Nursing Needs Big Data and Big Data Needs Nursing.
OBJECTIVE
Contemporary big data initiatives in health care will benefit from greater integration with nursing science and nursing practice; in turn, nursing science and nursing practice has much to gain from the data science initiatives. Big data arises secondary to scholarly inquiry (e.g., -omics) and everyday observations like cardiac flow sensors or Twitter feeds. Data science methods that are emerging ensure that these data be leveraged to improve patient care.


METHODS
Big data encompasses data that exceed human comprehension, that exist at a volume unmanageable by standard computer systems, that arrive at a velocity not under the control of the investigator and possess a level of imprecision not found in traditional inquiry. Data science methods are emerging to manage and gain insights from big data.


METHODS
The primary methods included investigation of emerging federal big data initiatives, and exploration of exemplars from nursing informatics research to benchmark where nursing is already poised to participate in the big data revolution. We provide observations and reflections on experiences in the emerging big data initiatives.


CONCLUSIONS
Existing approaches to large data set analysis provide a necessary but not sufficient foundation for nursing to participate in the big data revolution. Nursing's Social Policy Statement guides a principled, ethical perspective on big data and data science. There are implications for basic and advanced practice clinical nurses in practice, for the nurse scientist who collaborates with data scientists, and for the nurse data scientist.


CONCLUSIONS
Big data and data science has the potential to provide greater richness in understanding patient phenomena and in tailoring interventional strategies that are personalized to the patient.
Beta Eta at large, Lillian S. Moehlman-Bascom Professor of Nursing and Industrial Engineering, University of Wisconsin-Madison, Madison, WI, USA.
Patricia Flatley
PF
Brennan
Alpha Eta, The Alumni Professor of Nursing an Professor of Biomedical Informatics, Columbia University, New York, NY, USA.
Suzanne
S
Bakken
D057225:Data Mining; D006801:Humans; D048108:Nursing Informatics / Q000379:methods*; D015399:Nursing Research
Big data; clinical information; data science