Document Detail


A longitudinal analysis of nursing specialty certification by magnet® status and patient unit type.
MedLine Citation:
PMID:  23151929     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
The objective of this study was to examine nursing specialty certification trends by Magnet® status and unit type. Research exploring organizational and unit attributes associated with higher specialty certification rates is timely given the beginning evidence that certification is associated with lower patient adverse events. The sample included 6047 units in 1249 National Database of Nursing Quality Indicators hospitals. Hierarchical linear modeling was used to predict growth in percentage of specialty-certified RNs within each unit type and Magnet status. Data (Bayesian Information Criteria = 224 583.30) demonstrated significant growth in specialty certification rates over time (P < .0001). Magnet-designated organizations had significantly different starting certification rates (P = .0002) and rates of change (P = .0002). Unit types also had significantly different starting certification rates (P < .0001) and different rates of change (P < .0001). Magnet recognition is associated with increases in specialty certification rates. Certification rates have risen faster in unit types such as pediatric critical care than in unit types such as adult step-down and adult surgical.
Authors:
Diane K Boyle; Byron J Gajewski; Peggy A Miller
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  The Journal of nursing administration     Volume:  42     ISSN:  1539-0721     ISO Abbreviation:  J Nurs Adm     Publication Date:  2012 Dec 
Date Detail:
Created Date:  2012-11-15     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  1263116     Medline TA:  J Nurs Adm     Country:  United States    
Other Details:
Languages:  eng     Pagination:  567-73     Citation Subset:  AIM; IM; N    
Affiliation:
Author Affiliations: Associate Professor (Dr Boyle) and Research Assistant Professor (Dr Miller), School of Nursing, University of Kansas and Professor (Dr Gajewski), Schools of Medicine and Nursing, Department of Biostatistics, University of Kansas.
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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