Uncovering, Evaluating, and Assimilating Evidence: A Model for Decision Support Systems

2.50
Hdl Handle:
http://hdl.handle.net/10755/150286
Type:
Presentation
Title:
Uncovering, Evaluating, and Assimilating Evidence: A Model for Decision Support Systems
Abstract:
Uncovering, Evaluating, and Assimilating Evidence: A Model for Decision Support Systems
Conference Sponsor:Sigma Theta Tau International
Conference Year:2003
Author:Dluhy, Nancy M., RN, PhD
P.I. Institution Name:University of MA-Dartmouth
Title:Professor
Co-Authors:Eileen S. O'Neill, RN, PhD
Developers of Clinical Decision Support Systems (CDSS) must devise efficient ways to translate knowledge to practice as the debate continues over the best evidence to guide nursing practice. Most existing technology uses either textbooks or clinical guidelines as a support base for determining diagnoses and interventions. But is this adequate? When nurses are relying on a computerized system to assist them when making critical decisions, what evidence should be used to develop and maintain the system? In addition to developing a strategy to locate the best evidence to answer clinical questions, decisions are needed for “gray zones of nursing practice” where answers are not apparent. Although randomized clinical trials are often considered the “gold standard” of evidence-based medical practice, they are inadequate in reflecting the complexities of nursing practice. Professional knowledge for nursing includes not only an understanding of the scientific basis for practice, but also a thorough grasp of the contextual and relational issues. This paper presents a comprehensive process model addressing these issues. The model outlines a procedure to uncover, evaluate and assimilate information to develop the knowledge domain for N-CODES (Novice Computer Decision Support System). Both formal and practice-based knowledge are included. A formula determines scientific confidence levels based on the collective of different types of evidence. The model contains several innovative approaches including the use of clinical experts and a network of practicing clinicians. This model will assist scientists and practitioners interested in determining the best evidence to support nursing practice.
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.titleUncovering, Evaluating, and Assimilating Evidence: A Model for Decision Support Systemsen_GB
dc.identifier.urihttp://hdl.handle.net/10755/150286-
dc.description.abstract<table><tr><td colspan="2" class="item-title">Uncovering, Evaluating, and Assimilating Evidence: A Model for Decision Support Systems</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">2003</td></tr><tr class="item-author"><td class="label">Author:</td><td class="value">Dluhy, Nancy M., RN, PhD</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">University of MA-Dartmouth</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">Professor</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">ndluhy@umassd.edu</td></tr><tr class="item-co-authors"><td class="label">Co-Authors:</td><td class="value">Eileen S. O'Neill, RN, PhD</td></tr><tr><td colspan="2" class="item-abstract">Developers of Clinical Decision Support Systems (CDSS) must devise efficient ways to translate knowledge to practice as the debate continues over the best evidence to guide nursing practice. Most existing technology uses either textbooks or clinical guidelines as a support base for determining diagnoses and interventions. But is this adequate? When nurses are relying on a computerized system to assist them when making critical decisions, what evidence should be used to develop and maintain the system? In addition to developing a strategy to locate the best evidence to answer clinical questions, decisions are needed for &ldquo;gray zones of nursing practice&rdquo; where answers are not apparent. Although randomized clinical trials are often considered the &ldquo;gold standard&rdquo; of evidence-based medical practice, they are inadequate in reflecting the complexities of nursing practice. Professional knowledge for nursing includes not only an understanding of the scientific basis for practice, but also a thorough grasp of the contextual and relational issues. This paper presents a comprehensive process model addressing these issues. The model outlines a procedure to uncover, evaluate and assimilate information to develop the knowledge domain for N-CODES (Novice Computer Decision Support System). Both formal and practice-based knowledge are included. A formula determines scientific confidence levels based on the collective of different types of evidence. The model contains several innovative approaches including the use of clinical experts and a network of practicing clinicians. This model will assist scientists and practitioners interested in determining the best evidence to support nursing practice.</td></tr></table>en_GB
dc.date.available2011-10-26T10:20:48Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T10:20:48Z-
dc.description.sponsorshipSigma Theta Tau Internationalen_GB
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