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Exploring Precision Medical Education

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In this episode, CLIME Associate Director, Kate Mulligan talks with Michael Campion about precision medical education. They explore how personalized learning approaches could enhance the training of future healthcare professionals. Join us as we discuss innovative strategies for integrating data-driven insights into curriculum and assessment, fostering individualized learning paths, and ultimately improving outcomes in medical education.

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[Intro Music]

Amanda Garza: Welcome to CLIMEcasts. I'm Amanda Garza, the CLIME Program Manager. In today's episode, we're excited to bring you a conversation between CLIME Associate Director Kate Mulligan and Michael Campion on the topic of precision medical education. Before we dive in, here's a bit about our guest. 

Michael Campion serves as the Director of Academic and Learning Technologies at the University of Washington School of Medicine, where he and his team collaborate with faculty, staff, and students to enhance medical education through the effective use of technology and data. This includes everything from instructional design and course management to media production, data dashboards, and educational data governance.

Michael also co leads the UW School of Medicine's initiatives in exploring artificial intelligence and medical student education, as well as the Innovations in Curriculum Design and Delivery workgroup. He has served in various national committees and workgroups that connect education, technology, and medicine, and he is the immediate past chair of the Group on Information Resources within the Association of American Medical Colleges.

Let's join Kate and Michael as they discuss the future of medical education and how precision approaches are shaping the way we teach and learn.

[00:01:13] Kate Mulligan: Michael, it's really exciting for me to have you on to talk on CLIMEcast today. I know I've been wanting to do this for a long time, so thank you for joining us. I think it's fun for our listeners to hear about how people got to where they are, and so would you like to share a little bit about your background before you came to UW?

[00:01:28] Michael Campion: Sure, so my first career out of undergrad was, actually in development, while I was doing that, I was working in the College of Engineering, doing fundraising with corporations at the time and foundations and I really became interested in the intersection of education and technology and started to do a master's degree program while I was working in the College of Education. 

At UW? At UW. Oh, nice. And so I got my Master's of Education from UW in Curriculum and Instruction, with an emphasis in Educational Technology. And so that kind of set me up well when there was an opening in the College of Engineering to take over their distance learning program. I was able to move into that role and that was at a time where we were still doing broadcast television of lectures, and driving VHS tapes around to different corporate sites in the Puget Sound area. At the same time that I was coming in, there was a big move to online learning and streaming video of lectures and that sort of thing.

That program kind of got moved over into what was then educational outreach. It's now UW Continuum College So I took on a role there as director of online learning and then when I saw this opportunity in the School of Medicine come up, it sounded like a great opportunity to be part of more of a traditional academic program with actual students in, you know, live students in person, making use of technology that, was also useful for online programs.

And so, started as a department of one in the School of Medicine, for academic and learning technologies. And, we've been able to grow it into a lot of areas that, have been important for the school. So, things like, even things as simple as just course websites back in the day were just, you remember this, Kate they were painful and traumatic. Exactly. And having a common system to house those sites and have some structure to it video casting of lectures, streaming video of lectures, video conferencing has been important, throughout the years and has been a focus at different times. So connecting all of our WWAMI sites and then really being involved in that kind of design and delivery of curriculum, and instructional design. In more recent years, more focused on data so our systems are generating a lot of data, we're pulling it into a data warehouse and then, not only that, but how do we govern that data? How do we make sure that it's being used well and as it's intended to, so, that's been a big effort as well.

And then a lot of the emphasis just in the past year or two has been on AI. Yes. Because that has really just, come to the surface for everybody and lots of interest and creativity around how it could be used in medical education. So, that has been the career progression, if you will, but another part that has been really important to me recently or in the last several years has been work at more of the national level, and being involved in different projects and committees, mainly through AAMC.

[00:04:16] Kate Mulligan: I wanted to get the word out about that because I think you have some resources or some information broader view of things from outside, outside of our UW microcosm that would be great to share. And that's what we're going to be talking a little bit about today. Perfect. Okay, so today I know we had a long list of things that we could have talked to you about and maybe we'll have you back again.

But for today, I wanted to tap your fund of knowledge about precision medical education, partly because I just like the term, but I found a definition to start us off. According to the AAMC, Precision medical education can be described as the tailoring of education to the specific characteristics of the individual learner.

