Healthcare information technology: A correlational study of governance maturity and patient costs

The SAS Dissertation Abstract Journal publishes abstracts from UOPX SAS Students who have completed and published his or her dissertation manuscripts. A full text copy of the dissertation may be found at:

Rice, J. C. (2015, October 12). Healthcare information technology: A correlational study of governance maturity and patient costs (D.M./IST). University of Phoenix, Phoenix, AZ. https://doi.org/10.13140/RG.2.1.2860.2964

 

Abstract: 

United States healthcare businesses are changing. Commercial interests, public policy, and patient care considerations influence business decisions concerning the level of information technology (IT) expenditure. Despite research into the relationship between IT governance and efficient use of IT, literature about the relationship between the application of mature IT governance standards and IT cost-per-patient in healthcare systems does not exist. The specific research question for this study was; what is the relationship between IT governance maturity and the IT cost-per-patient in United States healthcare systems? Sirius Computer Solutions collects census data for the Governance Maturity variable. The Dorenfest Institute for Health Information, a HIMSS Analytics Foundation, collects data for academic research and provided data for the IT Budget per Adjusted Patient Day. A matching technique using the HAEntity variable as the repeated measure resulted in 194 data pairs that constituted a convenience sample from the population of 418 large United States integrated healthcare organizations. Analysis included data for the calendar year 2012, the most recent year that census data were available from both secondary data sources. Correlation analysis included linear regression, a Pearson Product-Moment analysis, and a Power Analysis. Results of the correlation analysis showed a significant inverse correlation between IT Governance Maturity scores and the IT Budget per Adjusted Patient Day variables. Although the study did not demonstrate causality, correlation analysis showed that 32.6% of the total variation between the variables is attributable to this statistically significant relationship.

This publication has been peer reviewed.
Publication Type: 
Dissertation
Authors: 
James C. Rice
Year of Publication: 
2016
Journal, Book, Magazine or Other Publication Title: 
SAS Dissertation Abstract Journal
Volume: 
April 2016
Issue: 
4
Edition: 
1
Pages: 
121
Publisher: 
University of Phoenix; ProQuest
Date Published: 
Wednesday, March 1, 2017
Place Published: 
http://research.phoenix.edu
Publication Language: 
English
DOI: 
10.13140/RG.2.1.2860.2964
Editors: 
Jacob Harris < Jacob.Harris@phoenix.edu>
Boyer's Domain: 

Additional content will be provided upon request.

Additional content will be provided upon request.

James Rice
More posts by author: