Episode Transcript
Dr. Chan: What is systems biology? How does presenting at a conference make one decide to pursue becoming at doctor? What's it like to have a husband in the Air Force and trying to match his order options with medical school applications? How does learning how to learn apply to nontraditional students? Today, on Talking Admissions and Med Student Life I interview Kristen, a second-year medical student here at the University of Utah School of Medicine.
Announcer: Helping you prepare for one of most rewarding careers in the world, this is Talking Admissions and Med Student Life with your host, the Dean of Admissions at the University of Utah School of Medicine, Dr. Benjamin Chan.
Dr. Chan: Well, welcome to another edition of Talking Admissions and Med Student Life. I've got a great guest today, first-year, Kristen. How are you doing?
Kristen: I am doing great, thank you.
Dr. Chan: Fantastic. All right. Let's start in the beginning. Where along your path did you decide to go to medical school?
Kristen: Well, I was one of those kids that I think always wanted to be doctor. Growing up, I loved superhero movies and a lot of superhero origin stories involve science and medicine, so I really liked that. But I kind of fell in love with engineering when I was in my undergrad and I didn't always love memorization so I decided I wanted to pursue engineering. I was actually planning on doing my Ph.D. in biomedical engineering.
Dr. Chan: And this is back in Ohio, right?
Kristen: Yeah, yeah.
Dr. Chan: Case Western.
Kristen: Case Western, yep, doing systems biology, which is a really cool program, which is kind of interdisciplinary between biology and computer science and math. I decided I just wanted to go kind of more the engineering route. I kind of fell into this opportunity, though, that I couldn't pass up, which was taking a job at Microsoft as a technical program manager, which I really loved. So that was a great opportunity.
Dr. Chan: So, I remember in my undergrad days that they would have these job fairs. Did Microsoft have a booth? How did you get into Microsoft? Correct me if I'm wrong, but I don't think they have a big presence in Ohio?
Kristen: No, no office is in Cleveland. No, Cleveland's great. Microsoft wants to go to Cleveland. No, I had already gotten into the Ph.D. program that I really liked and Microsoft, though, they had a booth at the career fair and they had water bottles. I really wanted a water bottle so I wound up giving a rÈsumÈ and did an interview. If you do well in the interview they actually send you out to Seattle. I'd never been to Seattle so I was like, "Oh, free trip to Seattle." Then that kind of turned into a job that I really, really loved, so I got really . . . it sounds weird to say "lucky," but I got really lucky. It was a great opportunity for me at the time and moved out to Seattle. It just gave me the opportunity to kind of live as an adult.
Dr. Chan: Is the Microsoft campus kind of like . . . I have this image in my mind where there's free smoothie bars and there's these little pods you sleep in, anything you want they just do because you've really got to focus. Is that an accurate description? Masseuses everywhere.
Kristen: I did not see any masseuses when I was there. They did have a 100 flavors of pop machine. That was really great.
Dr. Chan: Wow.
Kristen: Yeah. Coffee and just they had beverages and stuff. They did have great parties. Whenever we'd launch a product they would have amazing launch parties. It's just one of those places where also the people that you work with are really great, so there's just this exciting atmosphere there because everyone's just really excited to be there and do great things.
Dr. Chan: Seattle's a cool city.
Kristen: Oh, Seattle's amazing, yeah.
Dr. Chan: So you're working at Microsoft and then were you also still going to school through your Ph.D. or how did that work out?
Kristen: No, I actually declined the Ph.D. program after I got the offer at Microsoft. I was continuing to work on my master's thesis. That's kind of a long story as well, but I kind of started with a B.S./M.S. program, doing my master's in systems and control engineering. I tried to work on that part-time while working. Actually, for anyone listening out there, that's not a great plan. If you're going to do something, just do it. It'll be much faster and cheaper to just get it done.
Dr. Chan: Very true. Very true. All right. So you're working at Microsoft, cutting edge of technology. You probably had really great . . . I bet your Excel spreadsheet skills and your Microsoft Word skills and Outlook skills are just amazing. So you're kind of plugging along and then what was the next kind of pivot point or decision point?
