Big data using data science methods (data analytics) has the potential to effectively inform strategies to address complex healthcare challenges. However, this potential can only be realized if healthcare professionals have the requisite depth and breadth of knowledge (i.e., informatics competencies). With the emergence of electronic health records (EHRs – commonly known as clinical information systems [CISs]) in healthcare organizations, data analytics that can "interrogate" CIS big data are now possible. In its digitized form, CIS healthcare data meant to support real-time, evidence-based practice decisions and guide new health policy directions remain more of a conceptual promise than a practice reality. Further, the "data rich information poor" phenomenon existing with today's CISs is often the reality for nurses who document more patient information compared to other healthcare professionals and get negligible results in return. However, data science methods when applied to CIS big data are "uncovering" new evidence currently unavailable through traditional data analytic approaches. Big data science is predicted to provide immense opportunities for nurse leaders by offering robust, electronic tools, which support informed decision-making at corporate tables and "arm" all point-of-care/service clinicians with real-time evidence. In this article, we provide a perspective on how the field of data science can enable informatics-savvy nurse executives to lead clinical transformation in the development of the next generation of evidence-based practice, "practice-based evidence."
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