Episode 4 | Revolutionizing Healthcare Through Informatics | From Research to Real Life Podcast | Clinical and Translational Science Collaborative (CTSC)

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In this episode our host, Craig Jarrett, MD (University Hospitals) sits down with David Kaelber, MD (MetroHealth) CTSC of Northern Ohio Informatics Module Lead to discuss the intersection of informatics and translational science. Learn more about how systems like Epic, Cosmos, TriNetX, and Lyceum are used in research and provide insights into health trends and medical discoveries.

Links:

To gain access to these systems or to request an Informatics consult,
For those interested in joining the first ever multi-institution Epic Cosmos Datathon, registration is open for the December 7th event.
The inaugural CTSC Research Discovery Day will take place on Friday, March 21, 2025. Visit our website to learn more and get involved.
The CTSC offers monthly Science Cafe webinars, see the schedule of speakers and topics.
The second cohort for our Advanced Translational Leadership in Academic Science (ATLAS) will focus on early investigators, learn more on our website.

Transcript

"Basically three quarters of people in the United States have some information in the Epic electronic health record. So probably if you're listening, you or someone you know have some information in the Epic electronic health record." - David Kaelber, MD

[Intro]

From Research to Real Life, A podcast by the Clinical and Translational Science Collaborative of Northern Ohio.

Craig Jarrett:

Hello and welcome to From Research to Real Life. I'm your host, Craig Jarrett. I'm a clinical informatics fellow at MetroHealth. I work clinically in cardiothoracic surgery at University Hospitals. And I'm a PhD candidate in clinical informatics at Case Western. Today we have a special guest with us, Dr. David Kaelber, Vice President of health informatics at MetroHealth and the CTSC Informatics module lead. Welcome, David.

David Kaelber:

Thank you. Great to be here Craig.

Craig Jarrett:

Doctor Kaleber, I met you when I was, finishing my cardiothoracic surgery fellowship at University Hospitals. I met you through two of your fellows who are now on staff here at MetroHealth. And I'd like to go back to what got me interested into clinical informatics and meeting you through your fellows.

I was taking a class at �ǿմ�ý, in clinical informatics, because I was interested in pursuing this as a career. Your fellows had great things to say about the MetroHealth fellowship. And here we are.

On today's episode, we will explore the intersection of informatics and translational science. We'll discuss the systems we have access to provided by the CTSC highlighting their significance, similarities and differences.

And we will talk about some use case scenarios where these systems have been used in research. Join us as we dive into how informatics enhances our understanding and application of translational science.

Let's begin our conversation talking about Epic. Epic as an electronic health record software for large hospitals and health systems in the United States. Epic is implemented at four of our partner sites CCF, Metro Health, University Hospitals, and University of Toledo. The Epic system offers features for clinical research and recognition of medical conditions relevant to specific clinical trials. How does Epic support translational research efforts and how does it integrate with other systems?

David Kaelber:

Right, so the Epic electronic health record, probably as many of the audience might or might not be aware, basically three quarters of people in the United States have some information in the Epic electronic health record. So probably if you're listening, you or someone, you know, some information on the Epic electronic health record. So then that sort of provides a huge foundation for all types of, clinical and translational research. And so I sort of point to a couple of, of ways that that can can happen. First of all, within the Epic electronic health record, there's actually a whole research module, and that can do everything from help with recruitment to prospective trials to, identifying certain research drugs that may be need to be blinded in the electronic health record.

There's literally dozens and dozens of features within the research module of the electronic health record, even including helping with billing, that really just facilitate, clinical research. So that's one area to think about. A second area to think about is, actually using the electronic health record as a tool to do research to change care. So I'll just give one example of this.

So, MetroHealth, we've run a number of studies over time to really decrease smoking rates. And what we do is we're able to put certain prompts and certain workflows in our Epic electronic health record to one really help to identify people who are smokers. Identify their readiness to change, and then help provide them with the appropriate, tools, whether it be counseling, nicotine replacement or other things to enable them to stop smoking. So these are all externally funded research grants.

