#MeetUsMonday - Meet PhD student Reanna Panagides
Meet PhD student Reanna.
Devoted green thumb and plant-lover, bee-keeper, and outdoor enthusiast whose nursing began at the outset of COVID, when she worked in UVA Health’s medical ICU and infectious diseases unit. Now a third-year PhD student who recently added a master’s in data science to her growing list of degrees achieved. When not knee-deep in time series data or building machine learning models that just might revolutionize ICU care, she’s paddleboarding, hiking, fishing, or road-tripping to a national park with her girlfriend. Up next? Her dissertation, where she’s diving into over one million time series data points to better understand how critical illness unfolds over time.
HER PATH TO NURSING
“None of my close family or friends were nurses or doctors— but still, I just knew early on that I wanted to make a meaningful difference in the world. Although there are many professions that allow you to help people, nursing stood out because it’s versatile: there are so many ways to be a nurse!
“I started volunteering at a hospital in high school, which solidified my interest in healthcare. During my time as a BSN student, I worked as a patient care tech in the medical ICU for two years, gaining invaluable hands-on experience and confirming that I had found the right fit.”
“Not only do I want to be a part of research that uses routinely collected inpatient data to guide clinical decision-making, but I also want to create space for nurses in the field of data science, as our experience and expertise are invaluable in developing complex machine learning models that truly help inform clinical decisions.”
PhD student Reanna Panagides
HER EARLY NURSING ROLES
“My first nursing role was in the medical and COVID ICUs at UVA Health, where I started in spring of 2020—right in the midst of the pandemic. It was a challenging but incredibly formative experience that shaped the way I view patient care and respond to teamwork under pressure. Later, I worked as a clinical research nurse focused on cardiology-specific studies led both by primary investigators and with industry-sponsored medical device and pharmaceutical trials. This role gave me a deeper appreciation for the research that drives evidence-based practice and ultimately sparked my interest in data-driven innovation. Hence earning a PhD!”
WHY PIVOT INTO NURSING RESEARCH?
“As an ICU nurse, I saw first-hand the power of data in action. I regularly used the CoMET Prediction model—researched by nurse scientist Jessica Keim-Malpass, now my PhD advisor—to analyze real-time medical record data to predict respiratory and cardiovascular instability in ICU patients. It was one of UVA’s first predictive models to be displayed on the unit, and watching it shape clinical decision-making in real time was incredibly inspiring. That experience sparked my passion for data-driven research and innovation, especially when it comes to deriving and integrating clinically meaningful insights from time series data.
“Nurses wear many hats, but one of our most important roles is as data collectors. In a single shift, nurses note physical assessments, medication, and adverse events that evolve day and night—data that builds the very foundation of the medical data used in machine learning models. We intimately understand the context for how these kinds of predictive models can be practically used on the unit, and are uniquely positioned to contribute to and shape predictive technologies.
“Not only do I want to be a part of research that uses routinely collected inpatient data to guide clinical decision-making, but I also want to create space for nurses in the field of data science, as our experience and expertise are invaluable in developing complex machine learning models that truly help inform clinical decisions.”
WHAT SHE’S STUDYING
“My dissertation research focuses on how we process and analyze time-based hospital data—such as vital signs and other physiological markers—to better understand patterns in illness severity over time. I'm using unsupervised machine learning methods to identify these patterns and evaluate how different decisions made during the data preparation and modeling process can influence the results.
“The data I am using for my dissertation is from a clinical trial conducted at UVA (PM-IMPACCT) that collected more than one million time series data points on illness severity over the course of patients’ hospitalization. While my focus is on unsupervised machine learning application to inpatient time series data, I am also more generally interested in how to better use time series data in general to guide clinical practice (e.g. time series forecasting and classification).
“I will soon be proposing my dissertation research and conducting my research over the next year. I’m excited to dive into the data and write papers based on my findings!”
UVA SCHOOL OF NURSING IN A WORD?
“COMMUNITY. This community fosters learning by creating an inclusive and supportive environment. The dedication of the faculty and staff to their students is truly remarkable, and I am grateful to be working alongside such wonderful colleagues.”