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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 everyone, welcome to today's episode.

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I am Toyosi Onwuemene, your host on the Clinician Researcher podcast.

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What a pleasure to be here today.

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Thank you for tuning in.

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Thank you for listening.

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Today, I'm talking about how to find a biostatistician to work with.

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And before I start, I want to share with you that we are opening up slots for clinicians

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who are interested in Academic Negotiation Academy, and this is to help you negotiate

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your research career so that you can lead the research program that you really want

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to lead and thrive while you do it.

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So if you're interested, sign up on our website, clinicianresearcherpodcast.com.

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All right, we're talking about how to find a biostatistician to work with.

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And I want to tell you, it kind of depends whether you're looking for a biostatistician

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or not.

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Depends on the kind of research you do.

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So I'm a health services researcher.

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I do a lot of statistics heavy type analyses.

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And finding a biostatistician to work with can be difficult.

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So it does depend from institution to institution.

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I'm going to share with you some insights that I have that I want you to think about

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as general principles.

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But I've always known that I needed a statistician, at least kind of theoretically everybody tells

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you you do.

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And you're like, well, I need a statistician, OK.

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But one of the ways that I finally really understood that was when I finally had submitted

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a grant.

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This was a career development award that I had submitted.

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And when the award was not discussed, I had the opportunity after receiving the summary

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statements to talk with the program officer.

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And the very first thing the program officer said to me when we started talking was, oh,

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you're the one who didn't have a statistician.

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And I think I was kind of surprised by that because I was like, but how could you tell

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I didn't have a statistician?

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And you know, it's interesting.

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Of course they could tell.

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So on that panel, they usually will have a statistician represented to answer questions

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of does the statistics seem appropriate?

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Are the analyses appropriate for the particular hypothesis?

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And so yes, there will be a statistician reviewing your grant.

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And if you wrote the grant without a statistician, they can usually tell.

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Now maybe you have statistics background and you can write the methodology for statistics.

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Sure, good for you.

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But if you don't have that background and you're going to write a grant that involves

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any statistics, it is wise to get the involvement of a statistician.

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And many times, clinician researchers don't necessarily have access to statistical help.

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And so I want to just shed some light on a couple of things I think are helpful for finding

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a biostatistician collaborator.

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And actually, later on the show, I'm going to have a statistician come talk to us about

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how clinician researchers can work with statisticians for more effective collaboration.

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So stay tuned for that.

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Okay, so the first thing that I want to share with you is that a biostatistician is a collaborator.

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I want to say that again.

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Biostatistician is a collaborator.

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Because in research, we have this sense that we're doing the work and then the statistician

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is like the person who just comes and does like the magic analysis at the end.

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And that's the end of the story.

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Like, oh, great, we finished the analysis, come and do the statistics.

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And it doesn't actually work.

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It doesn't work that way.

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I mean, you can do it that way.

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It's not very effective.

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And the reason it's not very effective is because statistics is not just about doing

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math.

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It's about setting up the right equations, so to speak, to be able to do the math well,

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setting up the room well.

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Like, maybe if I would correlate it to like podcasting, you can make audio sound better

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post-production.

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But if you were there at the beginning, like, you know, making sure that the space was quiet

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and that you could record the best possible audio that you have at the beginning, then

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you don't need people doctoring much at the end.

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And so I think of a statistician in that way, where it's like if you're setting up the study,

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having a statistician work with you to say, okay, these are the parameters that you need

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to make sure that you have considered.

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These are the variables you need to collect.

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This is the systematic fashion in which you need to collect these variables.

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And then at the end, I'll come and do my magic math.

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It'll be so awesome.

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That's how you collaborate with a statistician.

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So from the very beginning, a statistician should really be part of your formulating

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your research question.

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And that's why it's important not to think of a biostatistician as an afterthought.

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This is not like a, I finished my analysis, who's going to analyze it for me?

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And to be honest, many of us, that's where we are.

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It's like, well, the project's been done.

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Now we need some help.

