 It's time for nurses to learn R. My name is Jacqueline Janis, and I currently work on the customer success team at RStudio, specifically with our customers in life sciences and healthcare who are putting our professional products to use. I'm really excited to speak with you today about why I think nurses should learn R. It's a topic that I've been thinking about for a long time, and I hope that these reflections will spark some conversation, some networking, and ultimately greater engagement between the R community and nursing. And I wanna be clear from the start about what this talk isn't. I'm not calling upon nurses to leave the bedside and pursue data science skills. So first, a little bit about why I spend so much time thinking about how nurses might improve their interactions with data. So I am a nurse, and I spent the greater part of a decade working clinically. My first job was in a family planning clinic, and then I moved on to labor and delivery for a few years, and then I spent four years across the medical ICU, surgical ICU, and some cardiothoracic ICU. And I also worked as part-time faculty in a School of Nursing, teaching in the simulation lab and leading acute care clinical rotations. And toward the end of these years, I was tremendously burned out, and that was pre-COVID. So I began coursework for a Master's in Public Health and I charted an exit, though I had the hope of keeping one foot in the clinical world going forward. And during my coursework, while still working at the bedside, I began to have this vague idea that I wanted to do something with data. And there was actually a vivid moment for me. It was on a night shift in the surgical ICU. The lights are turned down, the nine o'clock meds have been passed. And in a conversation, someone mentioned that one of our critical care docs does her own analyses for her research, writing her own code in R. And as simple as that, for me, the seed was planted. I actually didn't know what that meant. I didn't even know what R was, but I was really intrigued. And so eventually I enrolled in a data management and analytics course and a data-vis course, both based in R. And at that point, I had already been using SAS for research assistantship. So I already knew the benefit of writing code to do my analyses, but R was very different. R was fun, it was versatile. And in a lot of ways, for me, it was just much easier to learn. And then there's that satisfaction of successfully running a code chunk in an R markdown, seeing the green bar complete and watching your plot appear. It's a nice dose of dopamine, don't you think? So then I took a job as a data analyst in a health outcomes research shop within the research arm of a large health system. And I even tried to stay per diem as a nurse, but the combination of the two positions would not have been possible without sacrifices to my compensation and benefits. So I chose to leave the per diem position behind. And then I got to work in R on a daily basis for health outcomes and environmental health research topics. And I also led my institution's R user group. But all the while, I was picturing what I might have done with these data skills if I was still working at the bedside. And so I started asking, are there already nurses out there doing this? And I began to dig around for evidence of an existing connection between the R community and nursing. And I was surprised to find only a little. And what I found was this, that within nursing, there's generally an acknowledgement that nurses should have basic data analysis skills. But I think we need to flesh out this call a little bit. What skills, what are we talking about? What's the use case? What are the tools to achieve that? I also found beginning discussions about nurses involvement in data science, specifically stressing potential roles with big data and AI. And I think that nurses may have integral roles with data science going forward, but I do think there's a lot more opportunity for nurses right in front of our faces with small data before we're getting into the predictive analytics and how to use that model at the bedside. I also found a lot of pointing nurses to the field of nursing informatics in order to pursue data skill sets. And I think this is helpful. I think nursing informatics is a good place to point to for this. And I think this discipline is gonna be a tremendous help in pulling these worlds together. But my take on this is that nurses shouldn't really be called upon to necessarily get another degree and pursue an alternate career in order to make good use of data today. So I can't help but come to the conclusion that it's time for nurses to learn R. But why nurses? And it's super simple. Nurses are already using data. They're using data on key performance indicators, staffing data, they're looking at quality metrics and of course they're doing research. And the tools that they're using to work with the data today include a lot of Excel and even some paper. And I know that there must be teams out there that are doing this in a streamlined way in other platforms. But this is what I witnessed in my years of nursing. So I wanna think about what if clinical nurses had foundational data skills? What might we see? I think about what's coming in, what we're capturing. Nurses are putting such a vast amount of data into the EHR, each shift. What would happen to the quality of that data? What else might we capture? What other questions would we be asking and addressing? With more eyes on the issues and the skills to dig into them, what other outcomes could be improved more rapidly? And what would happen when we empower nurses to ask more questions and invest greater in the improvement of their clinical settings? Would they stay in their clinical roles? If they can have some effect on the things that they're seeing every day that are not working. So it's time for nurses to learn R, but why R and why now? R is free, open source with a large rapidly growing community that is welcoming and helpful. The tools are evolving and improving at a rapid pace. It's a good time to jump in. There is a steep learning curve. There's this reputation of that. I experienced that, but increasingly more developments are removing hurdles to learning and making that learning curve of especially particular elements a little less steep. So particularly with the advent of Corto, a home for both analyses and various means of communicating results. It's a good time to jump in. Other developments like the Shiny UI Editor make it easier to get from idea to execution with your Shiny apps. And education is evolving and ever improving with things like RStudio Academy to build foundational data science skills. And there's a lot of materials already out there geared towards people in the biomedical science and geared towards nurses included. But what's it to you? For those in the audience working in research, data analytics, data science, in health systems and clinical settings, I want you to consider engaging with more nurses. This might mean identifying those nurses who are working with data today and seeing how you might partner with them. And I'd also like you to consider if there are opportunities where you can facilitate nurses equipping themselves with additional skills. To the nurses working on Excel and on paper, I'm reluctant to ask you to do one more thing. I know what it's like to perpetually have one more thing added to your plate and nothing taken away. But I want you to consider how you're using data today, no matter how small. And I want you to know that there are tools out there that could save you time and effort and generate way more insights in the end. And you might even have some fun along the way. And to the nurses already using R, please reach out. I'd love to hear about your work and discuss ways to propagate the use of R in our studio across our profession. So there are already paths to learning and using R that ultimately lead nurses away from the bedside. And that's the route that I pursued. It's where the momentum carried me. But what if nurses were equipped and supported in the clinical setting to ask more questions, drive change, and improve outcomes? Having the right tools for the job is one small part of this, but it's an important part. So it's night shift. The lights are turned down. The nine o'clock meds are given. Let's get nurses talking about R. And also please don't sit on the floor of the hospital. No one ever does this. This was the best picture I could find to illustrate my point. Thanks. And let's keep in touch. Thank you so much for your time.