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Welcome to the Clinician Researcher podcast, where academic clinicians learn the skills

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to build their own research program, whether or not they have a mentor.

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As clinicians, we spend a decade or more as trainees learning to take care of patients.

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When we finally start our careers, we want to build research programs, but then we find

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that our years of clinical training did not adequately prepare us to lead our research

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program.

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Through no fault of our own, we struggle to find mentors, and when we can't, we quit.

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However, clinicians hold the keys to the greatest research breakthroughs.

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For this reason, the Clinician Researcher podcast exists to give academic clinicians

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the tools to build their own research program, whether or not they have a mentor.

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Now introducing your host, Toyosi Onwuemene.

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All right, everybody.

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Welcome to the Clinician Researcher podcast.

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I'm your host, Toyosi Onwuemene, and it is such a pleasure to be here today.

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I have an amazing guest with us today, and I'm going to take a minute to allow him to

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introduce himself.

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Dai Wai, thank you so much for being on the show.

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Welcome.

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Well, thank you.

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So my name is Dai Wai Olson.

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I'm a nurse at Dallas, Texas at UT Southwestern, and I've been involved in clinical research

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on a formal scale since 2001, but I think all of us get that first clinical research

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bug at about the age of three or four.

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Those are my favorites.

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The little super scientists who I remember watching one of my grandkids threw something

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into a pond, kind of looked and then got something else and threw it in and was doing the does

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it float, does it sink experiment.

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And I'm like, yeah, that's clinical research.

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So I think I've always been a researcher.

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I just didn't have the street cred yet.

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Oh, I love what you say.

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So what you're saying is that the curiosity that's alive in us from when we're young is

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really what prepares us to be clinician researchers later on in life.

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I think it's what drives us to be clinician researchers.

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What prepares us is learning how to ask the right question.

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I mean, we've got that.

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I think a friend of mine back in high school argued about everything and should have been

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a researcher because researchers were basically trying to find ways to win an argument.

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We're not taking no for an answer.

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Yeah.

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Yeah.

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Well, you're right.

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You thwarted me there.

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You've figured out how to make it that you rejected my null hypothesis.

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And I'm going to get more data.

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Because I still think I'm right, but now I've got to test this and build the data to eventually

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prove that, yeah, I was right all along.

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I just didn't ask the question in the right way.

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I like it.

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I like it.

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Well, tell us your story.

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How did you get here?

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Well, I got here.

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I started out college back in 1980 hoping to become a scientist.

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I was looking to become an aquacultural bioscientist.

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I wanted to grow plants using water.

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And then Ron Reagan came into power and lots of things happened.

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And I lost my scholarship and was homeless for a little bit and found that there was

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a nursing shortage.

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So I thought, ah, in two years I could get a nursing degree, make enough money to go

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back to school and become a scientist.

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And so I was in nursing school and I met my wife.

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I got married.

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I was a nurse for about seven years and a nurse named Denise Antle, who I owe my life

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to.

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I was blathering on about how I'm going to get out of nursing and do something.

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And she walked, this is in the 80s.

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You were allowed to do this.

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She walked up to me and slapped me across the face and said, what are you talking about?

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You're a nurse and you're a good nurse.

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And it was at that moment that I realized like, yeah, I love what I'm doing.

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I grew up, I didn't know men could be nurses.

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I was the only nurse in the hospital at the time who was male.

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And I'm like, yeah.

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And she mentored me and was wonderful and caring, which all nurses are.

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And I realized I had to go back to school and get the training that I needed to do the

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things I wanted to do.

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I had originally come out of high school thinking I was going to save the world by growing plants

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with water and realized that I still wanted to do my little part to sort of make a difference

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in the world.

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And so I went to nursing school and finished with that.

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I moved to North Carolina.

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I graduated from University of North Carolina with my PhD in nursing.

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Spent 20 years in North Carolina at Duke and then was recruited to Dallas where I am now.

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And I'm in the Department of Neurology and Neurosurgery and I run something called the

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Neuroscience Nursing Research Fellowship, training more people on how they can be researchers.

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Ooh, I love that.

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So now I want you, because now you coming up this not just as a clinician researcher,

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but also someone who trains people to be researchers.

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So what is needed for clinicians to make that transition from I'm a clinician, I take care

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of patients to I'm a researcher and I can move the research enterprise forward?

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I think we are not very good at letting people know they can do it.

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We put research on such a high pedestal that we almost approach it like you got to prove

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to me that you, lowly person that you are, can someday become an academic.

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And that's just crap.

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Like, anybody can do this.

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I'm not a particularly smart person.

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I just work really hard.

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And so I approach it by, let's your first study, because everybody who comes to me,

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there's two studies they have in mind.

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Study number one is I'm going to collect 400,000 variables from 270,000 patients and answer

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one question that will solve world peace.

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The other person says I'm going to do this one study with seven people that answers 248

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questions that will solve world peace.

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And instead of that, I'm like, how about let's just do one simple study you can do in about

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a year that's going to solve this little teeny tiny little question here.

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And that's going to move the ball forward.

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And they do it, and they go, you know, I did it.

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And it wasn't, it's not a jam of paper.

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But it did answer a question that we've had.

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And those people, I think, not everyone, but some of them get the bug and go, OK, now I

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want to answer a harder question and a better question and use more variables, and I want

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to get statistics.

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If you were teaching someone how to play chess, you wouldn't start out going, you know, like,

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well, first you have to learn the Queen's Gambit, right?

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You build your way into it.

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So that's sort of how I approach research is let them put a toe in the water.

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And frankly, some people decide they don't want to do it.

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And I'm OK with that.

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If after doing research, you discover you don't want to do research.

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That's a good thing.

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Find out early.

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I like it.

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So what you're talking about is the door is open for everyone.

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Everyone should have the opportunity.

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It shouldn't be a thing where you select people out to do it.

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And you start small and people achieve small wins, and then they can get bigger and bigger.

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Absolutely.

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Absolutely.

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Something we do if we really boil down to it, you know, the greatest chef in the world

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started out making a peanut butter jelly sandwich and was really proud of it, too.

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You know, my wife is now a phenomenal chef.

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She was cooking with one of our grandkids who got to stir something.

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But proudly announced, I made dinner.

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Now we could write the academic in us wants to go, you didn't make dinner.

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All you did was one of those.

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But really, you know, why not let him own it?

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There's no harm in that.

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And start start with us.

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Get this small win and and build that confidence.

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You can certainly name one person you've met in your life who doesn't have any good ideas.

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I can't think of it.

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You're right.

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Now, Tommy, Tommy, what are the major challenges you seeing for clinicians who want to transition

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to research roles?

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And maybe if you want to speak from the perspective of the clinicians themselves and from the

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perspective of the institution?

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Well, from the perspective of the clinician.

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And I don't know if you have to edit this out.

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Funding is an issue.

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The NIH is irrevocably broken.

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It is a failed institution.

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It's also the best game in town.

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And that's why we all do it.

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I've never talked to anyone behind closed doors who hasn't said, oh, yeah, the NIH is broken.

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It's all about who you know, and it's an old, you know, it's the old boys club.

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But we have to fight our way into it.

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So that's a challenge is how do how do how do we get in here?

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One way we can do that is partner with industry.

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Industry in the past 20 years has gotten a dirty like if you say, oh, I'm doing a study

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with sponsored by a drug company, people like, oh, a drug company.

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Well, if I don't help this drug company answer the question correctly, they're going to they're

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going to do harm.

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Right.

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This this device, they need some clinical expertise to identify something that's going

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to solve a problem that we that need solving.

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So we do need to partner with them.

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And that helps people get started.

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Right.

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And transitioning.

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The other thing is exactly what we talked about before.

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Go for a small win.

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Don't start out when you if you're going to get started and you want to be a clinician,

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scientist, a clinician, researcher.

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Start small.

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Get a win.

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I like it.

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OK.

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So, yes, I mean, you're talking about really diversifying your funding sources as well.

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Don't just have a one track.

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I want to go to the NIH.

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I want to go to the NIH because it's hard.

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And while you're pursuing that goal, you should be pursuing other funding opportunities as

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well, including industry.

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Yeah.

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And in the industry, there's there's an awful lot of money available for research.

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That goes unclaimed because nobody asked for it.

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There's grants and there's there's foundations and there's people trying to give away money.

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And, you know, there's there's there's philanthropists who want to give money to solve a problem,

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but no one's ever asked them.

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And if you if you start small and you're open to, well, you know, maybe this is only a thousand

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dollars.

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Maybe this is only ten thousand fifteen thousand dollars.

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What can I do?

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How can I ask a question that will move the ball forward?

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With just this much much funding.

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Not every question means 14 million dollars.

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And you can you can do a lot.

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There's important questions in the clinical environment that still need to be asked.

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Some of them don't don't take a lot of money at all.

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Yeah, I like it.

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It's like not not despising any source of funding, being open and and just being small.

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I'm starting small because sometimes we are looking for the million dollar couple of million

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dollar grant.

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But what can you do with a couple of ten thousand or or a hundred thousand?

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Yeah, right, right.

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Tommy, what are the major the insights, major insights that you gained along your journey

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that younger people who are just starting really should know?

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I think that one of the insights is is clinical research.

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We've taken we've sort of taken a backseat to binge science over the past 20, 30 decades

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that you know that we focused in on on killing mice and things like that as as science.

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And if you do clinical research, don't apologize.

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Don't like own it.

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That's where that's what your love is.

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And there's a lot of importance to that.

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And so so don't don't apologize for what you love.

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And I think that's why is own it and be proud of what you're doing.

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Two is I was taught that clinical research is dirty because of all the very.

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And and it's not dirty.

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It's filthy.

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It's more it's worse than dirty.

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But embrace it.

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Because all of that dirt, which statistically is what we call noise, right, it's error,

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it's variance, it's it's confounders, it's unexplained variables and the influence.

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Well, that's that's sometimes the best small start.

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Right.

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Is how can you reduce the noise by trying to clean up?

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There is an awful lot of dirt that needs to be cleaned up in clinical research.

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We all do almost everything different.

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And I personally think as a clinician scientist, a lot of that's important.

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Right.

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Whether or not you start.

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You you start the the IV and the left or right arm.

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Does that make a difference?

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I don't know.

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But it'd be awfully easy to easy to figure it out.

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When when we give a pint of blood.

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Look.

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Why do we do that?

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Why the volumes like to us volume is so important.

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Right.

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But is it three twenty four mils or four twenty five?

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Is there a difference between two hundred and eighty and two hundred and eighty one?

244
00:16:20,940 --> 00:16:26,540
At what point in time like these are easy questions, I think, to ask.

245
00:16:26,540 --> 00:16:33,020
But they become really, really important because the big big mega trials, right, the big mega

246
00:16:33,020 --> 00:16:36,100
trial will say.

247
00:16:36,100 --> 00:16:38,460
Infuse one liter.

248
00:16:38,460 --> 00:16:42,420
At the onset of X. OK, well.

249
00:16:42,420 --> 00:16:47,660
Most of us know that a liter of saline can have anywhere from nine hundred and fifty

250
00:16:47,660 --> 00:16:49,660
to eleven hundred mils.

251
00:16:49,660 --> 00:16:52,020
So a liter, even a liter.

252
00:16:52,020 --> 00:16:55,860
But then some scientists massages this data.

253
00:16:55,860 --> 00:16:56,860
Right.

254
00:16:56,860 --> 00:17:03,460
And comes up with this regression plot that that shows like for every one hundred mils

255
00:17:03,460 --> 00:17:06,820
X predicts Y.

256
00:17:06,820 --> 00:17:08,340
And you know, that's flawed.

257
00:17:08,340 --> 00:17:10,100
So you can.

258
00:17:10,100 --> 00:17:11,100
You could own this.

259
00:17:11,100 --> 00:17:17,780
You these questions that we have during rounds, these questions that, you know, it's as a

260
00:17:17,780 --> 00:17:24,220
nurse, sorry, our shift in at six forty five, the six thirty p.m. question.