Kristen: Yeah. Well, I had been dating this fantastic guy for some time. We were engaged and I decided that the commute between Seattle and Texas, where he lived, was getting a bit too long for me. My now husband is a pilot in the Air Force, so he was stationed down in Texas and I decided to try to find something that was a little bit more flexible that would allow me to do the things that I really enjoyed doing, so do something that was really intellectually stimulating and challenging and, I guess, fulfilling in a career kind of sense. So I found a position in big data development to do consulting and move down to Wichita Falls, Texas, which is the next stop on that journey.
Dr. Chan: So how long were you in Seattle for?
Kristen: I think about a year and a half to two years, somewhere in there.
Dr. Chan: And then did you meet your future husband back in Ohio?
Kristen: Yeah, we actually interned together back at NASA Glenn Research Center in Cleveland, Ohio. He's from Cleveland too.
Dr. Chen: Fantastic. Go Cavs, right?
Kristen: Oh, love the Cavs.
Dr. Chen: All right. So he's Air Force, he's flying jets and all sorts of planes, so he's down in Texas. So you were in Seattle for how long?
Kristen: A year and a half to two years, somewhere in there.
Dr. Chen: Then you make the jump. Help people understand, where's Wichita Falls, Texas?
Kristen: So I like to say sometimes it's . . . there's not a lot around Wichita Falls. I would say it's about halfway between Oklahoma City and Dallas.
Dr. Chen: Prairies. Ranches.
Kristen: Prairies and ranches. Really, really good steaks. If you like steak, go to Wichita Falls. You will get the best steak of your life. It's great.
Dr. Chen: So you set up shop in Wichita Falls and you do big data consulting. So for those people that don't know, what's big data? What does that mean?
Kristen: Basically any time you interact with a retailer or something that has an online presence, pretty much anything you can think of will have a digital touch point. So if you make a phone call, if you send a text message, if you're at the supermarket and you give them your phone number so you can use your reward points, those are all touch points. Those are all being collected by companies.
Companies have all this information but they're not always sure quite what to do with it because they have different goals. Maybe they want to retain customers or maybe they want to sell you more stuff. Or sometimes maybe they just want to make a better experience. Maybe they have a website and they want to see, hey, how can people use this website better so that they're not banging their head against a wall trying to buy something on our site.
They would hire people like me to come in and say, "Hey, you can use these mathematical methods to kind of figure out where are people getting stuck. How can we improve your process? How can we understand the results of this clinical trial?&" or kind of things like that? It's really broad but it was a great experience because you get to use these kind of cutting edge mathematical methods on problems that are super interdisciplinary.
For example, I did some work at a financial company understanding personal networks and then you can use that same kind of network theory in a hospital system to understand how people move between providers. So it's really interesting to kind of take techniques from one field and move it to another field where it can be applied. But basically big data is just big, big, big data that you have to kind of use sophisticated techniques to understand and you have to be able to use technologies that can scale to actually process all of that data.
Dr. Chan: So it sounds like it could be something as mundane -- because I've read a little bit about this -- as that when you go into . . . I'm just going to pick on Amazon. You go into Amazon, there's a reason why the buttons are where they are, because it is shown that people are more likely to click on the button if it's at that point on the screen. Right?
Kristen: Oh yeah.
Dr. Chan: Or it can be more higher up, like how do we drive traffic here? Kind of like you said. Am I kind of conceptualizing that?
Kristen: Yeah, exactly. Actually, one example that I can't talk about, most of my stuff is NDA so I can't go into too much detail.
Dr. Chan: Nondisclosure.
Kristen: Nondisclosure. Sorry. Nondisclosure agreement.
Dr. Chan: I love it. I feel like I'm in the know. I love this stuff. Okay.
