on this expertise when engaged in troubleshooting diagnostics or problem solving. And if there was a problem that no one had seen before, it would represent new knowledge. That could then be incorporated into the knowledge base for future use by technicians. But what about when AI starts thinking for itself?
Abbas: This is concern about AI as you mentioned. So this is new era. just recall that first time we. Have been introduced to internet or a smartphone. it was one step improvement or enhancement in human [00:24:00] capacities. AI is another advanced technology added to our life. So we need get used to it, but because of those concern we need well-defined guardrails for how much automation should be included in our life
This is the main concern. All AI
conferences or AI policy makers, they are focusing on. How they can make these rules and principles for ai. But this is new life. We should get used to it.
Blake Melnick: We're not going backwards on this one. It's already out there. And I think this is what the concern of people like Jeffrey Hinton from the University of Toronto has around AI and what it gets to that generative form.
But I know this is going to be a fear of a lot of people because, there's a lot of people that really don't understand.
Ai don't use it on a regular basis, are afraid to use it. And then there's a lot of people that are really against the consumptive nature of [00:25:00] ai. The energy it requires for every query is significant. And then all of a sudden when it becomes pervasive in all fields of endeavor across our society, the energy requirements are massive.
Abbas: Correct.
Blake Melnick: do you think about that? How do we deal with that? And as you say, medical data is the biggest source of data that AI will be working with.
Abbas: Yeah, for sure. But this maybe the most appropriate solutions for many of our problems. As I mentioned right now family physicians or most of physicians, there are burnout because of the, lack of interoperability.
EMR system is not well connected with all sorts of information. They are bombarding with many inputs coming from hospital pharmacy lab consulting insurance company in their EMR system. Their
inbox is messy. they need [00:26:00] based on the most recent research 20 hours extra of their. Clinic time, to work on documentation and clean their EMR system per week.
Huge. So AI can easily fix that Missy EMR inbox.
Blake Melnick: Yes, I agree.
Abbas: They can support them to make that documentation. They can connect all those silos of information, connect dots, find risk factors, find the pattern, offer some suggestion
Decision support. After each visit. They should find the best codes or billing codes claim that visit. AI can easily do that
AI can follow up with you, schedule . You. right now I'm working on how an AI agent in future, , reach out to me through conversation.
Ask about those lack of information in my EMR or [00:27:00] profile. Oh, let me know about your occupation, let me know about your activity and gathering this information and put in my family doctor, EMR. all of this can happened. I envision all of these functions in a primary care workflow, pre visit, end visit, and post each step.
Can be optimized or improve by AI solution I mapped out everything. I published it in Ontario, MD blog. Some of them just idea.
So that would be a great idea for a startup company or those invested on ai, but for many of them we have, available solution in the market. we just need a policy how we can integrate it to each other and make a full AI integrated healthcare system
Blake Melnick: We've all heard the stories about how your phone is listening all the time, so isn't that the conduit for [00:28:00] everything that we're talking about? Everybody seems to have a cell phone.
If that's always listing, as you just said, the additional gaps in your medical history, lifestyle or habits exercise and so forth. That can all be collected. by Your phone, and then, the question is what happens to it then and who owns it at that point? These are big questions and I'm not expecting you to be able to address all of them, but they are the things that we'll have to be concerned about as we advance forward in this AI supported world.
The biggest pushback you're gonna have is jobs, right? And this is where we're gonna talk a little bit about knowledge management, because, you're not suggesting that AI is going to replace the physician, correct?
Abbas: Not a hundred percent. I'm not sure.
But my thought is AI don't replace physicians, but those physicians that are using AI replace the others.
Blake Melnick: That's a great point. In fact, through the application knowledge [00:29:00] management principles, practices and methodologies, what we should be getting is better medical practitioners, more knowledgeable, better able to perform differential diagnoses.
But what's the thing that AI can't replace? That's how I wanted to flip this question a bit. So let's assume that your hypothesis goes forward and your work is greatly successful. And we move into this era where we can create a personalized medicine approach to dealing with patients through the, accumulation access and use of this data.
What can't it do?
Abbas: This is exactly I try to learn and improve it in my AI fellowship. This is human-centric fellowship. So we are focusing on more ethical perspective, but the most important thing , about compassionate care that a human can provide for other human
How Integration AI to our [00:30:00] system. But this compassionate care should be our main priority in our system I don't think in near future AI can do it. But I'm not sure about the late future. Nobody knows. Maybe AI can do that.
