Big Data: Why Should Canadian Nurse Leaders Care?
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...
| Published in: | Nursing Leadership (1910-622X) Vol. 32; no. 2; pp. 19 - 31 |
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| Main Authors: | , |
| Format: | review Journal Article |
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Longwoods Publishing
2019
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=139178561&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 139178561 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1910622X B8WH jtl: Nursing Leadership (1910-622X) issn: 1910622X maglogo: N pubinfo: dt: 2019 vid: 32 iid: 2 pid: 20495 pub: Longwoods Publishing place: Toronto, Ontario artinfo: ui: 139178561 139178561 139178561 10.12927/cjnl.2019.25964 139178561 ppf: 19 ppct: 12 formats: fmt: @attributes: type: P tig: atl: Big Data: Why Should Canadian Nurse Leaders Care? aug: au: Remus, Sally Donelle, Lorie affil: Western University, Arthur Labatt Family School of Nursing, London, ON sug: subj: Nursing Leaders Canada Electronic Health Records Documentation Data Analytics Canada Decision Support Systems, Clinical Nursing Practice, Evidence-Based Data Science Methods Informatics Computer Literacy Data Science Trends ab: 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." pubtype: Academic Journal doctype: review Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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