261
00:17:24,220 --> 00:17:25,220
Right.

262
00:17:25,220 --> 00:17:28,540
That's that's the one that needs to be.

263
00:17:28,540 --> 00:17:37,220
And that's the one that as a as a new clinician researcher, like like dig into it because

264
00:17:37,220 --> 00:17:41,780
you're passionate about it, you're passionate about it, not that that you're going to go

265
00:17:41,780 --> 00:17:46,460
to breakfast breakfast with someone or you're going to argue with someone down in the cafeteria

266
00:17:46,460 --> 00:17:50,060
over that little piece.

267
00:17:50,060 --> 00:17:54,300
Hang on to that and and own it.

268
00:17:54,300 --> 00:17:55,300
Thank you, Daiwa.

269
00:17:55,300 --> 00:17:59,140
We know one of the things that what you're saying brings up for me is many times clinicians

270
00:17:59,140 --> 00:18:02,180
will say, well, I just need to get on my mentor's project.

271
00:18:02,180 --> 00:18:03,740
I just need to get on my mentor's project.

272
00:18:03,740 --> 00:18:05,740
And they hate their mentor's project.

273
00:18:05,740 --> 00:18:08,540
It's hard to start.

274
00:18:08,540 --> 00:18:10,340
What is your advice for them?

275
00:18:10,340 --> 00:18:15,260
Well, first off, if you if you hate your mentor's project, get a different mentor.

276
00:18:15,260 --> 00:18:24,820
Because now, although I say that another one of my my mentors was Suzanne Thorie and her,

277
00:18:24,820 --> 00:18:34,020
she studied neo high risk neonatal infant feeding.

278
00:18:34,020 --> 00:18:35,900
I don't care anything about that.

279
00:18:35,900 --> 00:18:36,900
Right.

280
00:18:36,900 --> 00:18:40,860
It was all about like these these preterm infants.

281
00:18:40,860 --> 00:18:46,620
And did they did their oxygen saturation drop if they if they use this kind of a nipple

282
00:18:46,620 --> 00:18:49,300
versus that or that it met right.

283
00:18:49,300 --> 00:18:50,780
I ain't cared nothing about that.

284
00:18:50,780 --> 00:18:52,260
I hated her project.

285
00:18:52,260 --> 00:19:01,020
But she was a brilliant mentor and her patients were so similar to mine because I'm in neurocritical

286
00:19:01,020 --> 00:19:02,140
care.

287
00:19:02,140 --> 00:19:05,860
My patients can't talk to me.

288
00:19:05,860 --> 00:19:08,740
Her patients couldn't talk to her.

289
00:19:08,740 --> 00:19:15,140
And the family is a really big deal in the neuro ICU because they're they're present

290
00:19:15,140 --> 00:19:21,620
and they influence care like, you know, they they change things they do they move.

291
00:19:21,620 --> 00:19:26,420
Family is a big deal in in the NICU.

292
00:19:26,420 --> 00:19:30,380
I use a lot of machines to understand my my patients.

293
00:19:30,380 --> 00:19:31,380
Right.

294
00:19:31,380 --> 00:19:37,500
ICP monitors, heart monitors, oxygen, entitled CO2, like stroke, five, lots.

295
00:19:37,500 --> 00:19:44,580
I from from these machines, I derive an understanding of the patient.

296
00:19:44,580 --> 00:19:47,100
Because the patient can't tell me where it hurts.

297
00:19:47,100 --> 00:19:48,100
Same with her.

298
00:19:48,100 --> 00:19:49,100
Right.

299
00:19:49,100 --> 00:19:54,420
So, you know, my my people's brains aren't fully functioning.

300
00:19:54,420 --> 00:19:57,140
Her infant brain isn't fully functioning.

301
00:19:57,140 --> 00:20:06,420
So what we what we found was we have a lot of areas where where there is a commonality.

302
00:20:06,420 --> 00:20:09,340
And.

303
00:20:09,340 --> 00:20:11,740
And that's how we formed this relationship.

304
00:20:11,740 --> 00:20:16,660
And she agreed to mentor at first when when we were talking, you know, she was like, I

305
00:20:16,660 --> 00:20:18,620
don't think I'm the right person.

306
00:20:18,620 --> 00:20:25,780
And and so I think the answer to your question is if you hate your mentors project, but you

307
00:20:25,780 --> 00:20:28,540
really like that person.

308
00:20:28,540 --> 00:20:36,220
And you really think that I bet there's somewhere that maybe it's the techniques they're using

309
00:20:36,220 --> 00:20:40,260
or or or how they approach a problem.

310
00:20:40,260 --> 00:20:42,700
Find that piece.

311
00:20:42,700 --> 00:20:47,500
You may do a completely different study and and as mentors, I mean, you're a mentor, I'm

312
00:20:47,500 --> 00:20:48,660
a mentor.

313
00:20:48,660 --> 00:20:55,260
I love any time someone is foolish enough to listen to me.

314
00:20:55,260 --> 00:20:58,900
And and mentors love to mentor.

315
00:20:58,900 --> 00:21:05,460
So I bet that person really does want to help you succeed, even if it's not in their particular.

316
00:21:05,460 --> 00:21:10,820
I still have never done a study with a need.

317
00:21:10,820 --> 00:21:11,820
I love it.

318
00:21:11,820 --> 00:21:15,500
I think one of the things that sometimes, especially when the younger people are, is

319
00:21:15,500 --> 00:21:17,940
they come thinking they have to be like their mentor.

320
00:21:17,940 --> 00:21:19,860
And it doesn't have to be that way.

321
00:21:19,860 --> 00:21:23,100
But what you do want to take something from your mentor, what are you taking?

322
00:21:23,100 --> 00:21:25,660
Doesn't have to be the exact same project.

323
00:21:25,660 --> 00:21:29,820
But there's definitely something that they offer that you can take into your own project.

324
00:21:29,820 --> 00:21:31,700
And that's important to consider as well.

325
00:21:31,700 --> 00:21:33,980
Yeah, that's a brilliant way to put it.