And then the third way that I would point to how the electronic health record is, helping is through big data or huge data sets. Either within an individual health care system, electronic health records, or now we're starting to get to systems one. I think we'll touch upon a little bit later as well, where we can combine de-identified and aggregated standardized electronic health record data now across millions and even hundreds of millions of patients. And that's a a data set that's available literally has not been available in the history of the world before to conduct certain types of research.

Craig Jarrett:

Great. You've talked about some use case scenarios where Epic has played a crucial role. Can you elaborate on a couple of additional studies that specifically you've used, for instance, Cosmos or even the institutional data set available from Epic?

David Kaelber:

Certainly. So I'll start with this is like an oldie but goodie. So when I started in this space, about now, 17, 18 years ago, I was actually medical director for my PhD pediatric weight management program. And as part of this, I would see children that would be referred to me because of their weight problems. But then in trying to do a comprehensive review, I would also see that they had a blood pressure problem that had not been diagnosed before. So what happened is every week in my clinic, I would see one patient like this, another but it was all anecdotal. And so after a couple months of this, I said, wow, I wonder how much of an issue this undiagnosed pediatric hypertension could be just within the mental health data. So at the time, we basically sort of had a data request button on our internet. And so I requested data which to me at the time seemed amazing on like 15,000 patients. And again, as a provider, just seeing a couple patients a day, 15,000 seemed amazing. And so basically what I was able to do with those 15,000in patients or so, I looked at all the blood pressures that we'd recorded on those children, determined if they were high or not, and they had have at least three that were high in our meet the criteria for hypertension, and then to see how many of those children who met the criteria for pediatric hypertension based on data, just sitting in front of us and the electronic health record had actually ever had their their blood pressure problem diagnosed, and it was only about a quarter of the children.

And so this is like 2007, 2008. This is actually recognized as one of the top ten breakthroughs in all of stroke and cardiovascular medicine by the American Heart Association. Back that, you know, 17, 18 years ago. So that's when I thought 15,000 patients was big data. So I know we've exposed you some to as a fellow, you know, literally over more than a decade now, I've worked with, for example, the Epic corporation to now create something called cosmos, where now we have over 275 million patients worth of electronic health record data. And so we've really been able to do some very interesting things with that as well.

So one example I'd point to recently we we were working with a medical school student, at Case. And she had a very interesting question about gun violence. And one of the very interesting things about Cosmos is it does have some it's still maintains all the data to be de-identified, but it maintains some geographic specificity. So what Sara was able to do is she's able to look at different restrictiveness of state gun laws by state and then correlate that with, people presenting to the emergency department with gun related injuries. And I think it's something that makes intuitive sense to many of us, but we never had the data before. It's basically a straight linear relationship. So, you know, the the less restrictive gun laws are in a state, then the more the incidence of people presenting to the emergency departments with, gun related injuries.

Craig Jarrett:

Very interesting work. And can you just highlight how getting data, institutional data is now different with Cosmos, with the, my institution button?

David Kaelber:

Definitely. Yeah. So you know, now we have this all, in one forum where, you know, it used to just be the press to get my data. And then the other challenge with that is I would get line level, comma separated variable data. And then I would have to crunch all the numbers myself or I was working with a couple of other medical students at the time. So, and even then when I would say I want the data, it basically just took me to a form to request the data.

So again, and I know you know some about this, but, you know, so from when I had the idea, first of all, I had to write the IRB because again, line level data. So, you know, certainly we're always trying to improve the IRB is and the IRBs are working really hard. But that was a several month process. Then when I pressed the button and filled out the form, that was a several month process to get the line level data and then to analyze the data was another several month process. So we're literally taking, you know, probably close to a year from when I had this idea until I actually had results.

Well, just example for Sara. So first of all, because it's all de-identified. There's no longer any IRB. So the IRB sort of, you know, isn't a factor anymore. There's no concept of needing to request a data set because you can literally through the cosmos user interface, you can literally just look at the variables that you want your analysis to be run on, and then you're getting results. You know, very quickly. So I'll just give you some sense for her project. We went from project idea to submitted abstract. It was in about four weeks. So we took some of those many, many months and now taking it down to weeks.