Blake Melnick: I know for example, when I've been experimenting with it with this podcast, I wrote a satirical piece and I was interested to see whether AI understood satire It did not, this is heuristics, this is language, but it's meaning that lies underneath the surface that AI was not able to understand at all.
It took everything quite literally. It didn't understand what I was doing. But this is of course a major concern that people are going to have is displacement. And there's no doubt about it.
It's gonna happen across a number of different industries. I think you and I maybe had this conversation, our pre-call, but the question for each of us is, are you gonna become a passenger or are you gonna become the [00:31:00] driver or a pilot? And I think that's what people have to start turning their minds to is what do you want be, I don't think, as they say, the horse is out of the barn.
We're not going back. But let's look at the knowledge management piece. We've got this big corpus of data. AI is helping to sort it all and, and bring it all together. How is that being converted into clinical knowledge?
Abbas: I believe that one of the basic definition for knowledge management is providing the right knowledge to the right person at the right time,
Blake Melnick: Yep. That's the elevator pitch. Sure. Yep.
Abbas: brief one. Yeah. So it's very aligned with a definition of clinical decision
How can we transform all of those siloed and not interlinked data, health, data, omic data, lifestyle, environmental, occupational, social, determinant of health appropriately connect them, interlink them, and find the pattern. [00:32:00] And providing clinical insight at the point of care as an augmented intelligence to support any physicians or clinicians to make a better decision for us.
The core of knowledge management I see as a clinical decision support in personalized medicine approach?
Blake Melnick: Do you think that it will have an impact or significantly change the way doctors are trained?
Abbas: definitely. I'm not sure if I can name the company or solutions in our conversation, I found a fantastic solution. It's not Canadian, it's at American One. They integrating patient genomic or DNA analysis, synthesis to the EMR system and also pharmacogenomic information. So currently they have this live EMR with all this information integrated. [00:33:00] So at the. point of care. When I as a physician, wanna prescribe a new antidepressant for my patient. Their EMR system showed that the most common category of antidepressant is contraindicated for this patient.
The next two option is you can use it with caution. the last, three options is the best treatment only for this patient of all of those pharmacogenomics and genomics information.
Imagine if you integrated lifestyle, environmental,
so this is fantastic. And even with the same sex, same age, same disease, other patient, all of this suggestion would be different
Blake Melnick: , As you were talking, I was thinking, are we gonna need doctors at all down the road? I guess we might need them to perform some of the procedures and things like that, unless robots are doing it.
It's a [00:34:00] fascinating application of both AI and knowledge management. Because certainly by doing this at the scale that you're imagining, it will inform how doctors are trained.
How they do their internships. I think it allows them to focus on the patient and as you say, maybe this is at the metacognitive level, focusing on the person rather than the illness or kind of right back to that, training doctors in empathy or we used to call it bedside manner.
Oftentimes, you go to the doctor and depending on their ability around progressive inquiry to ask you the right questions in the right way. You find it hard to articulate.
What may be wrong with you? Number one, you could be afraid to tell anybody that you have this problem. And I think that happens more often than most people would think. But it's also, do I feel comfortable with this person to discuss this with them?
Do I [00:35:00] feel that I can open myself up honestly with this person, because they're actually engaging with me, not looking at the computer screen or looking at their watch to go I, you got 15 minutes before my next patient.
It adds a different dimension, I think, to medical training. To help them better engage with the patient and become more personal as you say.
This is a grand vision that you have and how far away are we, what are the barriers that you face?
Abbas: It is a good question. There are lots of gaps. I see lots of enablers at the provincial level or at the federal level and international level to resolving any of those issue or gaps. Improving interoperability. We came with this common data standard HL seven fire many our system that are following Doon That would be, for example. International language of [00:36:00] data around the world
they cannot understand each other
Blake Melnick: Yeah,
Abbas: each other, so
Interoperability. We are integrating ai, so, clean our data, link our data, transform data to knowledge. All of them are enablers but the only thing that I see is we are really slow in policy making. 2022 after chat, GPT came up, it was explosion of ai.
So how much policy or legislative. Created in Canada based on that in healthcare system, about those rules, about those guardrails. We are very slow adoption with that fast, rapid technology enhancement, these two speed do not match and this make problem.
Blake Melnick: that's a great point. You're right. Policy's not keeping up with development of the technology. It's moving so [00:37:00] fast and by the time you get the policy rolled out, it's probably slightly irrelevant because it's not addressing where the technology is.