I think it's a steal from the area of precision medicine, which denotes health care strategies that intentionally incorporate individual patient variability. Another way of describing precision medical education is simply delivering the right education to the right learner at the right time, which is nice and straightforward.

Yep. Uh, and resonates, I think, straight away with that just about anyone who hears that term, would you like to comment on these two definitions and maybe elaborate on why you think that precision medical education is crucial to know about now? 

[00:05:27] Michael Campion: Sure, so, precision medical education does borrow from precision medicine, and you're right that's really focused on the uniqueness of each patient, from a genetic standpoint. From an environmental standpoint, from lifestyle data, and so really being able to improve disease prevention and treatment based on those factors. So a lot of this has to do with the fact that our genetic data is much more known to us just in the last 10 or 20 years.

And, so there has been just a ton of research on genetic markers that predict a disease, that could develop or provide direction on how a disease might be treated. And so really trying to make use of that information that would never was really available to medical professionals and now is. has really transformed how medical care can be delivered. And so if you think about borrowing those concepts, for medical education, really, what we're doing is, shifting the focus to the learner from the patient to the learner and kind of taking those same approaches more from a teaching and learning standpoint and recognizing that each student is truly unique.

 Each person comes in with different academic background on different abilities, different lived experiences, and really different goals for what they're going to be doing in the future. And so how do we tailor education in a way that really leverages what people are bringing to the program and where they want to go with it, rather than having kind of a one size fits all, or even kind of a one size fits most type of program, trying to make it much more customized to the individual learner.

[00:07:07] Kate Mulligan: I love this, the fact that it sounds like it's a much more holistic approach to our students and that strongly resonant with me and I think faculty in the UW Medical System who feel that we don't get to see enough of the students or, you know, help them more individually, so, it's good for me.

[00:07:25] Michael Campion: Right, and, but very similar to, Precision Medicine with its focus on genetic data and We don't have a genome for, for a student, right? But what we can do is collect more and more information. Our systems are already collecting a ton of information about students. And so what can we take from that that could be useful in how you as an educator or others in different roles kind of interact with that student and what is appropriate for you to know about that person and decide making those decisions consciously up front.

 So that we can give the right information to the right person at the right time. Kind of what you're really describing is kind of those, correct interventions. So that's really kind of the ultimate goal of what we're talking about. 

[00:08:08] Kate Mulligan: So at its best, I think it sounds holistic and possibly more efficient once you've got infrastructure, which can be really expensive.

Right. Yeah. 

[00:08:17] Michael Campion: So, you know, another area that, in kind of society that is making use of the same kind of data is professional sports. So, like, Kate, are you a baseball fan? Funny you should mention that. I went to my very first baseball game last Friday when the Mariners won against the Phillies. But not much. So, uh, but there's been this huge trend in sports analytics.

And so, you know, the book Moneyball, was really one of the first, kind of entries into, popular culture about this topic. But taking all sorts of just minute data about a baseball game. So the spin of the ball when the pitcher pitches the ball, or what is the velocity off the bat, and is that going to tell us anything about how likely it is to be a home run? And so people are tracking these things on a very minute level and coming up with new statistical categories that didn't exist before because there's the ability to capture the information. And so similarly, when we talk about medical education, we're capturing more data than we've ever captured before, and we have the opportunity to capture even more than that.

And so what's going to be useful? What are the new categories of information that we're going to find valuable about our students in the future? Is really kind of an interesting question, because we don't necessarily know. We might have some ideas about what leads to student success, but, uh, how do we really kind of define that going forward is something that is going to be really interesting. And it is tied into a broader concept that is current right now, which is competency based medical education. So CBME is trying to shift how we assess our learners. So that it's not just about what they know, but also about other aspects of medical care. So communication skills, for example, or other areas where you wouldn't be able to necessarily test them on a multiple choice test.

Uh and this is a broader trend that is going to be really important, not only at our school, but nationally. But here, we are beginning to make moves towards CBME in the clinical phases, not so much foundations yet. But the idea of precision medical education really can be supportive of broader initiatives that are focused on CBME.

So that's another reason that I think that it's really interesting at this time. 

[00:10:43] Kate Mulligan: And I should jump in just now and say that for our newer faculty, or the ones involved in those multiple choice assessments in foundations, who aren't that familiar with competency based medical education, we will have some links and resources in the, in the episode notes that you can go and educate yourself about there.

