2.50
Hdl Handle:
http://hdl.handle.net/10755/155292
Type:
Presentation
Title:
Knowledge-Based Nursing Initiative: Translating Evidence into Practice
Abstract:
Knowledge-Based Nursing Initiative: Translating Evidence into Practice
Conference Sponsor:Sigma Theta Tau International
Conference Year:2007
Author:Swan, Beth Ann, PhD, CRNP, FAAN
P.I. Institution Name:Thomas Jefferson University, Jefferson College of Health Professions
Title:Associate Professor, Associate Dean Graduate Program
Co-Authors:Norma M. Lang, PhD, RN, FAAN, FRCN; Elizabeth C. Devine, PhD, RN, FAAN; Amy Coenen, PhD; Tae Youn Kim, PhD, RN and Mary Hagle, PhD, RN
[Research Presentation] The "Knowledge-Based Nursing" Initiative (KBNI) is a leading edge partnership among Aurora Health Care, Cerner Corporation, and University of Wisconsin-Milwaukee College of Nursing (ACW) to accelerate and expand the use of knowledge and evidence in nursing practice through intelligent technology. Variation in the quality of nursing care across countries, clinical settings, and populations is widely recognized.á KNBI identifies, defines, facilitates and improves nurses' direct contributions to patient outcomes through the enhanced use of evidence based clinical care using intelligent clinical information systems. This Initiative uses a structured process for knowledge discovery that defines criteria for a phenomenon of concern (POC), search, analysis, evaluation, and synthesis of referential evidence. Evidence is gathered from a variety of sources and translated into specific patient assessments, nursing judgments/diagnosis about the problem, nursing interventions and outcomes. The evidence is then synthesized into referential recommendations. This referential knowledge is then translated into action items for practice. The action items are then embedded into the workflow of the clinical information systems application structure that provides decision support to nurses at the point of care. This presentation will describe and discuss each step in the structured knowledge discovery process using the phenomenon of concern - risk for delirium - as an exemplar from referential evidence to actionable decisions by nurses at the point of care. Evidence about risk for delirium related to: 1) patient assessment of risk for delirium, 2) problem identification of risk for delirium, 3) nursing interventions for risk for delirium, and 4) nurse-sensitive outcomes of risk for delirium have been translated and embedded in a clinical information system at the point of care.
Repository Posting Date:
26-Oct-2011
Date of Publication:
17-Oct-2011
Sponsors:
Sigma Theta Tau International

Full metadata record

DC FieldValue Language
dc.typePresentationen_GB
dc.titleKnowledge-Based Nursing Initiative: Translating Evidence into Practiceen_GB
dc.identifier.urihttp://hdl.handle.net/10755/155292-
dc.description.abstract<table><tr><td colspan="2" class="item-title">Knowledge-Based Nursing Initiative: Translating Evidence into Practice</td></tr><tr class="item-sponsor"><td class="label">Conference Sponsor:</td><td class="value">Sigma Theta Tau International</td></tr><tr class="item-year"><td class="label">Conference Year:</td><td class="value">2007</td></tr><tr class="item-author"><td class="label">Author:</td><td class="value">Swan, Beth Ann, PhD, CRNP, FAAN</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">Thomas Jefferson University, Jefferson College of Health Professions</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">Associate Professor, Associate Dean Graduate Program</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">beth.swan@jefferson.edu</td></tr><tr class="item-co-authors"><td class="label">Co-Authors:</td><td class="value">Norma M. Lang, PhD, RN, FAAN, FRCN; Elizabeth C. Devine, PhD, RN, FAAN; Amy Coenen, PhD; Tae Youn Kim, PhD, RN and Mary Hagle, PhD, RN</td></tr><tr><td colspan="2" class="item-abstract">[Research Presentation] The &quot;Knowledge-Based Nursing&quot; Initiative (KBNI) is a leading edge partnership among Aurora Health Care, Cerner Corporation, and University of Wisconsin-Milwaukee College of Nursing (ACW) to accelerate and expand the use of knowledge and evidence in nursing practice through intelligent technology. Variation in the quality of nursing care across countries, clinical settings, and populations is widely recognized.&aacute; KNBI identifies, defines, facilitates and improves nurses' direct contributions to patient outcomes through the enhanced use of evidence based clinical care using intelligent clinical information systems. This Initiative uses a structured process for knowledge discovery that defines criteria for a phenomenon of concern (POC), search, analysis, evaluation, and synthesis of referential evidence. Evidence is gathered from a variety of sources and translated into specific patient assessments, nursing judgments/diagnosis about the problem, nursing interventions and outcomes. The evidence is then synthesized into referential recommendations. This referential knowledge is then translated into action items for practice. The action items are then embedded into the workflow of the clinical information systems application structure that provides decision support to nurses at the point of care. This presentation will describe and discuss each step in the structured knowledge discovery process using the phenomenon of concern - risk for delirium - as an exemplar from referential evidence to actionable decisions by nurses at the point of care. Evidence about risk for delirium related to: 1) patient assessment of risk for delirium, 2) problem identification of risk for delirium, 3) nursing interventions for risk for delirium, and 4) nurse-sensitive outcomes of risk for delirium have been translated and embedded in a clinical information system at the point of care.</td></tr></table>en_GB
dc.date.available2011-10-26T13:42:39Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T13:42:39Z-
dc.description.sponsorshipSigma Theta Tau Internationalen_GB
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