Kristen: But one I can't talk about I presented at a conference, and they wanted to know how they could reduce the time to go see a provider. So they had people coming in and they just wanted to give patients a better experience and figure out where are the bottlenecks here? If I'm coming into the system and I need to go see a specialist, what was taking so long to go see a specialist, how can we reduce those wait times, are there particular areas where people are getting stuck. So we use this type of graph model. So a graph is basically . . . Sorry, I didn't realize how much I relied on drawing stuff. Usually I normally draw stuff at this point.
Dr. Chan: All our listeners have really active imaginations. You're doing a good job.
Kristen: You can think about each appointment as being a point on a map. I'm starting out with my general practitioner. My general practitioner is going to refer me to get an X-ray and that person, from there, they're also going to refer me to go see an orthopedic surgeon and from there I'm going to go and I'm going to have this path where I might pick up pharmaceuticals. There are even various stops on this journey, each particular event. If I fall and I break my leg, that's going to start one particular path along this map. If I fall and break my arm, I'm very unlucky but I'm going to start on a different place in that map and I'm going to kind of navigate that system.
You can kind of superimpose all of those paths to find patterns. So what are the places with the highest traffic? You might imagine general practice to the pharmacy might be a very common path or general practice to getting X-rays, that might be a very common path as well. So we kind of want to understand how people are moving through the system and also how that varied for different age groups and for different regions, so just taking different slices of the population and saying, "How are people using these services? How are they moving through and what's the interplay between that and what their wait times are?"
People might get stuck in certain points and maybe bottlenecked. So if your general practitioner's only referring to one particular orthopedic surgeon, that person's going to be way too busy, so you might want to have more orthopedic surgeons in that particular area, that sort of thing. That's kind of how we . . .
Dr. Chan: So it's almost like tracking the data then. Here's a great question I've thought about. As you've interacted with different companies, different entities, organizations, you have all this data. Would you get sometimes people just pushing back, like they just didn't believe the date? Like, you do all this analysis and then they just don't believe it.
Kristen: I would say sometimes people can be surprised by things. What's kind of hard is you don't want to go in with too many assumptions about what you're going to get out of it. I don't think I've ever had anyone say like, "No, there's no way that can be true." But I think a healthy degree of skepticism is always a good thing because it forces you to kind of evaluate and say like, "Am I really doing this the right way? Is everything right? Is my code right?" Sometimes you make a mistake, and then if something is wrong, you look back and you're like, "Oh, actually, I definitely should have added here when I subtracted," or something like that.
Dr. Chan:I think I see powerful corollaries in medicine. I think sometimes doctors and patients are confronted with pretty strong evidence that either a treatment works or a medication works, but because of emotion or anecdotal past history they kind of push back against it. I don't know if you ever thought about it like that.
Kristen: Yeah. Actually, that's something that I really . . . I'm actually really glad you brought that up because we have an evidence-based medicine kind of section in our curriculum and what I've kind of been thinking about a lot is choosing the right numbers to describe a situation. So something that's really important is averages.
Everyone's like, "Oh, what's my average chance of surviving this?" Averages are not actually a great . . . at least I've found that averages aren't great for actually giving you information because, you know, we talked about people making appointments, some people are going to be really on it. They're going to make their appointments right away. Then some people might just forget. They might put it on their calendar and maybe they feel better, they don't want to make that appointment again, so your average time might be somewhere in the middle when, really, you have this bimodal distribution.
You have a peak of these people who are really overachievers. You have these people who kind of fall off the end. But the average doesn't really tell you that much. It's all really more about distributions. Even there, probabilities don't always help your understanding.
It's hard because when people do take numbers really personally, it only helps if you're in that number, right? If only 0.001% of the population gets hit by a bus, you're pretty safe. But if you're that person that's hit by a bus, that was not a very helpful number for you.
Dr. Chan: Yes. It makes it real.
Kristen: Yeah. I think that's just the hard thing is it's a lot of large numbers. Especially in medicine you see these weird conditions come up that we learn about. Not these weird conditions, I guess that's not very nice. You hear about these really unusual conditions and you're like, "Wow, that's really, really unlucky." But there are a lot of people in the world, which means that there will be some unlucky people. I think that's just the hard thing about probabilities is that you try to use these as guidelines, how should I make my decisions. But without knowing what population you're in, which you have no way of knowing, it's tough.