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Okay, great.

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And biostatisticians are awesome people, at least the ones I've worked with are.

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And they're usually able to take things and make it better.

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But if you really want optimal strategy, it really does help to meet with a biostatistician

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upfront to be clear about what question you're trying to answer.

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And one of the things that they do well is they understand the research methodology where

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it's like, hmm, that's a question you want to answer.

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This way that you're going about doing it will not answer that question.

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This is the question it will answer.

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And that's helpful to know upfront.

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So first of all, figure out that the biostatistician is your collaborator.

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And for that reason, think about how do you incorporate the biostatistician early on in

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the whole process and not just waiting until it's time for the analysis.

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So biostatistician is your collaborator point number one.

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Number two is to develop your research plan.

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So for many of us who may not have had research training, sometimes there's a sense that you

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are just kind of doing research on the fly.

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But research is not really successful when it's done on the fly.

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You could get lucky and sometimes we do.

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But really being very systematic about what question you want to answer through this project

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and being very systematic about the variables you're collecting and how those variables

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are being collected is pretty important.

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Sometimes as clinicians, we have the tendency to just say, let's just gather as much data

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as we can and then let's see what shakes out.

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And really, it's not a very effective strategy.

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It's important to figure out what is the question we hope to answer at the end and what is the

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data that we need to collect that helps us do that.

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And sometimes there's a sense of like, we've got to collect all the data we can now.

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We can't come back.

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And that's kind of like, I would say it's a scarcity type mindset.

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You will always be able to come back.

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Always be clear about what you're trying to answer and then be focused.

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And it helps you to be able to accomplish things a little bit more effectively than

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when you're paralyzed trying to collect all possible data.

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And at the end, you miss the data that you actually should have collected to be able

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to answer the question you wanted to answer.

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And so recognize that you need a plan.

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And this is why your statistical collaborator can help you at the very beginning of the

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plan to figure out how to pull it together and what variables you're going to need to

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make the plan a reality.

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Because what you don't want to do is get to the end of the study and it's like, oh, we

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can't answer the question because we didn't collect variables correctly.

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So develop your research plan, ideally with a statistical collaborator as part of the

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early development process.

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Okay.

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Number three is to determine what kind of statistical support you need.

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This is really important because I started first of all talking about the need for a

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statistical collaborator.

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There are many different kinds of statistical collaborators.

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There are many kinds of statisticians.

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And the experience that they have is myriad.

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So recently I started working with a statistician who's like, well, my expertise is trajectory

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class analysis.

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And I'm like, well, what?

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What?

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But every statistician has an air of expertise.

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And especially when you think about statistical collaborators, you're really talking about

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faculty.

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Faculty who have statistical methodology that they've honed and actually they're probably

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innovating and creating new types of statistical methodology.

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So your collaborator is really someone who's able to help think big picture about the project.

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But they may not be running their own statistical analyses.

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That's important to note.

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And sometimes clinician researchers are just like, well, we're just looking for someone

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to run the numbers.

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Well, you're just looking for someone to run the numbers, maybe a master's level statistician.

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But your faculty bio statistician, usually a PhD faculty statistician, is really like

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the big thinker.

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And so you want to be clear about what kind of statistical support you need.

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And hopefully you're not just looking for someone to crunch the numbers, because that's

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not necessarily what the collaborator does.

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They can crunch numbers, but you're better served with them really helping you think

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big picture rather than with them doing the number crunching.

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So you might need number crunching help and the statistician kind of like as a collaborator

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to really think through the data.

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But definitely be clear about what kind of statistical support you need.

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OK.

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Number four is to find out where the statisticians hide.

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So at every institution, every institution is different, but statisticians kind of exist

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independently.

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So sometimes there are statisticians who are associated with divisions or associated with

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departments.

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And sometimes statisticians have their own department where you kind of have to go to

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a hub to be able to kind of recruit a statistician.

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But whatever happens, it's important for you to understand how statistical support works

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at your institution.

