An empirical taxonomy of hospital governing board roles.
OBJECTIVE
To develop a taxonomy of governing board roles in U.S. hospitals.


METHODS
2005 AHA Hospital Governance Survey, 2004 AHA Annual Survey of Hospitals, and Area Resource File.


METHODS
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.


METHODS
One-thousand three-hundred thirty-four hospitals with complete information on the study variables were included in the analysis.


RESULTS
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.
Lee
Shoou-Yih D
SY
Department of Health Policy and Administration, School of Public Health, University of North Carolina at Chapel Hill, 1101 McGavran-Greenberg Hall (CB# 7411), Chapel Hill, NC 27599-7411, USA. sylee@email.unc.edu
Alexander
Jeffrey A
JA
Wang
Virginia
V
Margolin
Frances S
FS
Combes
John R
JR
D000573:American Hospital Association; D000704:Analysis of Variance; D002497:Centralized Hospital Services / Q000458:organization & administration; D016000:Cluster Analysis; D003659:Decision Making, Organizational; D006075:Governing Board / Q000145:classification* / Q000458:organization & administration* / Q000706:statistics & numerical data; D006764:Hospitals, Community / Q000145:classification* / Q000458:organization & administration* / Q000706:statistics & numerical data; D006801:Humans; D017146:Models, Organizational; D009936:Organizational Innovation; D016134:Organizational Policy; D015203:Reproducibility of Results; D014481:United States