Dr. Chan: Yeah, I agree with you. I don't think doctors are really that great at math. I don't know if you've seen that already with evidence-based medicine, but with your background you should be, like . . . it should come a little bit easier to you than others. That's what I'm saying.
Kristen: It's kind of a different perspective, though, which is interesting. Kind of the way that you look at problems from an evidence-based medicine perspective versus from a data science perspective, it's really, I think, kind of the opposite. For a lot of data science you use really new methods. You might use text mining or you might use graph analysis. Evidence-based medicine is a lot more like we're looking at P values and we're looking at odds ratios, which actually I don't love odds ratios but odds ratios are everywhere in medicine. I think that's been kind of challenging in some ways because I was really ready to kind of bring my perspective in but I kind of have to learn what is accepted here.
Dr. Chan: A different language almost.
Kristen: Yeah, exactly.
Dr. Chan: Was all of your consulting with healthcare kind of entities or not really?
Kristen: I did some stuff with healthcare. I did work with LLT Finance, transportation, insurance. I did, actually, a bit with insurance, and then, yeah, some with healthcare, some with pharmaceuticals.
Dr. Chan: And would that kind of, "Oh, yeah, I need to go to medical school"? Walk me through that. What was going on?
Kristen: Yeah. I actually had one particular moment that it was really clear that . . . I really started to think about it seriously. It's hard, changing careers and saying, "I have this thing and it's going really well and it's solid."
Dr. Chan: Yeah, you're good, you're moving up the ladder, you're flying around the world, doing all this cool stuff, you're just immersed in data.
Kristen: Exactly. It actually was for a pharmaceutical company. I was working for them and I was presenting, I think it was some sort of information on a clinical trial and I was presenting these numbers. I must have been pretty blasÈ about it, which I kind of regret now. This clinician who was sitting in and watching these results, she just interrupted me and she's like, "You're presenting these but you don't know what these numbers mean because you don't have to sit across from someone and explain these numbers to them. You don't have to take ownership of their care based on these numbers."
I thought about that and I was like, "I was a pre-med." That was kind of my first instinct. "I was a pre-med. I understand health stuff." Then I thought about it for a second longer and I was like, "I have no idea. I have absolutely no idea." She was completely right. For me, it was numbers. It was all just these are numbers that are in this table that's sitting in some data center somewhere.
I don't know, maybe that person was a marathon runner or has kids. They weren't people to me and that was kind of like a weird, sad realization. I had a conversation with my husband when we were traveling and I just kind of brought it up. I'm like, "This has been really great. I've been really fortunate in my career and I've had really great people I've worked with, really amazing experiences, but I kind of feel like I want to do more. I want to know what those numbers mean. I want to have that impact on people." That's when I started looking into medical schools and applying.
Dr. Chan: So you were looking for more meaning, in a way, behind the numbers.
Kristen: Yeah, and I just wanted to be able to do more good too because if you're good at numbers, you're good at numbers, but you don't always know the right questions to ask. I feel like that's sometimes a disconnect. A lot of people in medicine have great questions but it's hard to answer the questions without the mathematical skill set necessary. But I have the mathematical skill set but I didn't know what the right questions were. So I kind of wanted to bridge that gap and I thought I might be able to do that. So that's kind of one of my goals. We'll see how it goes.
Dr. Chan: Yeah, that's cool. I really hope we get you there. So you told your husband you were thinking about med school. I assume supportive?
Kristen: Yeah. Oh my gosh, he's amazing. My husband is absolutely amazing and I'll be honest, I don't know if I would have done it if he wouldn't have been so supportive because military, I mean, we've moved around a lot. Even when I was applying to schools I kind of kept it on the down low, if you will, when I was applying because every time I'd bring it up people were like, "Oh, what's going to happen if you don't get into med school where he is?" I was like, "Well, I guess we'll just see if that happens."
