Cited by 235Technology Adoption and User BehaviourPatient Safety and Medication ErrorsElectronic Health Records Systems

Testing the technology acceptance model for evaluating healthcare professionals’ intention to use an adverse event reporting system

Wu, J.-H., Shen, W.-S., Lin, L.-M., Greenes, R. A., Bates, D. W.·2007·International Journal for Quality in Health Care

Abstract

BACKGROUND: Many healthcare organizations have implemented adverse event reporting systems in the hope of learning from experience to prevent adverse events and medical errors. However, a number of these applications have failed or not been implemented as predicted. OBJECTIVE: This study presents an extended technology acceptance model that integrates variables connoting trust and management support into the model to investigate what determines acceptance of adverse event reporting systems by healthcare professionals. METHOD: The proposed model was empirically tested using data collected from a survey in the hospital environment. A confirmatory factor analysis was performed to examine the reliability and validity of the measurement model, and a structural equation modeling technique was used to evaluate the causal model. RESULTS: The results indicated that perceived usefulness, perceived ease of use, subjective norm, and trust had a significant effect on a professional's intention to use an adverse event reporting system. Among them, subjective norm had the most contribution (total effect). Perceived ease of use and subjective norm also had a direct effect on perceived usefulness and trust, respectively. Management support had a direct effect on perceived usefulness, perceived ease of use, and subjective norm. CONCLUSION: The proposed model provides a means to understand what factors determine the behavioral intention of healthcare professionals to use an adverse event reporting system and how this may affect future use. In addition, understanding the factors contributing to behavioral intent may potentially be used in advance of system development to predict reporting systems acceptance.

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Crossref · 10.1093/intqhc/mzm074

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Authors
Wu, J.-H., Shen, W.-S., Lin, L.-M., Greenes, R. A., & Bates, D. W.
Affiliations
  • National Sun Yat-sen University (TW)
  • Meiho University (TW)
  • Arizona State University (US)
  • Brigham and Women's Hospital (US)
Corresponding author
Greenes, R. A.
Venue
International Journal for Quality in Health Care
Published
2007-12-11
Volume
20
Issue
2
Pages
123-129
ISSN
  • 1353-4505 (ISSN-L)
  • 1464-3677
OpenAlex
W2128504617
Cited by
235
References
23
Citations by year
2026: 5 · 2025: 1 · 2024: 16 · 2023: 9 · 2022: 21 · 2021: 17 · 2020: 12 · 2019: 11 · 2018: 19 · 2017: 9 · 2016: 18 · 2015: 18 · 2014: 16 · 2013: 18 · 2012: 13
FWCI
15.11
Type
journal article
Language
en
Open access
closed
Locations
  • International Journal for Quality in Health Care (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
  • Health Sciences › Health Professions › Emergency Medical Services › Patient Safety and Medication Errors
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
Keywords
technology acceptance model, adverse event reporting system, healthcare workers, behavioral intention, trust, management support, perceived usefulness, perceived ease of use, subjective norms, medical errors, hospital safety
MeSH terms
Attitude of Health Personnel, Confidentiality, Female, Humans, Male, Models, Psychological, Taiwan, Organizational Culture, Adverse Drug Reaction Reporting Systems, Intention, Trust

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