Partnership Innovation to Advance Nursing Practice and Science through Intelligent Informatics

2.50
Hdl Handle:
http://hdl.handle.net/10755/159045
Type:
Presentation
Title:
Partnership Innovation to Advance Nursing Practice and Science through Intelligent Informatics
Abstract:
Partnership Innovation to Advance Nursing Practice and Science through Intelligent Informatics
Conference Sponsor:Midwest Nursing Research Society
Conference Year:2006
Author:Lang, Norma, PhD, RN, FAAN
P.I. Institution Name:University of Wisconsin - Milwaukee
Title:Professor
Contact Address:College of Nursing, P.O. Box 413, Milwaukee, WI, 53201, USA
Contact Telephone:414-229-5469
Co-Authors:Mari E. Akre, PhD, RN, Assistant Professor; Mary Hook, MS, RN, Predoctoral Student; Amy Coenen, PhD, RN, FAAN, Associate Professor; Tae Youn Kim, PhD, RN, Post Doctoral Fellow; and Mary Hagle, PhD, RN, AOCN
The ACW "Knowledge Based Nursing" Initiative (KBNI) is a partnership between three major sectors: nursing academia, health care delivery system and industry informatics with a shared vision: to accelerate the use of knowledge and evidence through intelligent technology. Variation in the quality of nursing care across countries, clinical settings, and populations is widely recognized. The ACW-KBNI seeks to identify nursing based evidence and translate to practice with the use of computerized decision support and clinical information systems. KBNI defines and improves nurses' contribution to healthcare outcomes using intelligent clinical information systems.

The KBNI established a conceptual framework for the translation of knowledge into practice. This process selects nursing phenomenon of concern across the spectrum of health conditions. Medication adherence and activity tolerance were the first phenomenon to test a proof of concept, using a structured and consistently applied process of searching, analyzing, ranking and synthesizing referential evidence. Evidence is embedded into practice using intelligent information systems logic that provides state of the art clinical decision support to nurses at the point of care. Nursing assessment, diagnosis/problem identification, intervention and outcome data are coded in standardized terminologies using a combination of SNOMED CT and International Classification of Nursing Practice (ICNP). Clinical care is coded and retrievable within the clinical data repository and data warehouse. Analyses such as data mining techniques will facilitate the description and evaluation of nursing practice across multiple types of patients, care settings, and caregiver variables. New knowledge generation opportunities are numerous as well as contributing to the international nursing initiatives such as the International Nursing Minimum Data Set. This innovative partnership is creating a robust, accelerated process that will move evidence into practice, improve outcomes and generate new knowledge.
Repository Posting Date:
26-Oct-2011
Date of Publication:
17-Oct-2011
Sponsors:
Midwest Nursing Research Society

Full metadata record

DC FieldValue Language
dc.typePresentationen_GB
dc.titlePartnership Innovation to Advance Nursing Practice and Science through Intelligent Informaticsen_GB
dc.identifier.urihttp://hdl.handle.net/10755/159045-
dc.description.abstract<table><tr><td colspan="2" class="item-title">Partnership Innovation to Advance Nursing Practice and Science through Intelligent Informatics</td></tr><tr class="item-sponsor"><td class="label">Conference Sponsor:</td><td class="value">Midwest Nursing Research Society</td></tr><tr class="item-year"><td class="label">Conference Year:</td><td class="value">2006</td></tr><tr class="item-author"><td class="label">Author:</td><td class="value">Lang, Norma, PhD, RN, FAAN</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">University of Wisconsin - Milwaukee</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">Professor</td></tr><tr class="item-address"><td class="label">Contact Address:</td><td class="value">College of Nursing, P.O. Box 413, Milwaukee, WI, 53201, USA</td></tr><tr class="item-phone"><td class="label">Contact Telephone:</td><td class="value">414-229-5469</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">nlang@uwm.edu</td></tr><tr class="item-co-authors"><td class="label">Co-Authors:</td><td class="value">Mari E. Akre, PhD, RN, Assistant Professor; Mary Hook, MS, RN, Predoctoral Student; Amy Coenen, PhD, RN, FAAN, Associate Professor; Tae Youn Kim, PhD, RN, Post Doctoral Fellow; and Mary Hagle, PhD, RN, AOCN</td></tr><tr><td colspan="2" class="item-abstract">The ACW &quot;Knowledge Based Nursing&quot; Initiative (KBNI) is a partnership between three major sectors: nursing academia, health care delivery system and industry informatics with a shared vision: to accelerate the use of knowledge and evidence through intelligent technology. Variation in the quality of nursing care across countries, clinical settings, and populations is widely recognized. The ACW-KBNI seeks to identify nursing based evidence and translate to practice with the use of computerized decision support and clinical information systems. KBNI defines and improves nurses' contribution to healthcare outcomes using intelligent clinical information systems. <br/><br/>The KBNI established a conceptual framework for the translation of knowledge into practice. This process selects nursing phenomenon of concern across the spectrum of health conditions. Medication adherence and activity tolerance were the first phenomenon to test a proof of concept, using a structured and consistently applied process of searching, analyzing, ranking and synthesizing referential evidence. Evidence is embedded into practice using intelligent information systems logic that provides state of the art clinical decision support to nurses at the point of care. Nursing assessment, diagnosis/problem identification, intervention and outcome data are coded in standardized terminologies using a combination of SNOMED CT and International Classification of Nursing Practice (ICNP). Clinical care is coded and retrievable within the clinical data repository and data warehouse. Analyses such as data mining techniques will facilitate the description and evaluation of nursing practice across multiple types of patients, care settings, and caregiver variables. New knowledge generation opportunities are numerous as well as contributing to the international nursing initiatives such as the International Nursing Minimum Data Set. This innovative partnership is creating a robust, accelerated process that will move evidence into practice, improve outcomes and generate new knowledge.</td></tr></table>en_GB
dc.date.available2011-10-26T21:38:57Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T21:38:57Z-
dc.description.sponsorshipMidwest Nursing Research Societyen_GB
All Items in this repository are protected by copyright, with all rights reserved, unless otherwise indicated.