Yep. Great. So, so why is precision medical education, especially fascinating to you? I think I know the answer, but we'll flesh it out. 

[00:11:06] Michael Campion: As we've been talking about, it's very dependent on technology and data. So the technology that generates the data and then the data itself that we can use to have a better holistic picture of our students and our program. And so the process of collecting all of that information and managing it is, you know, something that I mentioned we've been focusing on for the last several years, and this kind of takes it to another level. In particular, this question of how do we govern that data? How do we make sure that we are using it appropriately, and in ways that are really kind of intended for the benefit of our, our students, as well as for the, the medical profession. The other part of it is that, a lot of this is going to rely on use of new AI technologies and other emerging technologies. So, it's kind of bringing together so many of these things that are, that we're already interested in, and giving it a unified banner, essentially, uh, that we can possibly start thinking about these things.

Yeah, it feels kind of huge, actually. Well, and it is huge. It's not just about the technology and the systems and the supporting students, but this is really a cultural question and I think that's where it also is kind of fascinating that gets to much bigger questions of, what does it mean to succeed as a student, as a physician? Faculty. As faculty, right. How do we define that? And there's obviously not going to be a single definition for everybody, but, what are the factors that should go into it? It's thinking about it in ways that kind of break it down, but also try to look at the whole. 

[00:12:41] Kate Mulligan: It also sounds to me like, precision medical education might be introduce more of the learner's voice.

So if you talk about what it is to succeed, it's not just what this institution wants of their students, it's what the students want for themselves. And so I think that part of it also is really appealing. 

[00:13:01] Michael Campion: Absolutely. And, and I think that we need to be talking more conscientiously about that, about bringing student voices into that conversation because oftentimes when you hear people talking about precision medical education, they don't really have that student voice in place, but it really is kind of one of the pillars of how it should be approached. And so, I think that that would be tremendous to, to try to get student input on that.

Again, I think you're going to hear, you know, out of 275 students, you'll probably hear 275 different answers to what student success looks like, but the more that we can try to have all of those voices at the table, the better.

[00:13:38] Kate Mulligan: Great, thanks Michael. I know there are a number of precision medical education projects and initiatives across the country that you know about. I was wondering if you could maybe flesh out a little bit more for us some of the common characteristics of those programs. 

[00:13:51] Michael Campion: Yeah, so, the paper that really outlined a lot of this just came out a year ago. It was July of 23 and Mark Triola and Jesse Burke Raphael from NYU published this paper on precision medical education where they really did make the connection to precision medicine and borrowed a framework that came from precision medicine, called the, the P4 framework. And so, what they were doing is to say, let's translate that to precision medical education.

And so in the translated version, the four Ps are proactive, so we're getting continuous insights, and not just reacting to, like, major events. We're not just saying somebody failed a course and so therefore they should do something. It's more kind of on, on a micro basis that we're looking at the data and it's on a continuous stream.

 The second P is personalized, so these interventions should be specific to the unique needs of the individual learner. And because we have so much information about the learner, we should know what those unique needs are and we can translate, uh, kind of whatever the event is into an intervention that is specific to them.

The third P is participatory, kind of what we were just discussing, that learners really need to be part of the process and really co creators to ensure that whatever intervention takes place is valuable to them and their goals. And then finally, predictive so we should have evidence that, any sort of predicted outcome is valid based on previous, experience with other learners.

So, we need to make sure that we're using good predictive models and statistical methods, as we go through the whole thing. Okay. 

[00:15:28] Kate Mulligan: Great. So just to summarize, four Ps, proactive, personalized, participatory, and predictive. Exactly. Excellent. Love it. Okay. So now, can you give us the little story side of it? Like what are some of these projects that you think are interesting and doing well? 

[00:15:43] Michael Campion: So, the first area is probably in the automated alert area. So, when a student, uh, does poorly on an exam, for example, or doesn't meet their learning and goals, that there would be an automated notification that would either go to them directly or to a coach or other type of educator who would be able to create the right intervention.

And so we're actually doing some of this already with our proactive advising application that was developed here within the school of medicine. And, so we have a number of automated alerts that get generated. And go to student affairs deans and to proactive advising within student affairs, and they can work with the students as appropriate, given whatever that situation might be.

