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An Applied Healthcare Data Science Roadmap for Nursing Leaders: A Workshop Development, Conceptualization, and
Lisiane Pruinelli1, Steven G Johnson, Brianna Fesenmaier
1Author Affiliations: School of Nursing (Dr Pruinelli, Ms Fesenmaier, and Dr Delaney) and Institute for Health Informatics (Dr Johnson), University of Minnesota, Minneapolis, Minnesota; School of Medicine, University of Kansas Medical Center (Dr Winden), Kansas City; and Kirkhof College of Nursing, Grand Valley State University (Dr Coviak), Grand Rapids, Michigan.
Abstract:
Nurse leaders working with large volumes of interdisciplinary healthcare data are in need of advanced guidance for conducting analytics to improve population outcomes. This article reports the development of a roadmap to help nursing leaders use data science principles and tools to inform decision-making, thus supporting research and approaches in clinical practice that improve healthcare for all. A consensus-building and iterative process was utilized based on the Cross-Industry Standard Process for Data Mining approach to big data science. Using the model, a set of components are described that combine and achieve a process for data science projects applicable to healthcare issues with the potential for improving population health outcomes. The roadmap was tested using a workshop format. The workshop was presented to two audiences: nurse leaders and informatics/healthcare leaders. Results were positive and included suggestions for how to further refine and communicate the roadmap.
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