2.50
Hdl Handle:
http://hdl.handle.net/10755/151235
Type:
Presentation
Title:
Collaboration: A Transdisciplinary Roadmap to Discovery
Abstract:
Collaboration: A Transdisciplinary Roadmap to Discovery
Conference Sponsor:Sigma Theta Tau International
Conference Year:2007
Author:Brown, Diane Storer, RN, PhD, FNAQH, CPHQ
P.I. Institution Name:Northern California Kaiser Permanente
Title:Director of Quality & Continuous Readiness
Co-Authors:Carolyn E. Aydin, PhD; Nancy E. Donaldson, RN, DNSc, FAAN; and M. Linda Burnes Bolton, RN, DPH
[Research Presentation] The purpose of this paper is to describe the development of evidence-based best practice identification using a research and quality improvement database to identify acute care best practices and translate these findings into bundles of actions which improve healthcare delivery.áThe California Nursing Outcome Coalition (CalNOC) database, a state-wide voluntary research and quality improvement database, contains 9 years of data from 174 hospitals who contribute data in order to understand patient outcome and nurse staffing performance.áThe repository provides prospective data on structural variables and patient outcomes, collected concurrently at the unit-level within hospitals, using standardized codebooks and data capture methods, data collector rater-to-standard training, and data checking algorithms to ensure valid and reliable data. Member hospitals have access to on-demand reporting functions on the CalNOC website to generate quarterly reports that compare their own performance with that of "like" hospitals. Hospitals use reports for their own internal dashboards and for setting hospital-specific patient safety goals. This paper describes the methodology to identify sustained top and bottom quartile performance hospitals in relation to patient fall rates, falls with injury rates, and hospital acquired pressure ulcers.á Hospital case study approaches were used for identification of practices that determined quartile performance. The structure of care was explored related to nurse staffing skill mix, hours of care, bed or patient turnover, use of contracted staff, nurse turnover, and nurse variables related to education and experience.á The process of care was explored related to risk assessment processes, risk identification, and implementation of preventive nursing interventions.áMethodologies will be described which were used to translate these research findings into actions that all CalNOC hospitals could implement to improve their relative performance and patient outcomes.á The research teamÆs experiences with analysis of this large ongoing dataset will also be described.
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.titleCollaboration: A Transdisciplinary Roadmap to Discoveryen_GB
dc.identifier.urihttp://hdl.handle.net/10755/151235-
dc.description.abstract<table><tr><td colspan="2" class="item-title">Collaboration: A Transdisciplinary Roadmap to Discovery</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">Brown, Diane Storer, RN, PhD, FNAQH, CPHQ</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">Northern California Kaiser Permanente</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">Director of Quality &amp; Continuous Readiness</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">diane.brown@kp.org</td></tr><tr class="item-co-authors"><td class="label">Co-Authors:</td><td class="value">Carolyn E. Aydin, PhD; Nancy E. Donaldson, RN, DNSc, FAAN; and M. Linda Burnes Bolton, RN, DPH</td></tr><tr><td colspan="2" class="item-abstract">[Research Presentation] The purpose of this paper is to describe the development of evidence-based best practice identification using a research and quality improvement database to identify acute care best practices and translate these findings into bundles of actions which improve healthcare delivery.&aacute;The California Nursing Outcome Coalition (CalNOC) database, a state-wide voluntary research and quality improvement database, contains 9 years of data from 174 hospitals who contribute data in order to understand patient outcome and nurse staffing performance.&aacute;The repository provides prospective data on structural variables and patient outcomes, collected concurrently at the unit-level within hospitals, using standardized codebooks and data capture methods, data collector rater-to-standard training, and data checking algorithms to ensure valid and reliable data. Member hospitals have access to on-demand reporting functions on the CalNOC website to generate quarterly reports that compare their own performance with that of &quot;like&quot; hospitals. Hospitals use reports for their own internal dashboards and for setting hospital-specific patient safety goals. This paper describes the methodology to identify sustained top and bottom quartile performance hospitals in relation to patient fall rates, falls with injury rates, and hospital acquired pressure ulcers.&aacute; Hospital case study approaches were used for identification of practices that determined quartile performance. The structure of care was explored related to nurse staffing skill mix, hours of care, bed or patient turnover, use of contracted staff, nurse turnover, and nurse variables related to education and experience.&aacute; The process of care was explored related to risk assessment processes, risk identification, and implementation of preventive nursing interventions.&aacute;Methodologies will be described which were used to translate these research findings into actions that all CalNOC hospitals could implement to improve their relative performance and patient outcomes.&aacute; The research team&AElig;s experiences with analysis of this large ongoing dataset will also be described.</td></tr></table>en_GB
dc.date.available2011-10-26T10:55:55Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T10:55:55Z-
dc.description.sponsorshipSigma Theta Tau Internationalen_GB
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