326
00:21:33,980 --> 00:21:42,340
You know, is it and maybe that's that's one of the things people need to understand.

327
00:21:42,340 --> 00:21:46,500
Approach it, recognizing that.

328
00:21:46,500 --> 00:21:54,780
The myth, a lot of what what happens in research and medicine in general is these myths that

329
00:21:54,780 --> 00:22:00,060
everybody has to take this trajectory and you feel like you're you're the you're like

330
00:22:00,060 --> 00:22:03,020
the outlier.

331
00:22:03,020 --> 00:22:07,100
And the truth is, we're all outliers.

332
00:22:07,100 --> 00:22:09,020
And that's that's a benefit.

333
00:22:09,020 --> 00:22:16,680
Like the more outliers we have in health care, the better, because we all of our patients

334
00:22:16,680 --> 00:22:18,920
are outliers.

335
00:22:18,920 --> 00:22:22,480
And so we need we need more outliers.

336
00:22:22,480 --> 00:22:31,100
And so instead of thinking you don't belong, think like you got to be in there to to broaden

337
00:22:31,100 --> 00:22:32,100
that piece.

338
00:22:32,100 --> 00:22:33,100
Absolutely.

339
00:22:33,100 --> 00:22:38,660
And now speaking to kind of like bringing everybody in a question that I'm excited to

340
00:22:38,660 --> 00:22:44,420
ask you is why should every clinical study include a nurse investigator?

341
00:22:44,420 --> 00:22:47,420
Because I need to be fun.

342
00:22:47,420 --> 00:22:49,580
No.

343
00:22:49,580 --> 00:22:57,260
You had mentioned and and it took me I was I finished my degree probably five or six

344
00:22:57,260 --> 00:23:04,100
years before I learned how much research training most physicians get, which it turns out is

345
00:23:04,100 --> 00:23:06,980
close to none.

346
00:23:06,980 --> 00:23:10,140
Maybe one month or two in training.

347
00:23:10,140 --> 00:23:11,140
Hello.

348
00:23:11,140 --> 00:23:12,140
Right.

349
00:23:12,140 --> 00:23:20,280
And and and that opened my eyes to so most most nurse, PhD prepared nurse researchers

350
00:23:20,280 --> 00:23:25,500
have spent five to seven years of their life learning how to do clinical research.

351
00:23:25,500 --> 00:23:28,580
Like I spent seven years in my PhD program.

352
00:23:28,580 --> 00:23:35,820
I learned I took three different year long courses in methodology.

353
00:23:35,820 --> 00:23:44,380
Just how did I spent two semesters in a theory class learning how to ask a question?

354
00:23:44,380 --> 00:23:45,700
That was it.

355
00:23:45,700 --> 00:23:46,880
Right.

356
00:23:46,880 --> 00:23:52,540
So one big reason to get a nurse researcher on your team is we've probably spent a lot

357
00:23:52,540 --> 00:23:56,980
of time learning how to do research.

358
00:23:56,980 --> 00:24:03,820
Now we may not have the same question with you, but we have a whole back of ways to ask

359
00:24:03,820 --> 00:24:08,380
questions and to dig down to questions.

360
00:24:08,380 --> 00:24:17,540
Muriel Michelle, she she was at UNC and I just remember spending three hours with her

361
00:24:17,540 --> 00:24:21,200
where she kept saying, what's the question?

362
00:24:21,200 --> 00:24:24,100
And I would say, oh, the question is that she was no, no, that's not the question.

363
00:24:24,100 --> 00:24:25,200
Go deeper.

364
00:24:25,200 --> 00:24:26,200
What's the question?

365
00:24:26,200 --> 00:24:30,900
And I'm like crying like I don't know.

366
00:24:30,900 --> 00:24:37,580
But but she she taught us how to drill down to a really good question.

367
00:24:37,580 --> 00:24:41,020
And so a lot of us have have spent that.

368
00:24:41,020 --> 00:24:46,660
And we understand like nurses speak family and physician were translators.

369
00:24:46,660 --> 00:24:47,660
Right.

370
00:24:47,660 --> 00:24:50,660
We're at the bedside for 12 hours at a row.

371
00:24:50,660 --> 00:24:53,140
The same bedside in the ICU.

372
00:24:53,140 --> 00:25:01,540
And so we can speak to the reality of how are you going to collect your data?

373
00:25:01,540 --> 00:25:05,100
What data exists?

374
00:25:05,100 --> 00:25:07,860
What about the data fidelity?

375
00:25:07,860 --> 00:25:14,540
Like a lot of and if you're a physician and you believe this, I'm going to help you out

376
00:25:14,540 --> 00:25:15,540
right now.

377
00:25:15,540 --> 00:25:16,940
It's not true.

378
00:25:16,940 --> 00:25:21,540
Most of what's in the EMR is junk.

379
00:25:21,540 --> 00:25:28,100
Just because it says the blood pressure was 120 over 80 at 10 a.m. doesn't mean anything.

380
00:25:28,100 --> 00:25:31,460
It doesn't tell you what the blood pressure was at nine fifty nine.

381
00:25:31,460 --> 00:25:34,180
It might not even be 120 over 80 at 10 a.m.

382
00:25:34,180 --> 00:25:37,940
It may have been that the nurse checked the blood pressure somewhere around nine forty

383
00:25:37,940 --> 00:25:38,940
five.

384
00:25:38,940 --> 00:25:44,340
We wrote down on our little piece of paper or the computer, grabbed it or something.

385
00:25:44,340 --> 00:25:50,540
And so if you understand the fidelity of the data, which nurses intimately understand how

386
00:25:50,540 --> 00:25:56,280
stuff gets into the EMR, that's going to allow you to ask a better question.

387
00:25:56,280 --> 00:26:01,460
But also because we understand the clinical environment from the perspective of what's

388
00:26:01,460 --> 00:26:03,060
really happening.

389
00:26:03,060 --> 00:26:04,060
Right.

390
00:26:04,060 --> 00:26:09,380
And what happens for you as a physician when you as a physician walk into the room.