Craig Jarrett:

That's wonderful. I wanted I wanted to hear another example of research where you've used Cosmos, which is such a powerful tool.

David Kaelber:

Certainly. Yeah. So we we've done a lot now. We, we initially published the first study just talking about the cases that you could the types of research you could do using Cosmos. And then pretty quickly after that, about two years ago, if people remember back through Covid, this is right around the time when Paxlovid came out and Paxlovid, for anybody that might not know, is sort of one of the first medicines that could actually treat Covid if you sort of caught the person early enough, when you knew they were Covid positive and maybe if they had some risk factors that meant they might get sicker from Covid. So, Covid or excuse me, Paxlovid had only been out on the market, for a couple of months, and we wanted to see if there were any disparities in its, prescription. This is particularly of interest to us, you know, as as within our CTSA. You know, one of the things we're really trying to look at is our disparities focus and can we use our sort of research acumen to identify disparities and then try to correct them? So this seemed like a nice target to go after, just to see if this tool that was new to us at that time would help illuminate anything on a new type of treatment that was available in the marketplace.

And so the nice thing is, if you're starting out with hundreds and hundreds of millions of people, even then, if you only have millions and millions that are Covid positive and then even, you know, if thousands or tens of thousands of prescriptions, you can pretty quickly understand how new treatments are being used in the marketplace.

And so we were able to do this relatively quickly. Again, really took on the order of weeks. Unfortunately, what we saw is if you were white, you were more likely to get a Paxlovid prescription, than if you were black. And we tried to risk stratify to make sure we were matching patients appropriately. So I think it was a is a really nice example, sort of an unfortunate example based on the results, but a nice example of showing how we could really quickly identify disparities in new treatments that were available in the marketplace, in this case, a new medication to treat Covid.

Craig Jarrett:

Great. Thank you for that additional story. The CTSA offers a range of resources for collaborators, including mentoring for medical students, connections with peers at �ǿմ�ý School of Medicine and Access and Training and Lyceum. Lyceum is a product created by Epic that introduces medical and nursing students to electronic health records early in their education.

�ǿմ�ý School of Medicine was the first to implement lyceum provided by the DSC in July of 2023. Doctor Kaelber, could you share more about Lyceum and your experiences with it?

David Kaelber:

Sure. Well, just to put it into perspective, right. We realized that people come with very different understandings of informatics. And then they want to do very different things with informatics. So, you know, one of the analogies I use is, maybe it relates to some of the cardiothoracic surgeon is, you know, I think everybody needs to know as a medical student, everybody says something about the heart. You know, some people become cardiothoracic surgeon. Some people, they'll put their stethoscope away after medical school, not use it much. Not much more.

And so Lyceum is part of this continuum. So, you know, previously what was happening not only at Case Western, but a number of other medical schools around the country, is that there was almost zero, training about the electronic health record or training about any sort of informatics competency, even if you didn't use the word informatics. All of that was absent from the first two years of graduate medical education, or the first two years of medical school.

And so what it meant was that when the student started to come into the third year, they really weren't prepared. None of the foundation had been laid for that competency. Again, if we maybe use the physical, diagnosis analogy would be sort of like we wouldn't teach any physical diagnosis in the first two years of medical school, and then we just expect that sort of day one, you could sort of learn physical diagnosis on the fly or, you know, talk to one of your peers. And we just know that that is not equipping medical students the way we should be equipping them into the the 21st century. So for several years, we worked with the Epic Corporation to say what could the corporation do to help with this? And that was really the genesis of Lyceum, which really comes from the Greek, about sort of a learning laboratory.

And so the Epic Corporation created this Lyceum module, which not only gives a whole bunch of bite sized videos, usually a couple minutes to teach people about how to do things in the electronic health record. But it's also really a whole virtual hospital that many students can be looking at the same patient, you know, at the same time without sort of stepping on each other. And it has numerous, virtual patients in there that can, case, scenarios can be wrapped around. So it's really a much, much more robust learning environment for medical students to learn about the electronic health record. We have the second year class now is doing their second year. We've got the first year, last two in their first year. And we hope in the coming years to really be able to evaluate how well Lyceum is, helping again give medical students those basic electronic health record and informatics competencies, even if we're not calling them informatics before they hit their clinical years.

