Reasoning Into the Future: Complexity Thinking and The OPT Model of Clinical Reasoning

2.50
Hdl Handle:
http://hdl.handle.net/10755/152150
Type:
Presentation
Title:
Reasoning Into the Future: Complexity Thinking and The OPT Model of Clinical Reasoning
Abstract:
Reasoning Into the Future: Complexity Thinking and The OPT Model of Clinical Reasoning
Conference Sponsor:Sigma Theta Tau International
Conference Year:2007
Author:Pesut, Daniel J., PhD, APRN, BC, FAAN
P.I. Institution Name:Indiana University School of Nursing
Title:Chair, Professor
Co-Authors:RuthAnne Kuiper, RN, PhD
[Symposium Presentation] As the health care industry shifts to an outcomes orientation and embraces electronic medical and health records, the nursing process and nursesÆ clinical reasoning are likely to change and evolve. Contemporary trends and forces suggest that another transformation of the process is needed. Contemporary nursing practice, with its focus on outcomes and on the complex analysis of multiple client conditions, requires critical, creative, systems, and complexity thinking. Nursing classification systems and taxonomies provide the clinical vocabulary for clinical reasoning in nursing. The OPT model provides structure for embracing the nursing knowledge work of the past thirty years. It is a structure that supports clinical thinking about relationships among nursing diagnoses, interventions, and outcomes. The continued evolution and development of nursing knowledge classification systems, as well as continued research into the dynamics of clinical reasoning, set the stage for further developments in nursing knowledge work. Clinical reasoning regardless of discipline is both science and art. Edward Tufte (2006) in his book, Beautiful Evidence, suggests the common analytic task in nearly all disciplines is to help people understand causality, make multivariate comparisons, examine relevant evidence and assess the credibility of evidence and conclusions. OPT is a meta- model of clinical reasoning that requires clinicians áto consider many problems at the same time, and discern which problem or issue is most important. As information systems and electronic medical records provide ways for nurses to capture data related to diagnoses, interventions, and outcomes, there will certainly be ways to discover and mine the data associated with nursing knowledge that is embedded in health-related information technology systems. Such data mining activities contribute to our knowledge building and modeling and will support the nursing work of the future.
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.titleReasoning Into the Future: Complexity Thinking and The OPT Model of Clinical Reasoningen_GB
dc.identifier.urihttp://hdl.handle.net/10755/152150-
dc.description.abstract<table><tr><td colspan="2" class="item-title">Reasoning Into the Future: Complexity Thinking and The OPT Model of Clinical Reasoning</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">Pesut, Daniel J., PhD, APRN, BC, FAAN</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">Indiana University School of Nursing</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">Chair, Professor</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">dpesut@iupui.edu</td></tr><tr class="item-co-authors"><td class="label">Co-Authors:</td><td class="value">RuthAnne Kuiper, RN, PhD</td></tr><tr><td colspan="2" class="item-abstract">[Symposium Presentation] As the health care industry shifts to an outcomes orientation and embraces electronic medical and health records, the nursing process and nurses&AElig; clinical reasoning are likely to change and evolve. Contemporary trends and forces suggest that another transformation of the process is needed. Contemporary nursing practice, with its focus on outcomes and on the complex analysis of multiple client conditions, requires critical, creative, systems, and complexity thinking. Nursing classification systems and taxonomies provide the clinical vocabulary for clinical reasoning in nursing. The OPT model provides structure for embracing the nursing knowledge work of the past thirty years. It is a structure that supports clinical thinking about relationships among nursing diagnoses, interventions, and outcomes. The continued evolution and development of nursing knowledge classification systems, as well as continued research into the dynamics of clinical reasoning, set the stage for further developments in nursing knowledge work. Clinical reasoning regardless of discipline is both science and art. Edward Tufte (2006) in his book, Beautiful Evidence, suggests the common analytic task in nearly all disciplines is to help people understand causality, make multivariate comparisons, examine relevant evidence and assess the credibility of evidence and conclusions. OPT is a meta- model of clinical reasoning that requires clinicians &aacute;to consider many problems at the same time, and discern which problem or issue is most important. As information systems and electronic medical records provide ways for nurses to capture data related to diagnoses, interventions, and outcomes, there will certainly be ways to discover and mine the data associated with nursing knowledge that is embedded in health-related information technology systems. Such data mining activities contribute to our knowledge building and modeling and will support the nursing work of the future.</td></tr></table>en_GB
dc.date.available2011-10-26T11:25:48Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T11:25:48Z-
dc.description.sponsorshipSigma Theta Tau Internationalen_GB
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