Healthc Inform Res.  2015 Jan;21(1):43-48. 10.4258/hir.2015.21.1.43.

Performance Evaluation of Public Hospital Information Systems by the Information System Success Model

• Cho KW
• Bae SK
• Ryu JH
• Kim KN
• An CH
• Chae YM

• KMID: 2284597
• DOI: http://doi.org/10.4258/hir.2015.21.1.43

Abstract

OBJECTIVES
This study was to evaluate the performance of the newly developed information system (IS) implemented on July 1, 2014 at three public hospitals in Korea.
METHODS
User satisfaction scores of twelve key performance indicators of six IS success factors based on the DeLone and McLean IS Success Model were utilized to evaluate IS performance before and after the newly developed system was introduced.
RESULTS
All scores increased after system introduction except for the completeness of medical records and impact on the clinical environment. The relationships among six IS factors were also analyzed to identify the important factors influencing three IS success factors (Intention to Use, User Satisfaction, and Net Benefits). All relationships were significant except for the relationships among Service Quality, Intention to Use, and Net Benefits.
CONCLUSIONS
The results suggest that hospitals should not only focus on systems and information quality; rather, they should also continuously improve service quality to improve user satisfaction and eventually reach full the potential of IS performance.

Keyword

Electronic Medical Records; Information Systems; Evaluation Studies

MeSH Terms

Electronic Health Records
Hospitals, Public*
Information Systems*
Intention
Korea
Medical Records

Figure

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  Figure 1 Structural equation model for information system success factors.

Reference

1. Cho I, Choi WJ, Choi WH, Kim MK. The adoptions and use of electronic nursing records in Korean hospitals: findings of a nationwide survey. J Korean Clin Nurs Res. 2013; 19(3):345–356.

2. Chae YM, Yoo KB, Kim ES, Chae H. The adoption of electronic medical records and decision support systems in Korea. Healthc Inform Res. 2011; 17(3):172–177.

3. DeLone WH, McLean ER. The DeLone and McLean model of information systems success: a ten-year update. J Manag Inf Syst. 2003; 19(4):9–30.

4. Van Der Meijden MJ, Tange HJ, Troost J, Hasman A. Determinants of success of inpatient clinical information systems: a literature review. J Am Med Inform Assoc. 2003; 10(3):235–243.

5. Park J, Chae YM, Lee YT, Cho K, Kim J, Lee BH. Evaluation of CDSS for drug prescriptions based on success measures. J Korean Soc Med Inform. 2009; 15(3):293–301.

6. Pai FY, Huang KI. Applying the Technology Acceptance Model to the introduction of healthcare information systems. Technol Forecast Soc Change. 2011; 78(4):650–660.

7. Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Mark Res. 1981; 18(1):39–50.

8. Chin WW. The partial least squares approach to structural equation modeling. In : Marcoulides GA, editor. Modern methods for business research. Mahwah (NJ): Lawrence Erlbaum;1998. p. 295–336.

9. Kaushal R, Shojania KG, Bates DW. Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review. Arch Intern Med. 2003; 163(12):1409–1416.

10. Kim J, Chae YM, Kim S, Ho SH, Kim HH, Park CB. A study on user satisfaction regarding the clinical decision support system (CDSS) for medication. Healthc Inform Res. 2012; 18(1):35–43.