Craig Jarrett:

Well, Lyceum sounds like a great tool I wish I would have had as a medical student. I was fortunate to be in the Lerner College, so we got into the clinics early. But for freestanding medical schools without a university, that would be a great tool.

Is there anything else to CTSC is doing for training of students or fellows or residents?

David Kaelber:

Absolutely. So we really see Lyceum as sort of a pipeline, you know, something like Lyceum, you know, we expect hundreds and hundreds of people to benefit from. But it's sort of like, you know, it covers a broad spectrum but doesn't go too deep. So we have other programs that might cover a smaller spectrum, but go a little bit deeper. So let me explain some of those. So one I would point to is our clinical Informatics fellowship. So this is a two year basically full time fellowship open really to physicians because it's an American board of medical specialties and GME accredited program. We're now basically in about our 10th year. We're one of the first group of health care systems in the country to start a clinical informatics fellowship program accredited by the academy. It started out, really facilitated by the CTSC. And it was just at, the MetroHealth system where we accepted two fellows a year into the two year fellowship.

But the vision from the CTSC had always been, it can't just be a Metro. So, you know, over literally the course of a decade, we've been expanding it. So after being at continues to be at Metro, but then we also added a site at University Hospitals for your based clinically, and then, with this year's recruitment class, we've added two sites at the Cleveland Clinic, as well. So if you do the quick math here, it means that we're offering now five spots per year.

And this actually makes us the largest clinical informatics fellowship program in the country. The second largest only offers three fellowship spots per year. So we're hoping in the coming years we'll have five first year, five second year sort of spread across all three of our sites.

Started out some early discussions. I don't know if University of Toledo eventually will be part of that mix as well, but the structure we've developed, you know, allows for that as well. So we we hope in the coming years we're just going to be, again, the largest site in the country in terms of pumping out, future clinical informatics fellows.

So that's the sort of the physician training pipeline and then within �ǿմ�ý again, really going all the way back to being sponsored through the CTSC. We did not have any formal informatics curriculum, say, a decade ago. So through, Doctor Jonathan Haines, Doctor Satya Saaho, myself, Doctor Singer, we've really now created a robust curriculum at �ǿմ�ý so people can either get a certificate program, which all of our fellows get a certificate in health informatics. Or you can get a master's in biomedical and health informatics, or even a PhD in biomedical and health informatics, which I know you're pursuing, as well. So, so it sort of gives us the full complement of a rigorous academic program where people just want a little sampling of informatics, maybe, and electronic health records through something like Lyceum, all the way to spending many, many years to get a PhD in biomedical and health informatics.

Craig Jarrett:

Wonderful, as a current fellow and a PhD candidate, I am very fortunate to be here. And thankful to the CTSC for starting the spark that that led to all of this. And it's set my trajectory, I think, as a career in clinical decision support, integrating that decision support natively into the electronic health record. So thank you.

I'd like to talk now about networks and other big data research tool that is provided by the CTCS. TriNetX has been recognized as one of the top ten informatics systems for clinical research. And both Cosmos and TriNetX are tools that provide access to de-identified patient data for research purposes.

Could you elaborate on some of the differences between TriNetX and Cosmos, and perhaps examples of when to use cosmos versus TriNetX?

David Kaelber:

Certainly. So, you know, fundamentally they start sort of from the same place. They're both, aggregated electronic health record, platforms. They de-identified the data, they standardize it so that that's the same, where some of that where they start to differ. I already mentioned, Cosmos now is about 275 million people. What we have access to in TriNetX is probably closer to 110, 120 million, patients. So maybe, you know, about half the size. That's one difference. Second difference is that, you know, TriNetX is not just Epic customers. So Cosmos is just Epic customers. So if you're not an Epic customer, you can't contribute to Cosmos.

