An empirical taxonomy of hospital governing board roles.
Ontology highlight
ABSTRACT: Objective
To develop a taxonomy of governing board roles in U.S. hospitals.Data sources
2005 AHA Hospital Governance Survey, 2004 AHA Annual Survey of Hospitals, and Area Resource File.Study design
A governing board taxonomy was developed using cluster analysis. Results were validated and reviewed by industry experts. Differences in hospital and environmental characteristics across clusters were examined.Data extraction methods
One-thousand three-hundred thirty-four hospitals with complete information on the study variables were included in the analysis.Principal findings
Five distinct clusters of hospital governing boards were identified. Statistical tests showed that the five clusters had high internal reliability and high internal validity. Statistically significant differences in hospital and environmental conditions were found among clusters.Conclusions
The developed taxonomy provides policy makers, health care executives, and researchers a useful way to describe and understand hospital governing board roles. The taxonomy may also facilitate valid and systematic assessment of governance performance. Further, the taxonomy could be used as a framework for governing boards themselves to identify areas for improvement and direction for change.
SUBMITTER: Lee SY
PROVIDER: S-EPMC2517269 | biostudies-literature | 2008 Aug
REPOSITORIES: biostudies-literature
Publications
An empirical taxonomy of hospital governing board roles.
Lee Shoou-Yih D SY Alexander Jeffrey A JA Wang Virginia V Margolin Frances S FS Combes John R JR
Health services research 20080317 4
<h4>Objective</h4>To develop a taxonomy of governing board roles in U.S. hospitals.<h4>Data sources</h4>2005 AHA Hospital Governance Survey, 2004 AHA Annual Survey of Hospitals, and Area Resource File.<h4>Study design</h4>A governing board taxonomy was developed using cluster analysis. Results were validated and reviewed by industry experts. Differences in hospital and environmental characteristics across clusters were examined.<h4>Data extraction methods</h4>One-thousand three-hundred thirty-fo ...[more]
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