Although several previous studies have found “system affiliation” to be a significant and positive predictor of health information technology (IT) adoption, little is known about the association between corporate governance practices and adoption of IT within U.S. integrated delivery systems (IDSs).
Rooted in agency theory and corporate governance research, this study examines the association between corporate governance practices (centralization of IT decision rights and strategic alignment between business and IT strategy) and IT adoption, standardization, and innovation within IDSs.
Cross-sectional, retrospective analyses using data from the 2011 Health Information and Management Systems Society Analytics Database on adoption within IDSs (N = 485) is used to analyze the correlation between two corporate governance constructs (centralization of IT decision rights and strategic alignment) and three IT constructs (adoption, standardization, and innovation) for clinical and supply chain IT. Multivariate fractional logit, probit, and negative binomial regressions are applied.
Multivariate regressions controlling for IDS and market characteristics find that measures of IT adoption, IT standardization, and innovative IT adoption are significantly associated with centralization of IT decision rights and strategic alignment. Specifically, centralization of IT decision rights is associated with 22% higher adoption of Bar Coding for Materials Management and 30%–35% fewer IT vendors for Clinical Data Repositories and Materials Management Information Systems. A combination of centralization and clinical IT strategic alignment is associated with 50% higher Computerized Physician Order Entry adoption, and centralization along with supply chain IT strategic alignment is significantly negatively correlated with Radio Frequency Identification adoption
Although IT adoption and standardization are likely to benefit from corporate governance practices within IDSs, innovation is likely to be delayed. In addition, corporate governance is not one-size-fits-all, and contingencies are important considerations.
Aaron Baird, PhD, MBA, is Assistant Professor, Institute of Health Administration and Center for Health Information Technology, J. Mack Robinson College of Business, Georgia State University, P.O. Box 3988, Atlanta. E-mail: email@example.com.
Michael F. Furukawa, PhD, is Director, Office of Economic Analysis, Evaluation, and Modeling, Office of the National Coordinator for Health Information Technology, Department of Health and Human Services, Washington, DC. E-mail: firstname.lastname@example.org.
Bushra Rahman, MBA, MHSM, is Research Administrator, Health Sector Supply Chain Research Consortium, Department of Supply Chain Management, W.P. Carey School of Business, Arizona State University, P.O. Box 874706, Tempe.
Eugene S. Schneller, PhD, is Dean’s Council of 100 Distinguished Scholar, Department of Supply Chain Management, W.P. Carey School of Business, Arizona State University, P.O. Box 874706, Tempe.
This research was partially funded by a grant from the Health Sector Supply Chain Research Consortium, W.P. Carey School of Business, Arizona State University.
The authors have disclosed that they have no significant relationship with, or financial interest in, any commercial companies pertaining to this article.