Literature DB >> 18338086

User acceptance of a picture archiving and communication system. Applying the unified theory of acceptance and use of technology in a radiological setting.

P Duyck1, B Pynoo, P Devolder, T Voet, L Adang, J Vercruysse.   

Abstract

OBJECTIVE: The aim of this study is to gain insight into the individual user acceptance of PACS by the radiology department staff of the Ghent University Hospital. Hereto a basic--direct effects only--form of UTAUT was assessed.
METHODS: Ninety-four questionnaires were distributed and 56 usable questionnaires were returned (19 radiologists - 37 technologists). The questionnaire consisted of scales of Venkatesh et al. [13] for performance expectancy (PE), effort expectancy (EE), facilitating conditions (FC), social influence (SI), self-efficacy (SE), attitude (ATT), anxiety (ANX) and behavioral intention (BI), and a scale of Moore et al. [22] to assess the perceived voluntariness of PACS-use.
RESULTS: The reliability of all scales, except FC and voluntariness, was acceptable to good. The voluntariness scale was divided into a mandatoriness (MAN) and a voluntariness (VOL) measure. Both radiologists and technologists seem to welcome PACS, with radiologists having higher ratings on PE, EE, ATT, VOL and BI. Only PE and FC were salient for predicting BI, while EE and SI were not salient. Variance explained in behavioral intention to use PACS was 48%.
CONCLUSION: Both radiologists and technologists were positive towards PACS and had strong intentions to use PACS. As other healthcare professionals, they appear to make their technology acceptance decision independent from their superiors, hereby focusing on usefulness rather than on ease of use. It is also important that support is supplied. Basic UTAUT is an adequate model to assess technology acceptance in a radiological setting.

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Year:  2008        PMID: 18338086

Source DB:  PubMed          Journal:  Methods Inf Med        ISSN: 0026-1270            Impact factor:   2.176


  22 in total

1.  Monitoring the PACS implementation process in a large university hospital--discrepancies between radiologists and physicians.

Authors:  Philippe Duyck; Bram Pynoo; Pieter Devolder; Tony Voet; Luc Adang; Dries Ovaere; Jan Vercruysse
Journal:  J Digit Imaging       Date:  2008-10-28       Impact factor: 4.056

2.  Testing the Electronic Personal Health Record Acceptance Model by Nurses for Managing Their Own Health: A Cross-sectional Survey.

Authors:  K Gartrell; A M Trinkoff; C L Storr; M L Wilson; A P Gurses
Journal:  Appl Clin Inform       Date:  2015-04-08       Impact factor: 2.342

3.  Assessing task-technology fit in a PACS upgrade: do users' and developers' appraisals converge?

Authors:  Luigi Lepanto; Claude Sicotte; Pascale Lehoux
Journal:  J Digit Imaging       Date:  2011-12       Impact factor: 4.056

4.  Structured Data Entry in the Electronic Medical Record: Perspectives of Pediatric Specialty Physicians and Surgeons.

Authors:  Ruth A Bush; Cynthia Kuelbs; Julie Ryu; Wen Jiang; George Chiang
Journal:  J Med Syst       Date:  2017-03-21       Impact factor: 4.460

5.  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

6.  Determinant Factors in Applying Picture Archiving and Communication Systems (PACS) in Healthcare.

Authors:  Mohammadhiwa Abdekhoda; Kawa Mirza Salih
Journal:  Perspect Health Inf Manag       Date:  2017-07-01

7.  A new sociotechnical model for studying health information technology in complex adaptive healthcare systems.

Authors:  Dean F Sittig; Hardeep Singh
Journal:  Qual Saf Health Care       Date:  2010-10

Review 8.  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

Review 9.  A systematic review of patient acceptance of consumer health information technology.

Authors:  Calvin K L Or; Ben-Tzion Karsh
Journal:  J Am Med Inform Assoc       Date:  2009-04-23       Impact factor: 4.497

10.  The Determinants of M-Health Adoption in Developing Countries: An Empirical Investigation.

Authors:  Ahmad Alaiad; Mohammad Alsharo; Yazan Alnsour
Journal:  Appl Clin Inform       Date:  2019-10-30       Impact factor: 2.342

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