Literature DB >> 18222963

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

Jen-Her Wu1, Wen-Shen Shen, Li-Min Lin, Robert A Greenes, David W Bates.   

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.

Mesh:

Year:  2008        PMID: 18222963     DOI: 10.1093/intqhc/mzm074

Source DB:  PubMed          Journal:  Int J Qual Health Care        ISSN: 1353-4505            Impact factor:   2.038


  39 in total

1.  Determinants of Physicians' Intention to Collect Data Exhaustively in Registries: an Exploratory Study in Bamako's Community Health Centres.

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Journal:  Ghana Med J       Date:  2015-06

2.  Understanding the mediating effects of relationship quality on technology acceptance: an empirical study of e-appointment system.

Authors:  Shih-Chih Chen; Shih-Chi Liu; Shing-Han Li; David C Yen
Journal:  J Med Syst       Date:  2013-10-19       Impact factor: 4.460

3.  Factors influencing presence in virtual worlds.

Authors:  Meyrick C M Chow
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4.  Status and problems of adverse event reporting systems in korean hospitals.

Authors:  Jeongeun Kim; Sukwha Kim; Yoenyi Jung; Eun-Kyung Kim
Journal:  Healthc Inform Res       Date:  2010-09-30

5.  Willingness to Report Medical Incidents in Healthcare: a Psychological Model Based on Organizational Trust and Benefit/Risk Perceptions.

Authors:  Xiaosong Zhao; Shumeng Zhao; Na Liu; Peng Liu
Journal:  J Behav Health Serv Res       Date:  2021-04-13       Impact factor: 1.505

6.  A Systematic Review of the Technology Acceptance Model in Health Informatics.

Authors:  Bahlol Rahimi; Hamed Nadri; Hadi Lotfnezhad Afshar; Toomas Timpka
Journal:  Appl Clin Inform       Date:  2018-08-15       Impact factor: 2.342

7.  Social networks and physician adoption of electronic health records: insights from an empirical study.

Authors:  Kai Zheng; Rema Padman; David Krackhardt; Michael P Johnson; Herbert S Diamond
Journal:  J Am Med Inform Assoc       Date:  2010 May-Jun       Impact factor: 4.497

8.  Applying Electronic Medical Records in Health Care: Physicians' Perspective.

Authors:  Mohammadhiwa Abdekhoda; Maryam Ahmadi; Afsaneh Dehnad; Alireza Noruzi; Mahmodreza Gohari
Journal:  Appl Clin Inform       Date:  2016-05-11       Impact factor: 2.342

9.  Factors Affecting Acceptance of Hospital Information Systems Based on Extended Technology Acceptance Model: A Case Study in Three Paraclinical Departments.

Authors:  Hamed Nadri; Bahlol Rahimi; Hadi Lotfnezhad Afshar; Mahnaz Samadbeik; Ali Garavand
Journal:  Appl Clin Inform       Date:  2018-04-04       Impact factor: 2.342

Review 10.  The technology acceptance model: its past and its future in health care.

Authors:  Richard J Holden; Ben-Tzion Karsh
Journal:  J Biomed Inform       Date:  2009-07-15       Impact factor: 6.317

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