But you can, to TriNetX. So that's a second difference. A third difference, which to me is very powerful right now for learners, is neither of them required IRB because it's it's really de-identified data. But, TriNetX has a number of built in analytic tools. So, you know, you don't really need a friendly neighborhood statistician or data analyst, sort of. If you have the right question, you can get your, you know, Kaplan-Meier curves or Cox proportions, your hazard risk odds ratio is relative risk P values, confidence intervals. All right out of the TriNetX tool. And you just can't do that at least today to the same degree as Cosmos. So that's another really big difference.

In in theory TriNetX has more international data than it than Cosmos does. Although I sort of tell people I sort of have a good handle on how electronic health records are used in the US. It's very hard for me to know sort of how that underlying data is created in other countries. So I typically recommend staying away from some of the global data, unless there's sort of a very particular need for that.

[BREAK}

McKenzie Ritter:

Hi everyone. I'm McKenzie Ritter, the Assistant Director of Research Education and Training at the CTSC, and I just like to take a few moments to highlight some upcoming education and training programs, as well as some opportunities in the realm of education. So the first is the Advanced Translational Leadership in Academic Science (ATLAS) program. And actually the first cohort has completed the program as of a few months ago. And this cohort focused on mid-career and senior level investigators. We're currently finalizing the second cohort that will focus on early stage investigators. This program seemed to be very successful, so stay tuned for other news about the updates in regards to ATLAS.

Another program that I would like to highlight is Science Cafe, which is a monthly seminar series that aims to increase collaboration by bringing together investigators, trainees, and community members around a common research area. So if you're interested in seeing the full schedule, or if you have a topic that you would like to suggest for a future session, be sure to check out our website.

And then the last event that I would like to highlight is, that we have an upcoming CTSC Research Discovery Day that will take place on March 21st of 2025. This will be in-person at Tinkham Veale. And this is a day that will showcase not only all of the research that, going on within the CTSC, but also our six partnering institutions. So another component of this day is that it will provide local high school students with the opportunity to learn about research, as well as the vast number of careers in clinical research. So if you're interested in either submitting an abstract or volunteering and being involved in the day, be sure to go to the CTSC website and click on the Research Discovery Day tab.

Craig Jarrett:

Can you provide, some examples of how TriNetX has been applied to a translational research project?

David Kaelber:

Certainly. So one of the ones that that made a lot of, popular press and as well as already well cited from earlier this year, these new medicines on the market called, semaglutide is one of them. It's a new type of medicine that a lot of people; used to be they still use a lot for type two diabetes. And a lot of people are using it for, weight loss now. As well. It's an injectable medicine. Millions and millions of people are being prescribed it. And then starting about a year ago now, in the summer of 2023, there started to be concerns of, wow, it seems like some of the people on this medicine are having suicidal ideations or sort of thoughts of suicide.

Obviously, you know, very concerning. FDA and others started to just sort of recognize this. But the important thing here, if you're giving something to millions and millions of people, you know, some of them will have suicidal ideations, some of them have heart attacks, some of them will have colds. It doesn't mean that that that medicine they're on is necessarily causing them.

Although, of course, you know, in the history of the US, we have examples where sometimes medicines do create side effects that weren't understood prior to them going on the market, because you're just not able to test in a large enough population for a long enough period of time. But now we have trained medics, and so we're able to basically conduct a study in, November and December of 2023 looking at the association where we had millions and millions of people on, these semaglutide, medication and what was their, risk or odds of, having a suicidal thought and then really match those to people that weren't on those medicines. And what was their chance of having, suicidal thoughts? And basically what we showed was that, yes, there are people on the medicines that have suicidal thoughts. So those case reports were true. But when you look at the full range of how they're used in the denominator, actually those people did not. That population did not have a disproportionate number of suicides, or suicidal thoughts.

And so what happened then is, you know, we we published this and literally within about a week that the USDA came out with basically a statement saying, hey, don't worry about, you know, suicidal thoughts in the semaglutide medication that the European equivalent to the FDA a couple months later, came out basically with the same statement there. So we didn't talk to the regulators, but in Europe, they actually cited our study as one of the reasons for them to make their decision. So, to me that was very exciting because not only was it good science, but it really helped to shape, public policy, at least in the form of, drug regulation in this space.