So this is a small step in that direction, and I think that there is more that we could do with that. There are additional people who could be notified, there are additional alerts that could be automated, but we're at least making some small steps in that direction. Other schools have done other things with, like, getting granular data from OSCEs and doing similar interventions.

Or even things like, did somebody turn in an assignment? Do they have, have they developed a pattern of not turning in assignments on time? Or maybe they've kind of disconnected from learning platforms, and so using kind of the analytics data that come from the LMS, for example, in learning management system, and saying that, that students may not be keeping up because they're not accessing materials.

So, other schools have focused on some of that and generated these types of alerts. 

[00:17:16] Kate Mulligan: Interesting, yeah, thanks for sharing about the proactive advising. I wasn't aware of that program in UWE. How long has that been going on here? 

[00:17:23] Michael Campion: I think, first launched it in 2019, maybe 2020 either just before or just early in the pandemic days, uh, but it's really intended to be kind of taking the metaphor of an electronic medical record, but applying that to students.

So it's similar to precision medicine being applied to teaching and learning, kind of taking that metaphor of an electronic health record and applying it to the student, as the patient, essentially. So can we have, valuable information in one place that people can go to see test results and be able to design action plans, for example, like what kind of followup does the student need?

[00:17:59] Kate Mulligan: Great, thank you. Yeah. I feel anything that can help us understand a student's struggles, As early as we can, is going to be super helpful. And those struggles aren't necessarily purely academic, but something like withdrawing from the class in some way is important information. So. 

[00:18:19] Michael Campion: And then some other schools are taking some of that even a step further with this concept of nudges. So, getting not just like failed an exam, but if a student got several questions wrong about asthma, Uh, just as an example, being able to take that in and automatically generate some resources that that could be sent to them systematically about, Hey, I see that you, you didn't do so well on these asthma questions.

Here's some videos about asthma that you might want to review before the next test or before a final exam, without any human intervention, which is. It's interesting to think about all the steps in that process, and how would that be received by the learner? Is that something that they're going to take as a positive suggestion that they say, yes, I actually want to learn more about asthma so that I can do better in the future?

Or is it like yet another thing that I'm doing wrong? And so how that gets received, I think, is going to be a really interesting question. 

[00:19:18] Kate Mulligan: It's interesting that you said it with not too much human intervention, because there's part of me as a faculty member who's saying, okay. So, if I write a question about asthma on a test, not only do I have to write the question and the specific learning objective and all that sort of stuff, but I also have to link appropriate No?

You're shaking your head no. AI is going to do it all for me? 

[00:19:40] Michael Campion: Yeah. Okay. That, that is kind of what So, NYU is one of the schools that has been developing this nudge system and that's exactly it. So, uh, they, they have algorithms that will determine what the topic was and which resources should be provided to the student, and basically not quite real time, but on a regular basis.

And they're also looking at this taking actual electronic health record information. So that same student, when they, you know, have moved on from the foundations phase into the clinical phases, maybe they're seeing on their pediatrics clerkship a child with asthma. And that gets logged in the electronic health record.

That data gets kind of pulled in, and then resources could be provided about pediatric asthma. That that could be provided to that student, say, the next day. Say, I see that you saw a patient yesterday in your clerkship with this condition. Here's an up to date article that you might want to check out, so that you're kind of even more prepared for that next time.

[00:20:42] Kate Mulligan: Okay, I think we're going to touch on this a bit more later, but I can see some students absolutely loving that, some students not really at the moment. 

[00:20:50] Michael Campion: But a lot of that is the cultural question, right? So, when we have a very performance oriented culture, I think a typical reaction would be, you're just telling me that I'm doing things wrong. You're monitoring me all the time. If we potentially had more of a, uh, adaptive expertise type of culture where people are expecting to not be excellent all the time, that there are going to be areas where they're going to be learning. Maybe that would, there would be more openness to that.

[00:21:20] Kate Mulligan: So those are amazing examples. Maybe we should think about what you think are the main benefits of precision medical education. This is more probably a summary of what you've already said, but. 

[00:21:34] Michael Campion: Yeah, maybe to some extent. So we, we have talked about kind of that personalization and having high relevance to these interventions, based on what we already know about the student.

And so I think that that is really, both of those things are a plus, kind of that personalization and the relevance. Organizationally, I think, Tying this into a conversation about CBME, I think is really useful. Again, that's competency based medical education. Since this is a direction that the school is moving in, at least in the clinical phases, thinking ahead to what precision medical education could look like in the context of CBME could be really useful.

