5 Key Things Nurses Need to Know About Data Science

 

Think of a typical day in your practice area. In just a few minutes, you might record a patient’s blood sugar, log their medication dosage, take their vital signs, and make notes in their chart. Each of these steps generates data.

Massive and complex data sets, like the ones that flow from healthcare systems, are known as “big data.” Whereas traditional data might fit neatly into columns on a spreadsheet, big data comes from diverse sources like connected medical devices, mobile apps, electronic health records (EHRs), and even social media feeds. We need advanced computer systems to manage and make sense of big data.

Today, nurses are increasingly generating and relying on big data in their work. As an influential 2015 study published in the Journal of Nursing Scholarship put it: “Nursing Needs Big Data and Big Data Needs Nursing.”

Emory School of Nursing and Nurse.org have teamed up to host a series of podcasts on the often-overlooked skillsets that today’s nurses need to thrive. Tune into this episode to understand data science, including how to use it to improve patient care.

Data science defined

“Data science provides the tools and methods we need to analyze and make sense of big data, helping to uncover patterns and insights,” says Jane Chung, PhD, RN, FGSA, a nurse scientist and associate professor at the Nell Hodgson Woodruff School of Nursing at Emory University in Atlanta, whose research focuses on leveraging technology to promote independent living among older adults.

With data science, we can look at cause-and-effect patterns at the levels of systems or populations. Those insights can help us streamline clinical processes, reduce healthcare costs, and improve patient outcomes.

“We can also use data to generate evidence that can drive changes in policy,” says Jacqueline Nikpour, PhD, RN, an assistant professor at Emory School of Nursing and a researcher who studies models of nursing care in primary care and other community-based settings. For example, large-scale data on the supply and demand of nurses across various specialties and geographic areas can inform policy decisions and appropriations to support workforce planning.

As healthcare becomes more reliant on digital tools, it becomes more important for nurses to not only know how to generate big data (such as via charting) but also how to use it for the betterment of patient care. “Data analytics or informatics knowledge is one of the core things that you should know as a nurse, a nurse scientist, or a nurse leader,” says Dr. Chung.

If you’re allergic to tech, not to worry. There are opportunities for any nurse to become more data savvy.

You can learn data science in nursing school (and even outside the classroom)

While more and more nursing schools are providing instruction in data science (such as Emory’s Center for Data Science), the bulk of such teaching takes place at the graduate level. If you didn’t get data science training during your undergraduate nursing education, you’re not alone.

“I don't recall in nursing school ever having a class about data science or informatics that would make it feel tangible in my day-to-day as a clinician,” says Raquél Pérez, BSN, RN, a health-tech executive, former NICU nurse, and a host of Nurse.org’s Nurse Converse podcast.

If you’re currently in school and your courses don't include data science, there may still be ways to learn about it through your institution.

“No matter what kind of degree program you're in, there are opportunities,” says Dr. Nikpour. “Go to a professor you trust and say, ‘Hey, I think I might be interested in learning more about data science. Is there someone I can just talk to about what this would look like?’” Signing up for special projects as a research assistant can also give you exposure to data science, she adds.

You can learn data science on the job, too

Already graduated? There are ways to learn data science at work.

“If you’re a nurse practicing at the bedside, a lot of hospitals or health systems will have what’s called a nurse scientist,” says Dr. Nikpour. This may be a member of the hospital staff or a dual role with a hospital and nursing school. In many cases, the job of the nurse scientist is to work with nurses who have research interests and who are looking to develop scientific questions.

Think about the problems you face every day in practice and how to position these problems as research questions that draw on clinical data as part of the solution. “For example, how can we predict people who are at risk for developing sepsis or a central line infection?” Dr. Nikpour says. “If that's something that you're interested in, ask your manager if there is a nurse scientist at your hospital and see if you can schedule an appointment.”

Meanwhile, nursing schools are launching programs for nurses to learn more about data science. Emory’s Project NeLL, for example, allows students and practicing nurses across the United States to learn about and get hands-on experience with big data.

AI can be a powerful partner

You might have heard about how artificial intelligence (AI) is disrupting various industries, and nursing is no exception. That’s why it’s so important for nurses to play an active role in designing responsible AI that can help nurses and patients. For example, if you learn data science, you may find it useful to learn how to train and personalize AI models.

Drs. Nikpour and Chung acknowledge the fear that many nurses have about how AI might impact the security of nursing work. Says Dr. Nikpour: “You cannot replace the clinical judgement that comes with having a nurse who is able to look at and put their hands on a patient who is right in front of them.”

Rather, AI can help with rote tasks that nurses perform every day that get in the way of spending quality time with patients, such as charting. One 2024 study published in the Journal of Emergency Nursing noted that nurses spent 27 percent of their time on electronic health record tasks, compared to 25 percent on direct patient care. If a computer, which doesn’t get fatigued after a long day, could take up some of that administrative work, a human nurse could devote more time to taking care of patients.

Nurses can co-create data systems

Digital systems that don’t make sense to nurses have no place in the clinical setting. “Some of the tools that are designed to supposedly improve patient care are made without the end user in mind. And really, the end users in a lot of these cases are nurses,” says Dr. Nikpour.

If systems developers have no idea how a product is being used in real life, it will end up just being a waste of time and money, she adds. Either nurses won’t leverage it or it will contribute to negative feelings about technology.

The solution is for nurses to become more involved in the design of these products. “I frequently hear of data scientists looking actively for nurses to help them think about problems they're interested in solving,” says Dr. Nikpour.

Adds Dr. Chung: “Nurses have a wealth of knowledge and insights about clinical problems. Those are things we can bring to the table to start something innovative and creative.”

🤔Nurses, what challenges do you face when using digital tools or EHR systems? Share your thoughts in the discussion forum below!