Using a modified technology acceptance model in hospitals

Int J Med Inform. 2009 Feb;78(2):115-26. doi: 10.1016/j.ijmedinf.2008.06.006. Epub 2008 Aug 3.


Purpose: The use of information technology in the health care sector and especially in hospitals offers great potential for improving the quality of services provided and the efficiency and effectiveness of the personnel, but also for reducing the organizational expenses. However, the main question that arises according to the literature is whether hospital personnel are willing to use state of the art information technology while performing their tasks. This study attempts to address this issue by developing and testing a modified technology acceptance model taking into consideration other relevant models found in the literature.

Method: The original TAM has been extended to include some exogenous variables in order to examine HIS acceptance by Greek hospital personnel. Correlation, explanatory and confirmation factor analysis was performed to test the reliability and validity of the measurement model. The structural equation modeling technique has also been used to evaluate the causal model.

Results: The results indicate that perceived usefulness, ease of use, social influence, attitude, facilitating conditions and self-efficacy significantly affect hospital personnel behavioral intention. Training has a strong indirect impact on behavioral intention through the mediators of facilitating condition and ease of use. Furthermore, the existence of significant positive effects between self-efficacy and social influence, perceived usefulness and anxiety, and facilitating conditions and social influence is also supported.

Conclusions: The proposed model can explain 87% of the variance of behavioral intention indicating that the core constructs of the technology acceptance models have a strong and statistically significant influence on hospital personnel usage intention.

MeSH terms

  • Adult
  • Female
  • Health Personnel / statistics & numerical data*
  • Hospitals*
  • Humans
  • Male
  • Medical Informatics / methods
  • Medical Informatics / statistics & numerical data*
  • Middle Aged
  • Reproducibility of Results