Nursing Knowledge: Big Data Science-Implications for Nurse Leaders.


The integration of Big Data from electronic health records and other information systems within and across health care enterprises provides an opportunity to develop actionable predictive models that can increase the confidence of nursing leaders' decisions to improve patient outcomes and safety and control costs. As health care shifts to the community, mobile health applications add to the Big Data available. There is an evolving national action plan that includes nursing data in Big Data science, spearheaded by the University of Minnesota School of Nursing. For the past 3 years, diverse stakeholders from practice, industry, education, research, and professional organizations have collaborated through the "Nursing Knowledge: Big Data Science" conferences to create and act on recommendations for inclusion of nursing data, integrated with patient-generated, interprofessional, and contextual data. It is critical for nursing leaders to understand the value of Big Data science and the ways to standardize data and workflow processes to take advantage of newer cutting edge analytics to support analytic methods to control costs and improve patient quality and safety.

DOI: 10.1097/NAQ.0000000000000130
Citations per Year

54 Citations

Semantic Scholar estimates that this publication has 54 citations based on the available data.

See our FAQ for additional information.

Cite this paper

@article{Westra2015NursingKB, title={Nursing Knowledge: Big Data Science-Implications for Nurse Leaders.}, author={Bonnie L. Westra and Thomas R. Clancy and Joyce Sensmeier and Judith J. Warren and Charlotte A. Weaver and Connie White Delaney}, journal={Nursing administration quarterly}, year={2015}, volume={39 4}, pages={304-10} }