But he was really great because it's a decision you have to make . . . if you're married, you have to make that decision as a couple. Like, "Hey, I have this job and I'm going to not be having income for awhile," or, "I'm going to have a really busy schedule for a while. It's going to put a little bit more on you for some time." Yeah, I just feel really fortunate there.
Dr. Chan: So very supportive. Was your work supportive or did you kind of tell them at the very end?
Kristen: My management and my whole team, really great. I can't overstate how lucky I was to have those particular people.
Dr. Chan: "Come back and work for us after you've got your M.D."
Kristen: Well, they were really amazing. They actually let me do a short educational leave, so I was able to do some of my post-bacc because I didn't do my prerequisites or I didn't have all the prerequisites.
Dr. Chan: I remember that. Wichita Falls Community College or something, right?
Kristen: I had, let's see, Midwestern State, I had Kansas State. I have Estrella Mountain down in Arizona.
Dr. Chan: Yeah, I remember when your transfers came in, like, "Oh, this is an impressive array of places you take your classes."
Kristen: Yeah. Well, every time we moved I had to find . . . there was one I did online. You just do them when you can. My management was really supportive. I was able to take time and do some shadowing and study for the MCAT. I think the hardest thing there was just being a nontraditional student, trying to figure out where to start. If you're kind of doing the traditional path from undergrad, you have resources that are available for you.
I reached out and the pre-med advisors at both Case and Midwestern State were great. But it's kind of hard when you don't have longitudinal support. The Case meetings I had to do remotely and then at Midwestern I just wasn't there for very long. What was good was I was able to say, "Here's my transcript. If you could just take a look and let me know what my chances are, kind of what I need to aim for with my MCAT, or where I'm missing things in my application." So I was kind of able to get a high level road map of where I needed to go.
I would say the rest of my information I got through online sources. I kind of lived on the Premedit, they call it.
Dr. Chan: I know that very well, yes. I dabble there every once in a while.
Kristen: They have a lot of good information there about how to navigate MMIs and applications and essays and things like that.
Dr. Chan: Do you feel there was kind of a corner just for nontraditional students in a way or it was just more vague, more general than that?
Kristen: Yeah, I would say it was pretty general. I did try to look . . . I was nervous because it's hard kind of being . . . you feel like, oh, you're way older than everyone. I was out for five years. You're just coming from a different place. I was actually trying to figure out, oh, are there schools that are more nontraditional friendly? Which was one of the challenges I had with figuring out where to apply.
Dr. Chan: Okay, so let's break this down.
Kristen: I'm sorry. There are a lot of pieces.
Dr. Chan: I know, it's beautiful. It's life. It's complex. It's like the data. Everyone thinks I retain everything but my brain doesn't retain everything. Did your husband kind of go through the Air Force to kind of figure out where he was going to be for some stability or did you kind of take the lead on that? I know that was kind of the decision, I got the sense.
Kristen: It was actually kind of crazy how it worked out. I was actually planning on applying a year later because I was like, "I don't have a lot of shadowing hours." I kind of thought I needed a bit more clinical experience but I decided to apply a little early. But the crazy thing about the timing is that my husband was figuring out what plane he was going to be flying. He was an instructor pilot flying T-6s and from there he had a plane that he was going to get as his main . . . I'm completely blanking out on the word for this plane.
Dr. Chan: His baby.
Kristen: Yeah. His main big plane that's very powerful.
Dr. Chan: Yes, the very fast one. But he wasn't sure because there are a few different options for what he could get and each of those options had several locations so we had a list of here are the 20 different places that he could go. Then for me the next step was, okay, let me see what medical schools are around those areas. So I kind of applied. Hill and Utah, that's a big one so I applied here, some places in Arizona. I think I applied in the Carolinas. I have family in Ohio so I applied in Ohio. I was also a resident of Texas so I applied to Texas and there are a lot of Air Force bases in Texas as well. I think I applied to 25 schools kind of all over the place.
