Written by Ali Garavand, Mohammah Mohseni, Heshmatollah Asadi, Manal Etemadi, Mohammad Moradi-Joo, Ahmad Moosavi
Parent Category: Year 2016, Volume 8
Category: Volume 8, Issue 8, August 2016
Introduction: The successful implementation of health information technologies requires investigating the factors affecting the acceptance and use of them. The aim of this study was to determine the most important factors affecting the adoption of health information technologies by doing a systematic review on the factors affecting the acceptance of health information technology.
Methods: This systematic review was conducted by searching the major databases, such as Google Scholar, Emerald, Science Direct, Web of Science, Pubmed, and Scopus. We used various keywords, such as adoption, use, acceptance of IT in medicine, hospitals, and IT theories in health services, and we also searched on the basis of several important technologies, such as Electronic Health Records (HER), Electronic Patient Records (EPR), Electronic Medical Records (EMR), Computerized Physician Order Entry (CPOE), Hospital Information System (HIS), Picture Archiving and Communication System (PACS), and others in the 2004-2014 period.
Results: The technology acceptance model (TAM) is the most important model used to identify the factors influencing the adoption of information technologies in the health system; also, the unified theory of acceptance and use of technology (UTAUT) model has had a lot of applications in recent years in the health system. Ease of use, usefulness, social impact, facilitating conditions, attitudes and behavior of users are effective in the adoption of health information technologies.
Conclusion: By considering various factors, including ease of use, usefulness, and social impact, the rate of the adoption of health information technology can be increased.
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Keywords: Technology Acceptance Model (TAM), Acceptance, Health Information Technology
Volume 12, Issue 4, October-December 2020
The worldwide spread of COVID-19 as an emerging, rapidly evolving situation, and the dramatic need of urgent medicine or vaccine, has rapidly brought new hypotheses for pathophysiology and potential medicinal agents to the fore. It is crucial that the research community provide a way to publish this research in a timely manner.
To contribute to this important public health discussion, the Electronic Physician Journal is excited to announce a fast-track procedure to help researchers publish their articles on COVID-19 related subjects that fall under the broad definition of public health, internal medicine, and pharmacology. We are especially welcome to all hypotheses about the pathological basis of the COVID-19 infection and the possible characteristics of potential medicine and vaccine. Submit your manuscript here
The 6th World Conference on Research Integrity (WCRI) is to be held on June 2-5, 2019 in Hong Kong.
The WCRI is the largest and most significant international conference on research integrity. Since the first conference in Lisbon in 2007, it has given researchers, teachers, funding agencies, government officials, journal editors, senior administrators, and research students opportunities to share experiences and to discuss and promote integrity in research. Read more:
TDR Clinical Research and Development Fellowships
Call for applications
Deadline for submission: 7 March 2019, 16:00 (GMT)
TDR provides fellowships for early- to mid-career researchers and clinical trial staff (e.g. clinicians, pharmacists, medical statisticians, data managers, other health researchers) in low- and middle-income countries (LMICs) to learn how to conduct clinical trials. Read more:
Meta-Analysis Workshops in New York, USA, and London, UK, in April and May 2019
Don't miss this exceptional opportunity to learn how to perform and report a Meta-analysis correctly. Two Meta-analysis workshops are organized in April and May 2019 by Dr. Michael Borenstein in New York, USA (April 08-10, 2019) and London, UK (May 27-29).
About the Instructor
Dr. Michael Borenstein, one of the authors of Introduction to Meta-Analysis, is widely recognized for his ability to make statistical concepts accessible to researchers as well as to statisticians. He has lectured widely on meta-analysis, including at the NIH, CDC, and FDA. Read more: