2.50
Hdl Handle:
http://hdl.handle.net/10755/165811
Category:
Abstract
Type:
Presentation
Title:
Results from the outcomes research in nursing administration project
Author(s):
Mark, Barbara
Author Details:
Barbara Mark, University of North Carolina at Chapel Hill School of Nursing, Chapel Hill, North Carolina, USA, email: bmark@email.unc.edu
Abstract:
The Overview in this symposium series presented the conceptualization and design of the Outcomes Research in Nursing Administration Project (ORNA). This presentation discusses the findings, based on the analytic technique of multi-level covariance structure analysis. For ease of presentation, we first present the hospital level model, and then the nursing unit level model. All results are significant at p < .10. Hospital Level Model: 5 hospital characteristics were included: size, technological complexity, case mix index, teaching status and admission volatility. Multicollinearity between size and technological complexity resulted in problems in model convergence; hospital size was dropped from the model. Teaching status and case mix index led to further problems of model convergence and were also dropped. Professional practice was diminished in hospitals where there was a volatile pattern of admissions (standardized coefficient -.27), and was enhanced in hospitals that offered many high tech services (.39). Professional practice was also enhanced by the availability of support services (.33), but diminished on larger units (-.38). Further, unit size directly reduced the rate of patient falls (-.79). Professional practice had an extremely strong positive impact on work satisfaction (.83), and was associated with lower nursing turnover (-.48). Nursing Unit Level Model: Professional practice was solely predicted by the availability of support services (.57), which, in turn predicted higher levels of nurses' work satisfaction (.35). There were no significant relationships between professional practice and any other organizational or patient outcomes. There were a number of significant relationships between nursing unit characteristics and outcomes. Larger unit size contributed to both lower levels of nurse satisfaction (-.20), and higher levels of turnover (.29), as well as to lower levels of patient satisfaction (-.34). In addition, the rate of reported patient falls was higher on larger units (.20). Patient technology, a measure complexity of care, contributed to lower levels of job satisfaction (-.38). On units with more experienced nurses, turnover was lower (-.26), but the rate of reported patient falls was higher (.26). RN skill mix was associated with both higher rates of reported patient falls (.21) and medication errors (.23). Model Fit: The chi-square value was 146 with 122 degrees of freedom (p = .06) for the full structural equation model (which incorporates both the hospital level model and the nursing unit level model). The RMSEA for the full model was 0.041 (90% confidence interval .00 - .064, probability of RMSEA < .05 = .72). Both measures indicate a good fit of the hypothesized model. Conclusion: This is the first study in nursing systems to use multi-level covariance structure analysis, and the results support that the explained variance in selected outcome variables is highly dependent upon the unit of analysis.
Repository Posting Date:
27-Oct-2011
Date of Publication:
27-Oct-2011
Conference Host:
Southern Nursing Research Society
Note:
This is an abstract-only submission. If the author has submitted a full-text item based on this abstract, you may find it by browsing the Virginia Henderson Global Nursing e-Repository by author. If author contact information is available in this abstract, please feel free to contact him or her with your queries regarding this submission. Alternatively, please contact the conference host, journal, or publisher (according to the circumstance) for further details regarding this item. If a citation is listed in this record, the item has been published and is available via open-access avenues or a journal/database subscription. Contact your library for assistance in obtaining the as-published article.

Full metadata record

DC FieldValue Language
dc.type.categoryAbstracten_US
dc.typePresentationen_GB
dc.titleResults from the outcomes research in nursing administration projecten_GB
dc.contributor.authorMark, Barbaraen_US
dc.author.detailsBarbara Mark, University of North Carolina at Chapel Hill School of Nursing, Chapel Hill, North Carolina, USA, email: bmark@email.unc.eduen_US
dc.identifier.urihttp://hdl.handle.net/10755/165811-
dc.description.abstractThe Overview in this symposium series presented the conceptualization and design of the Outcomes Research in Nursing Administration Project (ORNA). This presentation discusses the findings, based on the analytic technique of multi-level covariance structure analysis. For ease of presentation, we first present the hospital level model, and then the nursing unit level model. All results are significant at p < .10. Hospital Level Model: 5 hospital characteristics were included: size, technological complexity, case mix index, teaching status and admission volatility. Multicollinearity between size and technological complexity resulted in problems in model convergence; hospital size was dropped from the model. Teaching status and case mix index led to further problems of model convergence and were also dropped. Professional practice was diminished in hospitals where there was a volatile pattern of admissions (standardized coefficient -.27), and was enhanced in hospitals that offered many high tech services (.39). Professional practice was also enhanced by the availability of support services (.33), but diminished on larger units (-.38). Further, unit size directly reduced the rate of patient falls (-.79). Professional practice had an extremely strong positive impact on work satisfaction (.83), and was associated with lower nursing turnover (-.48). Nursing Unit Level Model: Professional practice was solely predicted by the availability of support services (.57), which, in turn predicted higher levels of nurses' work satisfaction (.35). There were no significant relationships between professional practice and any other organizational or patient outcomes. There were a number of significant relationships between nursing unit characteristics and outcomes. Larger unit size contributed to both lower levels of nurse satisfaction (-.20), and higher levels of turnover (.29), as well as to lower levels of patient satisfaction (-.34). In addition, the rate of reported patient falls was higher on larger units (.20). Patient technology, a measure complexity of care, contributed to lower levels of job satisfaction (-.38). On units with more experienced nurses, turnover was lower (-.26), but the rate of reported patient falls was higher (.26). RN skill mix was associated with both higher rates of reported patient falls (.21) and medication errors (.23). Model Fit: The chi-square value was 146 with 122 degrees of freedom (p = .06) for the full structural equation model (which incorporates both the hospital level model and the nursing unit level model). The RMSEA for the full model was 0.041 (90% confidence interval .00 - .064, probability of RMSEA < .05 = .72). Both measures indicate a good fit of the hypothesized model. Conclusion: This is the first study in nursing systems to use multi-level covariance structure analysis, and the results support that the explained variance in selected outcome variables is highly dependent upon the unit of analysis.en_GB
dc.date.available2011-10-27T14:34:11Z-
dc.date.issued2011-10-27en_GB
dc.date.accessioned2011-10-27T14:34:11Z-
dc.conference.hostSouthern Nursing Research Societyen_US
dc.description.noteThis is an abstract-only submission. If the author has submitted a full-text item based on this abstract, you may find it by browsing the Virginia Henderson Global Nursing e-Repository by author. If author contact information is available in this abstract, please feel free to contact him or her with your queries regarding this submission. Alternatively, please contact the conference host, journal, or publisher (according to the circumstance) for further details regarding this item. If a citation is listed in this record, the item has been published and is available via open-access avenues or a journal/database subscription. Contact your library for assistance in obtaining the as-published article.-
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