Literature DB >> 22733680

Acceptance of health information technology in health professionals: an application of the revised technology acceptance model.

Panayiotis Ketikidis1, Tomislav Dimitrovski, Lambros Lazuras, Peter A Bath.   

Abstract

The response of health professionals to the use of health information technology (HIT) is an important research topic that can partly explain the success or failure of any HIT application. The present study applied a modified version of the revised technology acceptance model (TAM) to assess the relevant beliefs and acceptance of HIT systems in a sample of health professionals (n = 133). Structured anonymous questionnaires were used and a cross-sectional design was employed. The main outcome measure was the intention to use HIT systems. ANOVA was employed to examine differences in TAM-related variables between nurses and medical doctors, and no significant differences were found. Multiple linear regression analysis was used to assess the predictors of HIT usage intentions. The findings showed that perceived ease of use, but not usefulness, relevance and subjective norms directly predicted HIT usage intentions. The present findings suggest that a modification of the original TAM approach is needed to better understand health professionals' support and endorsement of HIT. Perceived ease of use, relevance of HIT to the medical and nursing professions, as well as social influences, should be tapped by information campaigns aiming to enhance support for HIT in healthcare settings.

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Year:  2012        PMID: 22733680     DOI: 10.1177/1460458211435425

Source DB:  PubMed          Journal:  Health Informatics J        ISSN: 1460-4582            Impact factor:   2.681


  30 in total

1.  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

2.  Awareness, Knowledge, Attitude and Skills of Telemedicine among Health Professional Faculty Working in Teaching Hospitals.

Authors:  Zayabalaradjane Zayapragassarazan; Santosh Kumar
Journal:  J Clin Diagn Res       Date:  2016-03-01

3.  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

4.  Nurses' perceptions of a novel health information technology: A qualitative study in the pediatric intensive care unit.

Authors:  Onur Asan; Kathryn E Flynn; Laila Azam; Matthew C Scanlon
Journal:  Int J Hum Comput Interact       Date:  2017-02-10       Impact factor: 3.353

5.  Computer-Facilitated 5A's for Smoking Cessation: A Randomized Trial of Technology to Promote Provider Adherence.

Authors:  Jason M Satterfield; Steven E Gregorich; Sara Kalkhoran; Paula J Lum; Jessica Bloome; Nicholas Alvarado; Ricardo F Muñoz; Maya Vijayaraghavan
Journal:  Am J Prev Med       Date:  2018-06-18       Impact factor: 5.043

6.  Factors Affecting Patients' Acceptance of and Satisfaction with Cloud-Based Telehealth for Chronic Disease Management: A Case Study in the Workplace.

Authors:  Yung-Yu Su; Su-Tsai Huang; Ying-Hsun Wu; Chun-Min Chen
Journal:  Appl Clin Inform       Date:  2020-04-15       Impact factor: 2.342

7.  mDurance: A Novel Mobile Health System to Support Trunk Endurance Assessment.

Authors:  Oresti Banos; Jose Antonio Moral-Munoz; Ignacio Diaz-Reyes; Manuel Arroyo-Morales; Miguel Damas; Enrique Herrera-Viedma; Choong Seon Hong; Sungyong Lee; Hector Pomares; Ignacio Rojas; Claudia Villalonga
Journal:  Sensors (Basel)       Date:  2015-06-05       Impact factor: 3.576

8.  Health Professionals' readiness to implement electronic medical record system at three hospitals in Ethiopia: a cross sectional study.

Authors:  Senafekesh Biruk; Tesfahun Yilma; Mulusew Andualem; Binyam Tilahun
Journal:  BMC Med Inform Decis Mak       Date:  2014-12-12       Impact factor: 2.796

9.  Electronic Health Record Patient Portal Adoption by Health Care Consumers: An Acceptance Model and Survey.

Authors:  Jorge Tavares; Tiago Oliveira
Journal:  J Med Internet Res       Date:  2016-03-02       Impact factor: 5.428

10.  Electronic Health Record Portal Adoption: a cross country analysis.

Authors:  Jorge Tavares; Tiago Oliveira
Journal:  BMC Med Inform Decis Mak       Date:  2017-07-05       Impact factor: 2.796

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