The great thing is I actually . . . I really liked the schools that I applied to so there are a lot of great programs out there. Then kind of as we went through, as time passed, we kind of had an idea . . . I think in the summer we found out, okay, he's going to be flying the F-35. Then from there they're like, the few locations. I think we had some kind of general idea but we weren't quite sure where he was going to go.
Dr. Chan: Again, it's very different. I realize all the military branches are different but did he have a lot of voice in this? I know at the end of the day they just kind of tell you, "You will go here and you will do this." But I assume he got to have some voice in it.
Kristen: It's kind of like a ranking thing. Actually, it's a lot like the match. He has his packet or whatever he put in and I think he had to rank the planes he wanted or rank the location, something like that. Anthony, if you're listening, I'm sorry that I don't . . .
Dr. Chan: She's been paying attention all the time.
Kristen: It was a very stressful time. Yeah, then from there he had to put his options and then -- I forgot about this -- he actually had to go through another program to figure out if he was going to be flying the F-16 or the F-35 and that was in November, December, somewhere around there. So there was just a lot of decision points for him as to where he could go. So for me it was just filling out secondaries and trying to go through the process. Actually, my mother passed away during secondaries and that was really tough as well. I was far away from everyone and my husband was actually away doing training at the time so I was going back to Ohio, filling out applications, trying to figure out where life was going, so it was crazy times.
I think I've heard someone else say this on one of your podcasts before, which is that the time's going to pass no matter what happens. When things happen that are really hard things in your life, you just want to make sure your life's already kind of going in the direction that you want because it'll . . . you know, that's how the time is passing.
Sorry. I thought this would be more eloquent but now that I'm saying it . . .
Dr. Chan: No, it's beautiful, beautiful. It sounds really stressful. A lot of stuff's going on.
Kristen: Yeah.
Dr. Chan: So I get the sense that your husband found out Hill Air Force Base was his destination.
Kristen: Yeah, and I forgot exactly when that was. I think it was actually . . . I think it was in 2017 is he got the final thing. But what was hard was there was a point then where . . . so I'm nontraditional but I was out of state applying to Utah and the stats are kind of sobering.
Dr. Chan: Yeah, we have a lot of people apply from out of state.
Kristen: Yeah, yeah. The numbers are . . .
Dr. Chan: Against the math.
Kristen: Yeah. You want the odds to be in your favor but I actually . . . I didn't hear back from Utah for awhile so I was kind of looking at my other options and kind of figuring out . . . I think there was really one other school that I really, really was feeling strongly for so it was kind of a hard decision in the end but I was also really glad to hear from Utah. I don't know. I still can't believe we pulled it off. My husband's here, I'm here.
Dr. Chan: He's flying around the country doing stuff.
Kristen: Yeah.
Dr. Chan: All right. With being a nontraditional student, how did your first year go? I mean, how would you describe it? We kind of talked before I turned on the podcast but you said something that I thought was fascinating. You're learning how to learn. You said something like that.
Kristen: Yeah, yeah, learning how to learn. In engineering you really don't have to memorize very much because it's mostly about problem solving. So you learn different ways to solve these problems and you can kind of apply these to different things. But in medical school it's a lot of memorization.
In anatomy, if you forget what a structure is, you cannot logic out what that structure is. You can logic out maybe what it does, like, okay, it's connected to this and therefore it does this and if it's injured then this will happen. You can use that kind of process-based logic. But some of these things have really bizarre names. You are not going to guess those names. You're not going to logic your way out of it.
Dr. Chan: A lot of historical, a lot of people in Greece and Rome, other things.
Kristen: Yeah. So I think it was more just trying to learn how to memorize, learn kind of memory tricks, and actually just get back into the study habits. I was just working for a long time and I worked jobs that could be very demanding but it's different having a job and having projects that you're working on with set deadlines and then you have to do a little bit more self-starting, I think, in medical school. No one is going to make sure that you're doing your tasks except for you. So as far as accountability goes, you kind of have to be your own accountability.