391
00:26:09,380 --> 00:26:13,540
Like the world stops like the nurses, the patient, the family.

392
00:26:13,540 --> 00:26:16,220
Everybody's like, OK, they're here.

393
00:26:16,220 --> 00:26:19,780
But that's not what happens as soon as you turn your back.

394
00:26:19,780 --> 00:26:25,180
And that's the environment where we can help design the study to get you the data that

395
00:26:25,180 --> 00:26:28,300
you really want.

396
00:26:28,300 --> 00:26:29,300
And to fit it in.

397
00:26:29,300 --> 00:26:35,660
So so where we're and I'm going to make up a fake example so no one gets offended that

398
00:26:35,660 --> 00:26:41,300
a physician says, oh, well, we're going to get our CTs at nine a.m.

399
00:26:41,300 --> 00:26:42,300
Right.

400
00:26:42,300 --> 00:26:46,580
Well, nine a.m. is like one of the busiest times for nurses.

401
00:26:46,580 --> 00:26:53,220
We got rounds and passing our meds and picking up after breakfast and getting that first

402
00:26:53,220 --> 00:26:54,220
walk in.

403
00:26:54,220 --> 00:26:55,220
Dude.

404
00:26:55,220 --> 00:26:59,220
How about.

405
00:26:59,220 --> 00:27:03,140
Does it really have to be nine a.m. is nine a.m. a magical time?

406
00:27:03,140 --> 00:27:05,420
And then when you talk to them, they're like, no, I don't care.

407
00:27:05,420 --> 00:27:11,020
But no, or two or three or well, how about at four o'clock in the afternoon?

408
00:27:11,020 --> 00:27:13,220
Yeah, that'd be fine.

409
00:27:13,220 --> 00:27:15,020
OK, that we can do.

410
00:27:15,020 --> 00:27:16,020
Right.

411
00:27:16,020 --> 00:27:20,100
And so having those conversations.

412
00:27:20,100 --> 00:27:22,220
With a nurse.

413
00:27:22,220 --> 00:27:25,220
It's easier to it's easier to collect the data.

414
00:27:25,220 --> 00:27:27,860
It's easier to enroll patients.

415
00:27:27,860 --> 00:27:32,940
Some of my my residents and fellows are like, oh, well, we'll just consent the family when

416
00:27:32,940 --> 00:27:35,700
data the.

417
00:27:35,700 --> 00:27:36,700
Family's not always here.

418
00:27:36,700 --> 00:27:37,700
Oh, they're always here.

419
00:27:37,700 --> 00:27:38,700
No, no.

420
00:27:38,700 --> 00:27:42,420
And you as a physician say, I'm going to be there at 10 a.m.

421
00:27:42,420 --> 00:27:44,860
There's 12 family members.

422
00:27:44,860 --> 00:27:46,860
But family ain't always here.

423
00:27:46,860 --> 00:27:47,860
Right.

424
00:27:47,860 --> 00:27:54,380
So so I think we have I think we can bring a lot towards making your study more successful,

425
00:27:54,380 --> 00:28:01,020
one because we've we've been trained in how to do research to we understand the clinical

426
00:28:01,020 --> 00:28:04,660
environment in a different way than the physician.

427
00:28:04,660 --> 00:28:06,300
We're not better than physicians.

428
00:28:06,300 --> 00:28:07,980
We're not worse than physicians.

429
00:28:07,980 --> 00:28:10,380
We are a different profession.

430
00:28:10,380 --> 00:28:18,540
And the more diversity we get with with the lens of looking at the problem.

431
00:28:18,540 --> 00:28:24,540
The more comprehensively we can understand and approach the question that will solve

432
00:28:24,540 --> 00:28:26,780
the problem.

433
00:28:26,780 --> 00:28:27,780
I love it.

434
00:28:27,780 --> 00:28:33,260
I love the idea of the need, the diversity of perspectives that strengthens every research

435
00:28:33,260 --> 00:28:34,260
study.

436
00:28:34,260 --> 00:28:38,980
And if you are invested in your study, actually succeeding and coming up with an answer that

437
00:28:38,980 --> 00:28:44,580
actually is meaningful and real, you should involve the people who are kind of drivers

438
00:28:44,580 --> 00:28:46,820
of patient care at the bedside.

439
00:28:46,820 --> 00:28:49,060
Yeah, I love the way you put that.

440
00:28:49,060 --> 00:28:50,060
I love it.

441
00:28:50,060 --> 00:28:52,060
Can I start over again and say that?

442
00:28:52,060 --> 00:28:54,820
Well, let me ask you this, though.

443
00:28:54,820 --> 00:28:58,940
OK, two things, because, you know, I listened to a talk that you gave at the American Society

444
00:28:58,940 --> 00:29:03,220
for Aforesis meeting in in April, which is phenomenal.

445
00:29:03,220 --> 00:29:07,500
And one of the things you talk about is authorship for your nursing colleagues.

446
00:29:07,500 --> 00:29:08,900
And so I want you to speak to that.

447
00:29:08,900 --> 00:29:14,540
And I also want you to speak to as physicians, we don't necessarily have a lot of nurses

448
00:29:14,540 --> 00:29:19,180
in our circles research wise, even though, of course, we're interacting with nurses clinically.

449
00:29:19,180 --> 00:29:25,580
Where do you go to find a nurse who's trained in research who can be part of your study?

450
00:29:25,580 --> 00:29:28,340
I bet there's more of them there than you think.

451
00:29:28,340 --> 00:29:29,340
Right.

452
00:29:29,340 --> 00:29:33,620
I like saying, well, I don't have anyone who's who's interested in.

453
00:29:33,620 --> 00:29:34,860
I don't know.

454
00:29:34,860 --> 00:29:41,460
I don't have anyone who's who's interested in the same band that I'm interested in.

455
00:29:41,460 --> 00:29:44,300
Well, have you told you have you have you asked?

456
00:29:44,300 --> 00:29:45,580
Right.

457
00:29:45,580 --> 00:29:47,980
And then you find out that actually.