And then, you know, as you had said, the idea of giving educators The information and the tools that they would need for more targeted interventions and more knowledge about, uh, students entering difficulty before they get into difficulty and being able to kind of redirect them before any sort of bad outcome happens, could be really, really valuable.

 For transparency sake, for the learners to see a lot of that for themselves, so that they can kind of build their own learning goals and their own learning plans and see how well they're doing towards those goals. 

[00:22:47] Kate Mulligan: That seems really attractive to me. It's kind of this idea that not just having pass or fail on your record is useless. Right. But if you had this thing and you could actually go back and say, Hey, look, I actually didn't understand that then, but now I totally am comfortable with it. I think that's, that's great. Reinforcement of the fact that there's progress. Yep. Could do a lot for mental health for everybody. 

[00:23:08] Michael Campion: Absolutely, and also to think about it from again the competencies. It's not just the medical knowledge. It's how did you develop your communication skills? How did you develop your skills around systems based practice? And other areas that really like everybody is coming in at a different level in each of those different areas And the goal is to get everybody to a consistent level by the end.

[00:23:28] Kate Mulligan: Okay, so Let's say we had enormous amounts of money and more numbers of talented people, what, what else would be needed to try and implement something like a precision medical education at UW, would you say? 

[00:23:45] Michael Campion: I think that the number one thing is just a ton of data. So, things that we are currently doing that where we're not necessarily emphasizing the data element of it. Maybe with some tweaks, we could pull in more of that data and find what's meaningful out of it and so both of those things require some effort. Because, it may change what systems we use to do day to day tasks that we're currently working on.

 But some of this is going to happen just naturally, you know, the move toward, competency based assessments in the clerkships means that we're going to be doing evaluations and assessments of students on a much more regular basis than we're currently doing. So that by itself is going to generate more data, but there are going to be other opportunities as well. So getting more analytics information, you know, we've actually done a pretty good job of starting to look at our, video platform analytics, mainly because we have access to the data pretty easily. But it, it gets people engaged in like, how are students actually watching the different videos that are getting produced, comparing different kinds of videos and, and trying to tweak things so that future development of videos is even more effective.

And the same thing would be true of. Um, and then we have analytics about accessing learning resources and other things that we currently don't have good access to, but if we had it, maybe we could make good use of it. 

[00:25:06] Kate Mulligan: It almost sounds like, evidence based, personalized faculty involvement. You know,, so we can see how our tools are doing with all this data and use that evidence to, you know, promote changes in directions that are helpful for the students. 

[00:25:22] Michael Campion: Absolutely, 100%. You also mentioned kind of skill sets, and I think that we do have a lot that we're building on. So not every medical school has the kind of data infrastructure that we have. There are other schools that are far ahead of us. I'll just state that as well. But we're doing pretty well. But there could be even more, especially in the area of, data science. So, we do great with kind of intaking data, managing it, developing reports, but what we, could really build capacity in is more the analytical aspect of things.

So, developing good predictive models, for example. And so, we're doing a project right now with, just starting it with the UW Tacoma Business School, where they have

And so we're going to be wanting a project for one of their teams, to really look at the data that we have and see what connections can be made between, the, primarily in the foundation space to see what can be predictors of success. So again, kind of moving in the right direction, but we really need to be able to increase that over time. Especially when we get into the area of AI tools, having expertise to assess what, methods are going to be most effective in the AI space. Right. 

[00:26:41] Kate Mulligan: Yep. Big opportunities for, faculty development there, I think. 

[00:26:45] Michael Campion: Right. But we do have a lot of expertise across the School of Medicine in these areas, so it might be a matter of leveraging some of that as well as bringing in additional expertise from outside.

[00:26:56] Kate Mulligan: So it seems like, we need to encourage a lot more interaction between a lot of different people. Is that what I'm hearing you say? 

[00:27:04] Michael Campion: Absolutely, and just this engagement from our entire community is really going to be, uh, an important step. We need to have educators, we need to have students, we need to have staff in different roles, all be part of this conversation of what we're doing.

What does good look like in this area of precision medical education? And how do we get the right, that right information to the right people at the right time? Uh, and these questions of, from a student perspective especially, how do we do that without adding stress to their already stressful lives? How do we try not to come across as big brother when it comes to seeing all of the data that we have about them?