Let's put it that way, at that present point in time. So that is a problem. I wonder if there's a solution in what you're suggesting for medicine in terms of health policy as well. But that's probably a topic for another show. So for you, where is your focus now for the next few years? And, feel free to tell us who you're working with or who's working with you and who's behind this push towards more personalized medicine.
Abbas: Currently I am working on how can I collect all required information that usually missing in family doctors, EMR system about occupational health, diet, activity, sleep pattern sexual health, mental status, social status. even multicultural, Canadians communities, have many spiritual behaviors [00:38:00] or thoughts can affect our health status positively or negatively. We need this data. We have lack of this information. So I started to put a package of standard and valid questionnaire to collect all this data with my students as a course assignment. And after I presented in conferences or on my LinkedIn. And many other clinicians and physicians joined this project. This is a huge research project, almost 60 people working with me.
Identify 16 topics that we need to find the best assessment tool for any of them. And . Special thanks to Canada Health.
Infoway funded our research project and we are at the end of phase one selected best valid, reliable questionnaire for any of those 16 topics. vision is [00:39:00] create a map of potential risk factors we can capture by using these assessment tools.
test Them out with any potential disease and disorder. This knowledge base is required for future AI algorithm development
support my vision my future vision of proactive prevention.
Blake Melnick: Will you do a control group study on this? Will you get a, slice of the population and collect all of these data points that we've discussed in this interview and see how , those can be interpreted by the AI can take this massive corpus of data along the lines that you've suggested, health, medical spiritual, and so on and so forth.
Abbas: We define our current project in multi phases. Currently, as I said, we are completing our phase one, that would be next phases. Hopefully if we fund it with any organization, we can continue our research project. Definitely. We have to pilot it, [00:40:00] we have to test it out how can it be integrated to healthcare system. One of the concern about my research project is we make it this automated and any of this information automatically sit in the EMR system,
It make responsibility for the physicians.
We need to find the best approach, how we can deal with this. maybe then that would be a barrier we need to find the best way how we can integrate it to the system.
Blake Melnick: I raised that one simply in case some of our listeners may wanna volunteer. If you're, if you do run
Abbas: my
Blake Melnick: a control group study at some point they could reach out to you. I would make a final point here is that by the opportunity you gave me to speak to some of your students at the University of Toronto around knowledge management, a lot of them gave me some feedback after the presentation.
And one of the things they took a certain umbridge to was a hierarchical KM model that I had shown them that basically said, look people at the [00:41:00] top technology at the bottom of the pyramid. And it was really to say, there's two views around the use of this kind of technology technology of use versus use of technology technology of use is more what we're talking about here in the context of this interview.
We're using AI algorithms really to help produce better doctors, nurse practitioners, and so forth. But you're not suggesting we're replacing human beings with ai. What we're saying is we're using AI and again, a technology of use to help doctors do a better job in diagnostics, patient-centered care and making it more personal.
So I wanted to end on that note because I think it's an important one, and I did tell your students that I would address it
Abbas: hundred percent
Blake Melnick: Abbas it was great to talk to you. This is a fascinating subject. I'll follow your work. I hope you'll consider coming back on the show as you work through some of your research.
When I put this out to people that I was doing this show, I got a lot of response from people who [00:42:00] are very passionate about this. So I'm hoping you'll agree to come back on the show 'cause this is fascinating stuff and I think it's a real problem in our system.
We need to address it. And certainly you're one of the pioneers working on this. So I really appreciate your time today.
Abbas: Yeah, my pleasure. Thanks for having me.
Blake Melnick: Well, that's it for this week's episode of for what it's Worth, called Making It Personal with my guest, Abbas Zavar from the University of Toronto's Institute of Health Policy Management and Evaluation. Today we took a deep dive into the crisis facing the Canadian healthcare System, exploring the root causes from physician shortages and long wait times to siloed medical data and a system that is often reactive rather than proactive.
Azavar laid out a compelling vision for the future. One where personalized medicine, artificial intelligence, and knowledge management come together to transform raw data from a myriad of sources into actionable knowledge and [00:43:00] meaningful medical insights. The goal isn't to replace physicians, but to support them, freeing them from administrative burdens so they can focus on what really matters.
Addressing the individual needs of every patient with knowledge, compassion, and care. As Abbas Zavar reminded us, the real opportunity lies in making healthcare proactive and personal, empowering both practitioners and patients to achieve better outcomes. I'll be watching his research closely, and I look forward to having him back on the show in the near future.
So thanks for listening, and until next time, I'm Blake Melnick. For what it's worth.
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