An Applied Healthcare Data Science Roadmap for Nursing Leaders: A Workshop Development, Conceptualization, and Application. Issue 10 (October 2020)

• Record Type: Journal Article
• Authors: Pruinelli, Lisiane; Johnson, Steven G.; Fesenmaier, Brianna; Winden, Tamara J.; Coviak, Cynthia; Delaney, Connie W.
• Is Part Of: Computers, informatics, nursing. Volume 38:Issue 10(2020)
• Publication Date: 2020-10
• Subjects: CRISP-DM -- Data science -- Nurse leaders -- Nursing education -- Nursing informatics; Nursing -- Data processing -- Periodicals; 610.730285
• DOI: 10.1097/CIN.0000000000000607
• Languages: English
• ISSNs: 1538-2931

Abstract

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.