 So, having that student engagement is going to be really important as well as all these other, kind of corners of our community. But again, this is kind of a cultural change question. It's really moving away from norm referenced assessments, where people are being compared to each other, and more towards criterion based assessments, where it's really more did somebody achieve something.

 Regardless of how many other people already achieved that, uh, and not drawing those comparisons. But ultimately, students are vying for these residency spots. It's a competitive world from their perspective. And so, how do they set themselves up and kind of have that growth mindset at the same time that they are recognizing that ultimately, They need to put their best foot forward in their residency application.

So that's kind of a larger cultural question that is not directly related to precision medical education, but precision medical education, in my opinion, can't really be successful unless we also address that question. 

[00:28:42] Kate Mulligan: Right. Right. Thank you okay. So, that's all the good things. What do you think are the major drawbacks or pitfalls for precision medical education? 

[00:28:53] Michael Campion: Yeah. So, this may be a list of things that I worry about rather than downsides to precision medical education. The things that keep you up at night.

Yes, okay. Yeah, exactly. So, I worry a little bit that we're going to see this as a technical problem. That this is going to be seen as like, let's just buy the right system to implement and it will solve all of our problems. Uh, because A, that never works. But it especially doesn't work in a situation like this where there are not mature products out there to just choose from.

If we're going to do this anytime soon, and we're, we're talking years, we're not talking months, but if we're really going to engage in this, this needs to be something that is kind of an institutional priority, because it's going to take a lot of effort from a lot of different people to do it right, and so I, I wouldn't want this to be seen as only a technical challenge, even though there's a lot of technology and data that goes into it. I also, worry a little bit about, the possibility that when we start looking at all of the different data that we have available about our students, that our students take on, kind of the role of a collection of data points rather than individuals, and so we really need to make sure that people are seen as people and not just a technology profiler. So that, that's another concern that I have. 

[00:30:11] Kate Mulligan: Seems like we should just pause there and let that sink in. Didn't you, didn't you share that quote with me about with great data comes great responsibility?

I love that quote. But thank you for, thank you for emphasizing that. And so if I'm just up until now, what I think I heard you say was, You know, it's not going to be a one and done thing, and it's not going to be a, Oh, check the box, we've got the, we've got the infrastructure. It's really going to be the thing that we stumble on a lot of the time, which is the change in hearts and minds and the whole cultural piece.

[00:30:42] Michael Campion: Right, and it's going to have to be developed on different tracks concurrently, right? You can't, it's not sequential, because you need to develop them at the same time. And so, happy everybody being part of that conversation on those different levels is going to be an important part of this.

I'll say. Yeah, it's a challenge. Is there any other pitfalls that you want to bring up? 

Well, so we've touched on this a little bit already, but this idea of students feeling like they're constantly being monitored, is another concern that I have. And so, uh, the more that we can have those conversations and get them involved in that early on, uh, the better because if we don't, it's just going to be exhausting for them to feel like they're, they need to perform every minute of every day and so if that happens, there's going to be this kind of mass checkout phenomenon, that we really want to try to prevent. 

[00:31:41] Kate Mulligan: Yes, and maybe there's even a role for admissions to make sure that we admit students who are really totally involved in a growth mindset and ready to take that on. I mean, it feels to me like there's this balance between a real, true, absolute commitment to lifelong learning from, you know, from the moment you're born, say, as a medical student and that's in balance with this constant scrutiny or this, you know, commitment. Lifelong surveillance. Part of it would be not a very nice way of putting it, but a lifelong feedback mechanism, that would benefit your improvement.

[00:32:15] Michael Campion: So I guess another thing that we also need to think about is that if we really take this to kind of a logical conclusion. then the whole question of what is a cohort of students gets called into question. If people are going to be doing things at different paces and maybe somebody who's really, you know, had a biochemistry undergraduate degree doesn't have to do all the biochemistry curriculum that we currently deliver, but somebody who's done a lot with systems based practice, you know, through some other experience before medical school maybe does less of that and has to focus more on the biochemistry.

Like, are they actually doing the same things? Do they have a shared experience? Uh, and what does it mean to be a cohort, I think is also going to be a really interesting question because so much of, of knowledge is created socially. It's in, in community with other people that you really kind of develop and, and construct your own knowledge.

And so if everybody's doing their own thing, is there a negative impact on that? 

