• Bonnie L Westra, Thomas R Clancy, Joyce Sensmeier, Judith J Warren, Charlotte Weaver, and Connie W Delaney.
• School of Nursing, University of Minnesota, Minneapolis (Dr Westra); School of Nursing, University of Minnesota, Minneapolis (Dr Clancy); Health Information Management Systems Society, Chicago, Illinois (Ms Sensmeier); School of Nursing, The University of Kansas, Lawrence, and Warren & Associates, LLC, Plattsmouth, Nebraska (Dr Warren); School of Nursing, University of Minnesota, Minneapolis (Dr Delaney); and Healthcare Executive and Board Member (Dr Weaver).
• Nurs Adm Q. 2015 Oct 1; 39 (4): 304-10.

AbstractThe 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.

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