Nurses can benefit from continually strengthening their quantitative skills, whether they’re working in clinical settings or performing research, a new article by College Public Health researchers suggests.
“When armed with appropriate statistical knowledge, nurses can play a unique role in using data to promote health and prevent disease among individuals, communities and populations,” the commentary, in the Journal of Advanced Nursing, concludes. The article is an interdepartmental collaboration by Krista Schroeder, assistant professor of nursing, Levent Dumenci, professor of epidemiology and biostatistics, and David Sarwer, associate dean for research. Other co-authors are David C. Wheeler, associate professor of biostatistics at Virginia Commonwealth School of Medicine, and Matthew J. Hayat, associate professor in epidemiology and biostatistics for the School of Public Health at Georgia State University.
“Healthcare data is getting more complex,” Schroeder explains. “Nurses practicing clinically need to be sophisticated readers of the literature to know how to interpret and apply evidence. They need quantitative literacy for things like medication calculations and other measures that are part of understanding physiology and wellness and sickness.”
Nurse practitioners can benefit from training in statistics in order to improve operations or contribute to scholarship in their fields. “A nurse practitioner is looking at quality improvement work, or systems change work within a practice,” Schroeder explains. And PhD-prepared nurses may need even more expertise in statistical techniques, as they often are involved in designing studies and research that is quantitative in nature, she adds.
The paper suggests that nurses seek out opportunities to improve their statistical knowledge and be ready to reach out for collaborative help from statistical experts when necessary. Having a shared language with biostatisticians helps.
“It’s really important to understand what you don't know,” she says. “It’s easy to forge ahead with inappropriate methods if you don't. Our paper talks a lot about the importance of collaborating with a statistician, talking to them early, and realizing that you both bring a whole set of expertise.”