In February 2015, my editorial focused on issues related to big data in nursing. Featured at the ANA Quality Conference that month, it focused on nursing issues we’d been talking about for years—the importance of documentation, links between nursing and quality care, and the role of the individual nurse in generating patients’ healthcare data. However, gaps exist between what we want to know versus what we need to know.
One year later, are we any closer to bridging these and other data-related gaps? The answer to that question is open to debate, but this month I’d like to address a key part of the big data conversation that still seems somewhat invisible—the need for big-data roles for nurses. I don’t see many, if any, nurse-specific big-data jobs in recruitment ads or job descriptions that clearly define the unique competencies needed for nursing data analytics.
Data science, nursing science: The critical link
The term data scientist, which Harvard Business Review seems to have coined in 2008, refers to a high-ranking professional with the training and curiosity needed to make discoveries in the world of big data. This role is not the same as the nurse informaticist, although nursing informatics is a key foundational knowledge platform for the analytics specialty.
So how do we attract and hire data scientists and, more importantly, use them to advance nursing knowledge and practice? Let’s back up a little to clarify just why we need this nursing role to begin with. To do that, we need to understand the link between data science and nursing science.
Clearly, we need data scientists to communicate in language everyone can easily comprehend—nurse colleagues, medical staff, patients, families, and communities. This special type of communication demands special skills—those that demonstrate the ability to tell stories visually and verbally with data. Some say the most important attribute for a data scientist is an intense curiosity—a desire to go beneath the surface of a problem, explore contributing factors, and connect the dots to make the defining issues easier to understand.
Here’s where nursing science enters the picture: Interest in a particular issue goes far beyond simply “Googling” it to encompassing clinical inquiry aimed at addressing a clinical issue informed by evidence, practice, and professionalism. As the world becomes increasingly digital, we must have nursing-related roles filled by nurses who understand data science.
Why am I worried about this? The demand for data scientists is tremendous. The data scientists already in the field are having a huge impact on industries in this country and across the globe. I see analytics being applied to the care environment without nursing informaticists or nursing data scientists driving decisions. Technology, analytics platforms, and patient data seem to be evolving faster than the human ability to adapt to it.
The result? Fast decisions related to systems and sophisticated analytics—without nursing at the table. The digital doctor is now in place, but where’s the digital nurse and, just as important, the digital nurse leader?
Let’s fix this problem. Doing this will offer an exciting opportunity to promote new nursing roles from the convergence of rich data, integrated analytics innovations, and the ever-demanding needs of patients across the care continuum.
Big data and big-data roles are here to stay. When I wrote “I am data” in this space 1 year ago, I had no idea that in just a year, the concept of nursing data scientists would grow from a whisper to a roar.