So, so we continue to have this very valuable medicine available to lots and lots of people with assurance that it doesn't seem to cause an increase in suicidal thoughts. That's a wonderful study. And I'd just like to reiterate that in this this is a good example of a negative study being published. And so, you know, hypothesis was that there was no difference, in suicidal ideations when patients taking this medications and patients not taking these medications, you found that there was no difference.

Craig Jarrett:

And so it could be thought of as a negative result, which is highly publishable. All right. Yeah. And usually negative results are really hard to publish. But this is one of those cases where again, if there's the right alignment with really a public policy question, then, you know, people are really almost more I mean, they would have been been interested in the positive result too, but they're very interested in the negative result.

So I use TriNetX for our PhD qualifying exam. As you know, the question was to use specifically use TriNetX to answer a research question in your field of study. And so one of the things I thought was interesting, and we have worked on before and other databases, was the increased rate of permanent pacemaker insertion with trans-catheter, aortic valve replacement. So in transcatheter aortic valve replacement we have a valve that pushes out the aortic valve leaflets and puts pressure on the conduction system of the heart. So there is an underlying mechanism for increased permanent pacemaker insertion. And so I wanted to study this using TriNetX. And so for the qualifying exam I found that was very easy to use; we had only a couple weeks right, to answer these questions for the PhD qualifying exam. And I was able to show that indeed, there was an increased rate of permanent pacemaker insertion, with tava, which is kind of well known. It hasn't been shown yet with the TriNetX data and with multiple valves.

So if you add on mitral valve with additional valves, you increase the permanent pacemaker insertion rate. So it's a very easy tool to use. The graphical user interface allows you to get all of the statistical analyzes that Doctor Kaelber already mentioned.

David Kaelber:

Yeah, just to build on all of that, I'll just tell you earlier this week, we just signed up our 500th person as a trained TriNetX user. And most of those users are learners. So medical students, residents, fellows. And, you know, my typical spiel is I can take someone that's never used TriNetX before, sort of give a half hour orientation to them when they set up their account, make sure that account access by the end of the half an hour, tell them to basically do 3 to 4 hours of online self-study videos that are embedded in training. And then they can use the tool. They have enough of sophistication, enough skills then to use the tool after those 3 to 4 hours of of self-study, there's a little bit of, thought and experience that goes into picking the right question. I mean, you have a lot of those skills now, I try to help students, but it's, it's a very quick turnaround.

I'll just give you a sense of, you know, last I did, one orientation is 30 minutes. A week ago Friday. So about ten days ago already earlier this week, there was a medical student is are like, hey, I think I found something. I want to write it up. Can you look at it really quick? I have an abstract I want to submit it to by the end of the week. Now I'm not I'm not necessary. That's typical. But it's just this idea you can take someone from sort of like zero to 60 or 0 to, you know, an abstract, particularly if they're very, engaged, literally can even be in a matter of days.

Craig Jarrett:

As another example of a tool offered by the CTSC, I'd like our listeners to hear about REDCap. So personally, I love REDCap. I use it for every study I do with institutional data. It's easy to sign up the best feature of REDCap is that you get out very clean data. It forces the investigator, the researcher, to enter data in a specific way. And then by default, you get out clean data. Gone are the days of getting Excel spreadsheets with random yeses and no's spelled three different ways. If you use REDCap. So can you elaborate on your REDCap experience?

David Kaelber:

Sure. So, REDCap, just everybody understands the way I sort of describe it. It's sort of like, a HIPAA compliant, database program. But it's really a platform then to. So it really forces, standardization. And it's usually. That's good. You know, all of the, the sites, in the, CSV all use it, I would say for Metro, the one I'm most familiar with, you know, we have literally thousands of users at this point and thousands of studies, you know, over more than a decade. It not only allows research coordinators to, to put in, data as really structured data, all the other things that we have a lot of people are using as the survey tool.

