title: Understanding physicians' acceptance of the Medline system for practicing evidence-based medicine: a decomposed TPB model.
abstract: OBJECTIVE
  Evidence-based medicine (EBM) supports physicians in their improvement of clinical quality and enhances hospitals' improvement of patient safety. Many health care institutions implement information systems to support physicians practicing EBM. However, studies exploring the antecedent factors of physicians' usage intention of information systems facilitating EBM practice are rare. Hence this study proposed a research model based on the decomposed theory of the planned behavior model (decomposed TPB) to investigate the factors influencing physicians' acceptance of the Medline system.
  
  
  METHODS
  A field survey was conducted in Taiwan to collect data from physicians with experience in using the Medline system. A valid sample of 224 physicians was collected for data analysis. Structural equation modeling using the partial least squares (PLS) method with bootstrap estimate was used to test the research model.
  
  
  RESULTS
  The findings of this study show that a physician's usage intention is significantly influenced by three factors, i.e. attitude, the subjective norm, and perceived behavior control. Furthermore, these three factors can be predicted by perceived usefulness and perceived ease of use, interpersonal influence, personal innovativeness in IT and self-efficacy, respectively.
  
  
  CONCLUSIONS
  The results of this study indicate that our research model provides an effective prediction of the intention of physicians to use the Medline system and provides valuable implications for academics and practitioners.
authors: Department of Information Management and Graduate Institute of Healthcare Information Management, National Chung Cheng University, Taiwan. syhung@mis.ccu.edu.tw
authors: Shin-Yuan
authors: SY
authors: Hung
authors: Yi-Cheng
authors: YC
authors: Ku
authors: Jui-Chi
authors: JC
authors: Chien
mesh_terms: D001291:Attitude of Health Personnel; D019317:Evidence-Based Medicine / Q000706:statistics & numerical data*; D016239:MEDLINE / Q000706:statistics & numerical data*; D008962:Models, Theoretical; D010820:Physicians / Q000706:statistics & numerical data*; D013624:Taiwan