For me, that involved really setting deadlines for, "Okay, I'm going to watch these recordings. I'm going to watch these external resources. I'm going to kind of bring these things together." I would say I'm still learning how to do that. I think it's still a challenge for me sometimes because it is just so different and there are some things that you can apply. I would say a lot of medicine, at least in the beginning, it seems like it's first principles.
In engineering and physics you try to boil everything down to first principles, so is this true with the laws of nature as we know them, and then from there use that to solve your problem. In medicine the base knowledge that you have to have is just so much wider, so much broader, there's just a lot of memorization that you could do before you start getting into the deep problem-solving.
Dr. Chan: Excellent. Going back to being nontraditional, have you found the other students . . . I would argue . . . at least my perspective is that our medical school has more nontraditional students than others because people tend to be a little bit older, they've switched careers, they've had families. Does that match with your experience?
Kristen: Yeah, definitely. I actually think Utah has turned out to be really great for me from the nontraditional route too because I was worried about that. I'm coming in at least five years out of school and married and there are different stages of life, I think, and I was a little bit worried. I guess you prioritize different things in some ways if you've been out in the world for a little while. I settled down a bit, I think, a few years out of school.
I think a lot of people here, like you said, have taken time off, have taken time with their families. I think Utah in general is more family-oriented than a lot of places as well. Yeah, so I'm kind of trying to figure out where I want to go.
Dr. Chan: I assume a lot of your peers, your friends you've made have also kind of been married and are a little bit further out from school as well?
Kristen: Yeah, yeah, definitely. I think it's actually really great because a lot of people are . . . they have really great stories. I think that's something I've really enjoyed hearing.
Dr. Chan: Well, this story's pretty great. I love your story.
Kristen: Thanks. Well, it's kind of incredible, though. We have people who have been really competitive athletes and musicians and people have traveled all over the place. I think almost everyone in our class speaks at least two languages. It's really, really incredible. I remember during the transition to medical school, kind of like the orientation program, there was a point where it was like, "Okay, raise your hand if you've been to at least 10 countries," or something and a bunch of people raised their hand and you're like, "Wow, this is kind of amazing."
Dr. Chan: Cool. Well, Kristen, I appreciate you coming on the pod. I guess the last question is what advice would you give someone? Someone's listening right now and they're in a job that they like but they've always kind of had that little feeling in the back of their head like, "Oh, I want to go to medical school," what advice would you give that person?
Kristen: I would say do some introspection. Really think about what it is that you want to do and where you want to go, and then just make sure that your decisions are in alignment with where you want to go. You never know how much time you have or when something might happen that might completely wreck your perspective, so just make sure when those things happen that your life is going in a direction that you feel comfortable with.
As long as you, at any given time, are comfortable with where you're going, where you are and what your motivations are for doing those things, I think you will be happy, whether that's staying at your job, whether that's kind of embarking on a new journey. I think there are a lot of great options out there, so just be comfortable with what you want and try to just understand where you want to go.
Dr. Chan: Fantastic. And last question -- I'm not going to hold you to this -- what kind of doctor do you want to be?
Kristen: Oh, I don't know. I don't know. I'm kind of like a dog from Up the Squirrel.
Dr. Chan: So a cardiologist comes in and talks to you, you think cardiology. The next day, pathologist, you switch.
Kristen: I'm all over the place. When I first came in, I was like surgery, because I had chatted a lot in surgery and I shadowed a lot of plastics procedures, and I just thought, "Wow, this is like a puzzle. It's like a body puzzle, which is very cool." Kind of got that spatial reasoning part of my brain really excited. I was like, "Oh, this will be really cool." But then hematology was really interesting as well and nephrology has some really cool kind of mathematical things you have to understand. Gosh, there are just a lot of great options. I don't know. You'll have to see, you'll have to see. I think it'll probably be some kind of surgical area but time will tell.
Dr. Chan: Time will tell. Cool. Well, thanks, Kristen, I appreciate you coming on.
Kristen: Thank you.
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