So you can build a survey in REDCap, and then you can basically send that hyperlink to, anybody that you want to participate in the study, and then they can actually be doing the data entry as well. So a lot of our residents, for example, one of the ways that they might do scholarly activity is to build a REDCap survey. And then send that out to folks. So yes, I think it's a it's another very powerful tool. It's different than some of the other tools like trying to use in Cosmos. Another very powerful tool we have in sort of our informatics toolkit that we provide and support through the CTSC. And if you received any correspondence from the CTSC, see specifically for the webinars or the data Thon, those are examples of Redcap surveys.

Craig Jarrett:

So that's that is a great feature as well. Thank you. If a CTSC investigator wants training or access to these systems, how would they gain access?

David Kaelber:

Right. So, hopefully everybody on the the podcast knows about the SPARC system. So that's the formal request system throughout all of the CTSC sites. If somehow you're not familiar with it. The website is, . You should also know, you know, each of the institutions also has CTSC representative, not only in informatics but in other is so anybody at your institution that you think has any, inkling of the CTSC should be able to directly to the, the SPARC system as well.

But that's really the intake system, not only for learning about these tools, but for any other, services and support from the CTSC. And then we routed appropriately based on the nature of the request, either to the right institution, and then the right people within the CTSC in that institution.

Craig Jarrett:

It sounds easy enough. If a potential investigator does not know who to request the root to, how would you suggest proceeding in that scenario?

David Kaelber:

So, you know, one of the things we talk a lot about in informatics is really like a research informatics consult. So, you know, one of the things is, as you know, we talk about the fellowship to, you don't need to come to us with a solution of what you think you need. You know, if you just come to us with the question, we have a lot of expertise to guide you for what the best approach for to be.

So one of the things you can you can request a specific service through the SPARC request system. Or you can basically say, I just need a research informatics consult. So that's basically just sort of raising your hand saying, I need some help, you know, then we'll come help you and then we'll figure out, you know, do you need access to try and help with that?

Craig Jarrett:

What about Cosmos? Maybe it's using some of those, you know, many research, functions within the Epic, module that we talked about.

David Kaelber:

Maybe it's I want to use, some of the new functionality around texting and, personal health record messaging to help with recruitment. So any of those, services we could help direct you to through research informatics, consult through SPARC.

Craig Jarrett:

Great. Does the CTSC have any upcoming events for the informatics module that listeners should know about?

David Kaelber:

I'm so glad you asked, Craig. So, for the first time ever. And we're one of very, very few seats in the country that we are hosting a Cosmos datathon that is going to be an all day event on Saturday, December 7th from 8 a.m. till about 5 p.m. in the Wolstein Building on the �ǿմ�ý campus. We're asking people to, apply for that or register for that. We're going to have people working in teams. So even if you don't know much about Cosmos, that's okay, we're going to be pairing more experienced people with less experienced people. On the teams, we hope to sort of have team themes. So depending on who all comes, we're hoping to group people by like, areas of interest. And, you know, the goal of that is one, hopefully we can actually generate a little bit of science even by the end of the day.

Because eight hours is a lot of time when you're using these tools. And even more than that, we hope to be able to generate partnerships in like areas that hopefully will continue to use Cosmos after the data thon and might lead to other things, potentially grants publications even outside of Cosmos. And we are hoping that this will be the first annual, Cosmos datathon. But it all depends on people like the listeners, signing up and then showing up and learning about Cosmos. And this is the first multi-institutional, Cosmos datathon. There have been a couple of prior datathons, at single institutions. So we look forward to hosting that.

Craig Jarrett:

Well, thank you, Doctor Colbert, for joining us today. It's been a pleasure having you on the podcast.

And for our listeners, don't forget to check out SPARC for training on the systems we discussed today. You can find a link to the SPARC website in the description. As always, we encourage you to become a member of the CTSC. There's no cost to join. This is the best way to stay informed about our events, funding opportunities and research support.

Please visit our website or follow the links in the podcast description. Thank you for tuning in and we'll see you next time on From Research to Real Life.

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