458
00:29:47,980 --> 00:29:50,620
So do you know who Lindsey Stirling is?

459
00:29:50,620 --> 00:29:54,780
OK, first off, got to look up Lindsey Stirling.

460
00:29:54,780 --> 00:29:57,700
She is amazing.

461
00:29:57,700 --> 00:30:03,380
And as a musician, she's just like changed my perspective of classical music.

462
00:30:03,380 --> 00:30:08,540
But I'm like, yeah, nobody knows.

463
00:30:08,540 --> 00:30:14,300
And so I was I when I do statistics, I always play music and I never I always use classical

464
00:30:14,300 --> 00:30:19,860
because I don't want to sing the words while I'm writing code.

465
00:30:19,860 --> 00:30:24,540
And I was playing that and somebody walked by and they go, oh, that's Lindsey Stirling.

466
00:30:24,540 --> 00:30:25,860
You know, right.

467
00:30:25,860 --> 00:30:31,940
And then I mentioned and it turns out a whole lot of people are into Lindsey Stirling.

468
00:30:31,940 --> 00:30:36,660
But it's it's that whole thing where you we all think we're the outliers until you find

469
00:30:36,660 --> 00:30:39,620
out like we're all outliers.

470
00:30:39,620 --> 00:30:44,660
And so you may have PhD prepared nurses that you just haven't asked about or nurses who

471
00:30:44,660 --> 00:30:47,780
are interested in research that you haven't asked about.

472
00:30:47,780 --> 00:30:54,860
When I started the the Neuroscience Nursing Research Center here in Dallas.

473
00:30:54,860 --> 00:31:02,700
They had they had done almost zero clinical research here with nursing.

474
00:31:02,700 --> 00:31:09,820
I have had over two hundred and fifty nurses in 10 years do studies.

475
00:31:09,820 --> 00:31:10,820
They all want to do it.

476
00:31:10,820 --> 00:31:11,820
No.

477
00:31:11,820 --> 00:31:16,260
And a lot of it is like, well, yeah, no one's ever asked.

478
00:31:16,260 --> 00:31:17,260
That's like so.

479
00:31:17,260 --> 00:31:25,540
Just ask, just ask and you shall find that's one in terms of authorship.

480
00:31:25,540 --> 00:31:29,740
The the.

481
00:31:29,740 --> 00:31:33,020
International guidelines, International Committee on Medical Journal Ethics and the Committee

482
00:31:33,020 --> 00:31:39,500
on Publication Ethics all share basically that there are four criteria to meet authorship.

483
00:31:39,500 --> 00:31:42,800
And if you meet those criteria, you should be an author.

484
00:31:42,800 --> 00:31:50,380
And it boils down to did the person provide an intellectual contribution?

485
00:31:50,380 --> 00:31:53,900
Now you can say no and that they didn't.

486
00:31:53,900 --> 00:31:57,700
And you say, well, one of the things is, did they make critical revisions to the manuscript?

487
00:31:57,700 --> 00:31:58,700
They did.

488
00:31:58,700 --> 00:32:00,500
Well, did you show them the manuscript?

489
00:32:00,500 --> 00:32:02,860
Did you give the manuscript to a nurse?

490
00:32:02,860 --> 00:32:04,800
It's like.

491
00:32:04,800 --> 00:32:09,340
You said you wrote here that all patients get out of bed on day one and they actually

492
00:32:09,340 --> 00:32:16,060
don't write because because we know things and you may think they did, you know, or you

493
00:32:16,060 --> 00:32:19,780
may think that you wrote an order and something happened.

494
00:32:19,780 --> 00:32:21,940
Oh, it's too.

495
00:32:21,940 --> 00:32:27,780
So so so they can make critical revisions, but also.

496
00:32:27,780 --> 00:32:34,380
It's important to recognize and and and I'll tell you why it benefits you as a physician

497
00:32:34,380 --> 00:32:37,540
to get a nurse as an author.

498
00:32:37,540 --> 00:32:41,380
First off, it opens up a whole nother range of places you can publish your work, which

499
00:32:41,380 --> 00:32:46,700
is important, but also.

500
00:32:46,700 --> 00:32:48,780
It gives you it gives you that buy in.

501
00:32:48,780 --> 00:32:49,780
Right.

502
00:32:49,780 --> 00:32:55,580
I mean, that when you're when you're going to do another study again in the in I'm in

503
00:32:55,580 --> 00:33:00,060
the ICU, wherever you happen to be, you're going to come into the ICU and say, hey, I

504
00:33:00,060 --> 00:33:02,700
got this this thing we're going to do, everybody.

505
00:33:02,700 --> 00:33:05,580
And the nurses are like, so you want us to do your work again and you're not going to

506
00:33:05,580 --> 00:33:06,580
recognize us.

507
00:33:06,580 --> 00:33:07,580
Yeah, sure.

508
00:33:07,580 --> 00:33:08,580
We'll get on that right away.

509
00:33:08,580 --> 00:33:09,580
Yeah.

510
00:33:09,580 --> 00:33:12,780
But if you're but if but if you're like.

511
00:33:12,780 --> 00:33:20,940
Dr. X, when she asked us to help, like she she rewards us, she includes us and she recognizes

512
00:33:20,940 --> 00:33:21,940
our value.

513
00:33:21,940 --> 00:33:22,940
Yeah, I am.

514
00:33:22,940 --> 00:33:27,740
I am so into that.

515
00:33:27,740 --> 00:33:32,300
And she's going to she's going to ask, like, how can I make this study better?

516
00:33:32,300 --> 00:33:35,180
And we can we can solve problems together.

517
00:33:35,180 --> 00:33:45,660
Like most nurses innately in our in our blood, in our DNA, in our training, we want to help.

518
00:33:45,660 --> 00:33:53,100
So you know, that doesn't mean we shouldn't be recognized like you recognize for your

519
00:33:53,100 --> 00:33:54,100
contribution.

520
00:33:54,100 --> 00:33:55,100
And that's the authorship.

521
00:33:55,100 --> 00:33:56,100
Absolutely.