[00:33:17] Kate Mulligan: Yeah, but the optimist in us would say, you've got all of this data, can we do some social engineering to put together the cohort so that the biochemistry major can work with the anatomy major to help each other, not just travel on parallel paths with here's a pizza party for somebody's birthday sort of interaction.

And I think that teaching someone something is the A very strong way of learning things sometimes. 

[00:33:41] Michael Campion: Right, so there just needs to be that kind of expectation coming in and willingness to engage in that. Uh, so that people see that as part of kind of their own growth. Uh, and maybe that could be even something that then gets assessed and then we have more data on how they're helping other people develop.

Don't you ever feel like you're just drowning in data? Not yet. Glad. But I hope to someday. Well, be careful what you wish for. Right. 

[00:34:08] Kate Mulligan: Would you have any tips on how, say, Our listeners, let's say it's faculty, staff, maybe administrators, should think about preparing ourselves or themselves to be ready for precision medical education.

[00:34:23] Michael Campion: Well, I think the first thing that I would say about that is probably engaging in this competency based medical education approach that is being introduced in the clinical phases right now and maybe down the road in foundations, um, but, so we should be thinking more. Kind of in a dedicated way about what does CBME look like in foundations?

But I think anybody who is teaching students would benefit from just making sure that you kind of understand how what you're currently doing fits into this competency based approach and and what does it mean for learners if they're being assessed on competencies in addition to what we're currently doing. And then, I think we need to just kind of continue to refine all of the tools that we have in place right now, and, things like the proactive advising application that I mentioned earlier, or some of the other kind of more pilot types of projects that we're working on. We need to continue to experiment, and we need to share what the results of that are so that we can decide what's valuable and what we want to carry forward.

All right. And building this data science capacity, I think, is going to be huge, whether it's with existing people and developing those skills or bringing in additional people from outside. So one last thought that I'll just kind of leave you with for how we might, try to be prepared is to think about where this might go for the transition to residency. So, students are very focused on their residency applications. In an ideal world down the road, they would have this kind of very broad portfolio of data points about their progression as a medical student towards these competencies.

The residency program that they go to are going to be very interested in that development and that trajectory. And where it's going to go from there. So, uh, one school has been reporting on an effort that they've had in one of their residency programs to basically take what students can bring them now, which is a much more limited data set than what we're talking about having in the future.

But, coming up with a learning plan and development goals for that resident once, once they enter their intern year, uh, with their own coaches and their own residency program, monitoring things as they go through. And so when we think about that from the standpoint of, people moving from one institution to another, that could mean something that looks very different for each new resident that that program takes on. That data set could look very different from institution to institution. And it kind of raises the question of, like, could there be data standards nationally, that would help translate, one institution's set of data to another? So being able to bring that together in a way that then could be more easily imported into the residency program system for monitoring these things and used as the starting point for the development of that, uh, at that stage of their learning.

So this is not something that we're going to address anytime soon, but, uh, at that national level, these are some of the conversations that are happening and we should be part of that conversation about how to do that translation from one level of learning to the next. 

[00:37:32] Kate Mulligan: Great, thank you. And it doesn't have to stop there, right?

I mean, you could argue that we're always learning and growing, and especially in an academic environment like this, and that ability to have feedback that you can use usefully instead of just putting in the faculty review thing that says, I did this many classes yesterday, and they all gave me 3. 0. Um, having someone actually suggest that, Here's some data, on some deficiencies that you may have, or some areas that you might want to work on. Could be really inspiring. 

Absolutely. Yep. Great. Well, thank you. I like ending, ending this on the idea of precision medical education, perhaps being a cornerstone for truly impressive lifelong learning. That'd be a great goal, wouldn't it? Yeah, yeah, it would. If we can get there.

So thanks Michael for joining me and taking all this time to help, help us understand precision medical education and some of the nuances of the challenges and the pitfalls and what would be required to move in that direction. It's been really fun talking to you and I can't wait to have you back.

Thanks a lot. Thanks Michael. Thank you.

[00:38:42] Amanda Garza: Thank you for listening to this episode of CLIMEcasts. We hope you enjoyed the conversation between kate Mulligan and michael Campion on precision medical education. If you'd like to learn more about the resources mentioned in this episode, be sure to check out the show notes where we've listed everything for easy access.

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Kate Mulligan, PhD

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