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What are the norms?

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How have people succeeded?

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So it's knowing what the general norms are and then understanding what's outside of the

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norms.

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So for example, perhaps the only way you can get access to a biostatistician at your institution

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is for them to be part of an established departmental budget or something.

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So to have access to the statistician, then you kind of have to go through a process where

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your project is approved and then you can talk to the statistician.

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Maybe that's the way it works.

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Or it could be that just individual people hook up with biostatistical faculty and they're

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like off to the races.

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So you do need to understand the structures within your own institution and then how other

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people have succeeded.

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Because it may be that you don't have the bandwidth to wait for the couple of months

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that's necessary to be next in line for the faculty biostatistician that's affiliated

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with your program.

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It may be that you are able to figure out a way to find a statistical student to work

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with you and a faculty member who's willing to look over their shoulder and just make

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sure they're doing things right.

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There are many, many, many, many ways to make this work.

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But understanding what the range of possibilities is at your institution allows you to know

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how to meet the needs that you have within the confines of the resources that you currently

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have available to you.

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And so that's really important.

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Know where the statisticians hide, aka figure out what the processes are, what it takes

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to work with a statistical collaborator, and what are the margins of what that could look

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like.

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Okay.

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Number five is to pitch your statistical collaborator.

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And I say pitch them.

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And so it's interesting because some people work within groups where this is just a statistician

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for the group.

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It doesn't matter what your project is.

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This is just a statistician everybody works with.

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And I will tell you that an engaged statistician will always be better than the statistician

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you just have to work with.

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And so helping statisticians that you work with understand your project.

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Why does that matter?

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Why is it important?

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Why is the question that you want to have answered important to be answered?

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Why have you decided to answer it in this way?

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And so it's important for you to help your statistical collaborator come on board and

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really understand the premise behind the work.

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Help them understand what's going on in the background because it does help them kind

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of better understand where the numbers are coming from and what the numbers are supposed

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to do for you.

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And ultimately, your biostatistical collaborator is likely not going to be a clinician.

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So there's so many things they don't understand clinically.

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Your clinical expertise is so important and you framing the project in light of the clinical

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problem is going to be super, super important as well.

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So you want to pitch your statistical collaborator and help them have a great reason to work

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with you.

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Okay.

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So there are five things I talked about.

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Understand that the biostatistician really is a collaborator.

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Make sure that you develop your research plan probably in concert with a statistical collaborator.

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Find out what kind of statistical support you actually need.

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Find out where your statisticians hide.

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So understand the structure of your institution, how you can work around them, and then pitch

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your statistical collaborator.

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Actually sell them on your project.

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Help them to really be a contributor to your project as well.

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So that's definitely important for finding a biostatistical collaborator.

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And if you're struggling and you're like, I'm trying to move work forward.

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I can't even find a statistician.

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Yes, there's someone in my institution who's supposed to be helping me and I can't make

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it work.

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It's possible that coaching will help you move it forward because what you really are

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doing is negotiating for resources.

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See it all comes back to negotiation.

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So if you are interested in learning to negotiate better for resources, including negotiating

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access to biostatistical support, we can help you in the Academic Negotiation Academy.

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For more information, you should visit our website, clinicianresearcherpodcast.com.

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Okay.

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Somebody else needs to hear this podcast.

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I'm going to ask you to please, please, please share it with someone else.

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And if you've been a listener for these last couple of episodes, please subscribe and rate

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the show so that other people can find us as well.

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All right.

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It's been a pleasure talking with you today.

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I look forward to talking with you again the next time.

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Thanks for listening to this episode of the Clinician Researcher Podcast, where academic

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clinicians learn the skills to build their own research program, whether or not they

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have a mentor.

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If you found the information in this episode to be helpful, don't keep it all to yourself.

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Someone else needs to hear it.

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So take a minute right now and share it.

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As you share this episode, you become part of our mission to help launch a new generation

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of clinician researchers who make transformative discoveries that change the way we do healthcare.