522
00:33:56,100 --> 00:33:57,100
Absolutely.

523
00:33:57,100 --> 00:34:01,380
I will tell you that recently I asked one of our nurses who's been working on a project

524
00:34:01,380 --> 00:34:03,060
with me to be an author.

525
00:34:03,060 --> 00:34:06,680
And it really to be honest, the response was overwhelming.

526
00:34:06,680 --> 00:34:11,140
She was like, I mean, she was so excited, told her supervisor, I got to hear about it

527
00:34:11,140 --> 00:34:12,140
from the supervisor.

528
00:34:12,140 --> 00:34:14,340
And to be honest, she's just run off with the project.

529
00:34:14,340 --> 00:34:16,260
It's like, oh, OK.

530
00:34:16,260 --> 00:34:19,060
So it's it's it's been good.

531
00:34:19,060 --> 00:34:20,060
I do agree.

532
00:34:20,060 --> 00:34:23,380
I think anybody who's made any significant contribution really should be an author, whether

533
00:34:23,380 --> 00:34:25,620
they're paid or not, they should be an author.

534
00:34:25,620 --> 00:34:27,140
And so I appreciate that.

535
00:34:27,140 --> 00:34:28,140
That's your perspective.

536
00:34:28,140 --> 00:34:29,140
And I agree.

537
00:34:29,140 --> 00:34:30,140
I think all physicians should think about that.

538
00:34:30,140 --> 00:34:32,140
OK, I'm glad it worked out well.

539
00:34:32,140 --> 00:34:33,140
Oh, yes.

540
00:34:33,140 --> 00:34:34,140
Oh, my goodness.

541
00:34:34,140 --> 00:34:36,660
Yes, I was actually thinking I was like, I should do this more often.

542
00:34:36,660 --> 00:34:41,500
But I love what you said about inviting people because you just assume people are not interested.

543
00:34:41,500 --> 00:34:44,220
But but but we should open the doors and see who comes in.

544
00:34:44,220 --> 00:34:45,220
Yeah.

545
00:34:45,220 --> 00:34:46,220
Yeah.

546
00:34:46,220 --> 00:34:47,220
Yeah.

547
00:34:47,220 --> 00:34:51,900
Look for someone who's not like you so you can get something different that you don't

548
00:34:51,900 --> 00:34:54,420
already know.

549
00:34:54,420 --> 00:34:56,620
And it's always a great journey.

550
00:34:56,620 --> 00:34:58,420
Oh, I love that.

551
00:34:58,420 --> 00:34:59,660
I love that.

552
00:34:59,660 --> 00:35:01,660
I love that.

553
00:35:01,660 --> 00:35:04,500
Look for someone who's not like you so you can get something different.

554
00:35:04,500 --> 00:35:05,500
Yes.

555
00:35:05,500 --> 00:35:07,140
Yes, it's a diversity bonus.

556
00:35:07,140 --> 00:35:08,140
I love it.

557
00:35:08,140 --> 00:35:09,140
Yeah.

558
00:35:09,140 --> 00:35:10,140
Diversity bonus.

559
00:35:10,140 --> 00:35:12,660
But but also it keeps you out of the echo chain.

560
00:35:12,660 --> 00:35:13,860
Right.

561
00:35:13,860 --> 00:35:14,860
That's right.

562
00:35:14,860 --> 00:35:24,180
And it's the echo chamber that ruins good science because you you should not do like

563
00:35:24,180 --> 00:35:31,580
on many ways we get guilty of I'm going to design this study to prove I was right.

564
00:35:31,580 --> 00:35:33,420
And those studies inevitably fail.

565
00:35:33,420 --> 00:35:36,900
You have to design a study to ask a question.

566
00:35:36,900 --> 00:35:38,660
And the echo chamber will kill you.

567
00:35:38,660 --> 00:35:44,660
That's why you have to you have to get that that broad depth of perspective.

568
00:35:44,660 --> 00:35:45,660
Absolutely.

569
00:35:45,660 --> 00:35:46,660
Absolutely.

570
00:35:46,660 --> 00:35:51,900
So that people can question the interpretation and give you different perspectives on how

571
00:35:51,900 --> 00:35:53,980
an interpretation you may not have thought of.

572
00:35:53,980 --> 00:35:54,980
Yeah.

573
00:35:54,980 --> 00:35:55,980
Yeah.

574
00:35:55,980 --> 00:35:56,980
This is really good.

575
00:35:56,980 --> 00:35:57,980
Okay.

576
00:35:57,980 --> 00:35:58,980
You've talked about so many great things.

577
00:35:58,980 --> 00:36:03,660
I'm coming to the end of the show, but I wanted to ask what what haven't I asked you what's

578
00:36:03,660 --> 00:36:08,580
an important thing for our audience to know that that we haven't talked about yet.

579
00:36:08,580 --> 00:36:11,940
Oh, I know.

580
00:36:11,940 --> 00:36:13,540
We haven't talked about prividemics.

581
00:36:13,540 --> 00:36:14,540
Private.

582
00:36:14,540 --> 00:36:15,540
Private.

583
00:36:15,540 --> 00:36:16,540
Yeah.

584
00:36:16,540 --> 00:36:17,540
Yeah.

585
00:36:17,540 --> 00:36:21,800
So private demics used to be a derogatory term.

586
00:36:21,800 --> 00:36:24,020
I think we're academics.

587
00:36:24,020 --> 00:36:25,020
Right.

588
00:36:25,020 --> 00:36:28,700
You go through med school and you get your degree and then you have a choice.

589
00:36:28,700 --> 00:36:32,380
You can go into academia or into private practice.

590
00:36:32,380 --> 00:36:37,460
And it was it was almost you know it was almost like the Montagues and the Capulets.

591
00:36:37,460 --> 00:36:38,460
Right.

592
00:36:38,460 --> 00:36:39,460
You could be one or the other.

593
00:36:39,460 --> 00:36:46,380
And and academics did research and prividemics didn't private practice didn't.

594
00:36:46,380 --> 00:36:55,340
Well along comes our need to understand how research translates across multiple environments

595
00:36:55,340 --> 00:36:57,380
of care.

596
00:36:57,380 --> 00:37:03,500
And so academics back in the late 90s early 2000s started reaching out to private practice

597
00:37:03,500 --> 00:37:07,380
and say hey will you be part of this study.

598
00:37:07,380 --> 00:37:12,420
And private practice docs who are smart people.

599
00:37:12,420 --> 00:37:20,100
And they're working in East Texas with a hospital you know a seven bed hospital.

600
00:37:20,100 --> 00:37:23,340
They have questions too.

601
00:37:23,340 --> 00:37:30,580
And it turns out that if smart people working in non academic centers ask good questions

602
00:37:30,580 --> 00:37:36,340
they can still contribute to the overall body of knowledge in a way that me working in the

603
00:37:36,340 --> 00:37:39,460
center of Dallas can't.

604
00:37:39,460 --> 00:37:40,900
Right.

605
00:37:40,900 --> 00:37:44,020
And that is a private practice academic.

606
00:37:44,020 --> 00:37:52,140
And you can actually look in Medline and there are now articles written about private demics.

607
00:37:52,140 --> 00:38:01,260
So do just because you are out in them in clinical practice or you are in an area hundreds

608
00:38:01,260 --> 00:38:07,180
of miles away from a university setting that does not mean you cannot do research.

609
00:38:07,180 --> 00:38:12,820
And it doesn't mean you can't do meaningful research because you have a different environment

610
00:38:12,820 --> 00:38:15,740
different questions different patient population.

611
00:38:15,740 --> 00:38:16,820
Right.

612
00:38:16,820 --> 00:38:17,820
I had this.

613
00:38:17,820 --> 00:38:19,940
I know you're running out of time.

614
00:38:19,940 --> 00:38:21,500
I got fortunate.

615
00:38:21,500 --> 00:38:28,700
I was asked to talk give a lecture on the Navajo reservation once and the docs there

616
00:38:28,700 --> 00:38:34,020
they fly in for seven days and they treat anything and everything that comes into this

617
00:38:34,020 --> 00:38:35,020
four bed hospital.

618
00:38:35,020 --> 00:38:36,020
Right.

619
00:38:36,020 --> 00:38:41,060
You might you might refill prescription for hypertension go deliver a baby take care of

620
00:38:41,060 --> 00:38:51,420
a trauma patient and then advise somebody on mental health all within like an hour.

621
00:38:51,420 --> 00:38:53,460
That is an environment of care.

622
00:38:53,460 --> 00:38:59,860
I can't even conceive of being in a high resource area.

623
00:38:59,860 --> 00:39:05,020
Who's going to do the research on that.

624
00:39:05,020 --> 00:39:14,060
Who's going to figure out best practice for critical access hospitals if it's not a private

625
00:39:14,060 --> 00:39:15,060
practice.

626
00:39:15,060 --> 00:39:23,380
So so just because you're you if you can ask a question you can be a researcher.

627
00:39:23,380 --> 00:39:24,660
I love it.

628
00:39:24,660 --> 00:39:27,780
The door is open for everybody to participate.

629
00:39:27,780 --> 00:39:31,200
You don't have to be in an academic medical center to do research.

630
00:39:31,200 --> 00:39:32,900
You need to be able to ask good questions.

631
00:39:32,900 --> 00:39:33,900
I love it.

632
00:39:33,900 --> 00:39:34,900
Oh I love it.

633
00:39:34,900 --> 00:39:36,540
That was a great great note to end on.

634
00:39:36,540 --> 00:39:42,300
You know why you've just you just I mean it's just every time I hear from you I feel like

635
00:39:42,300 --> 00:39:43,300
I'm inspired.

636
00:39:43,300 --> 00:39:48,740
I learn new things and so I think it's my life's mission now to hear from you more.

637
00:39:48,740 --> 00:39:54,380
Well I hope our paths cross much more often and I've enjoyed talking to you.

638
00:39:54,380 --> 00:39:57,980
Now it's been my pleasure and I know my audience has enjoyed listening.

639
00:39:57,980 --> 00:40:03,020
I would say to everyone who's listening this is a dynamite dynamite episode and someone

640
00:40:03,020 --> 00:40:04,020
else has got to hear it.

641
00:40:04,020 --> 00:40:06,820
If you're a mentor you need to share it with a mentee.

642
00:40:06,820 --> 00:40:11,580
If you're a mentee you share it with your mentor your peer group and if you are in academia

643
00:40:11,580 --> 00:40:15,020
you should share it with someone in private practice because they need to hear about private

644
00:40:15,020 --> 00:40:17,460
ethics and how they can get involved as well.

645
00:40:17,460 --> 00:40:19,620
And with your nurses.

646
00:40:19,620 --> 00:40:24,300
And with your nurses yes every one of your studies from now on should include a nurse

647
00:40:24,300 --> 00:40:25,300
as a co-investigator.

648
00:40:25,300 --> 00:40:26,300
I love it.

649
00:40:26,300 --> 00:40:30,260
Dai Wai thank you for being on the show.

650
00:40:30,260 --> 00:40:31,260
Thank you.

651
00:40:31,260 --> 00:40:41,300
All right everyone we'll see you again next time.

652
00:40:41,300 --> 00:40:46,660
Thanks for listening to this episode of the Clinician Researcher podcast where academic

653
00:40:46,660 --> 00:40:52,500
clinicians learn the skills to build their own research program whether or not they have

654
00:40:52,500 --> 00:40:53,500
a mentor.

655
00:40:53,500 --> 00:40:59,580
If you found the information in this episode to be helpful don't keep it all to yourself.

656
00:40:59,580 --> 00:41:01,300
Someone else needs to hear it.

657
00:41:01,300 --> 00:41:05,360
So take a minute right now and share it.

658
00:41:05,360 --> 00:41:10,820
As you share this episode you become part of our mission to help launch a new generation

659
00:41:10,820 --> 00:41:16,460
of clinician researchers who make transformative discoveries that change the way we do health

660
00:41:16,460 --> 00:41:44,380
care.