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Factors Affecting Patients’ Use of Electronic Personal Health Records in England: Cross-Sectional Study

BACKGROUND: Electronic personal health records (ePHRs) are secure Web-based tools that enable individuals to access, manage, and share their medical records. England recently introduced a nationwide ePHR called Patient Online. As with ePHRs in other countries, adoption rates of Patient Online remain...

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Autores principales: Abd-Alrazaq, Alaa, Bewick, Bridgette M, Farragher, Tracey, Gardner, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6693305/
https://www.ncbi.nlm.nih.gov/pubmed/31368442
http://dx.doi.org/10.2196/12373
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author Abd-Alrazaq, Alaa
Bewick, Bridgette M
Farragher, Tracey
Gardner, Peter
author_facet Abd-Alrazaq, Alaa
Bewick, Bridgette M
Farragher, Tracey
Gardner, Peter
author_sort Abd-Alrazaq, Alaa
collection PubMed
description BACKGROUND: Electronic personal health records (ePHRs) are secure Web-based tools that enable individuals to access, manage, and share their medical records. England recently introduced a nationwide ePHR called Patient Online. As with ePHRs in other countries, adoption rates of Patient Online remain low. Understanding factors affecting patients’ ePHR use is important to increase adoption rates and improve the implementation success of ePHRs. OBJECTIVE: This study aimed to examine factors associated with patients’ use of ePHRs in England. METHODS: The unified theory of acceptance and use of technology was adapted to the use of ePHRs. To empirically examine the adapted model, a cross-sectional survey of a convenience sample was carried out in 4 general practices in West Yorkshire, England. Factors associated with the use of ePHRs were explored using structural equation modeling. RESULTS: Of 800 eligible patients invited to take part in the survey, 624 (78.0%) returned a valid questionnaire. Behavioral intention (BI) was significantly influenced by performance expectancy (PE; beta=.57, P<.001), effort expectancy (EE; beta=.16, P<.001), and perceived privacy and security (PPS; beta=.24, P<.001). The path from social influence to BI was not significant (beta=.03, P=.18). Facilitating conditions (FC) and BI significantly influenced use behavior (UB; beta=.25, P<.001 and beta=.53, P<.001, respectively). PE significantly mediated the effect of EE and PPS on BI (beta=.19, P<.001 and beta=.28, P=.001, respectively). Age significantly moderated 3 paths: PE→BI, EE→BI, and FC→UB. Sex significantly moderated only the relationship between PE and BI. A total of 2 paths were significantly moderated by education and internet access: EE→BI and FC→UB. Income moderated the relationship between FC and UB. The adapted model accounted for 51% of the variance in PE, 76% of the variance in BI, and 48% of the variance in UB. CONCLUSIONS: This study identified the main factors that affect patients’ use of ePHRs in England, which should be taken into account for the successful implementation of these systems. For example, developers of ePHRs should involve patients in the process of designing the system to consider functions and features that fit patients’ preferences and skills to ensure systems are useful and easy to use. The proposed model accounted for 48% of the variance in UB, indicating the existence of other, as yet unidentified, factors that influence the adoption of ePHRs. Future studies should confirm the effect of the factors included in this model and identify additional factors.
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spelling pubmed-66933052019-08-20 Factors Affecting Patients’ Use of Electronic Personal Health Records in England: Cross-Sectional Study Abd-Alrazaq, Alaa Bewick, Bridgette M Farragher, Tracey Gardner, Peter J Med Internet Res Original Paper BACKGROUND: Electronic personal health records (ePHRs) are secure Web-based tools that enable individuals to access, manage, and share their medical records. England recently introduced a nationwide ePHR called Patient Online. As with ePHRs in other countries, adoption rates of Patient Online remain low. Understanding factors affecting patients’ ePHR use is important to increase adoption rates and improve the implementation success of ePHRs. OBJECTIVE: This study aimed to examine factors associated with patients’ use of ePHRs in England. METHODS: The unified theory of acceptance and use of technology was adapted to the use of ePHRs. To empirically examine the adapted model, a cross-sectional survey of a convenience sample was carried out in 4 general practices in West Yorkshire, England. Factors associated with the use of ePHRs were explored using structural equation modeling. RESULTS: Of 800 eligible patients invited to take part in the survey, 624 (78.0%) returned a valid questionnaire. Behavioral intention (BI) was significantly influenced by performance expectancy (PE; beta=.57, P<.001), effort expectancy (EE; beta=.16, P<.001), and perceived privacy and security (PPS; beta=.24, P<.001). The path from social influence to BI was not significant (beta=.03, P=.18). Facilitating conditions (FC) and BI significantly influenced use behavior (UB; beta=.25, P<.001 and beta=.53, P<.001, respectively). PE significantly mediated the effect of EE and PPS on BI (beta=.19, P<.001 and beta=.28, P=.001, respectively). Age significantly moderated 3 paths: PE→BI, EE→BI, and FC→UB. Sex significantly moderated only the relationship between PE and BI. A total of 2 paths were significantly moderated by education and internet access: EE→BI and FC→UB. Income moderated the relationship between FC and UB. The adapted model accounted for 51% of the variance in PE, 76% of the variance in BI, and 48% of the variance in UB. CONCLUSIONS: This study identified the main factors that affect patients’ use of ePHRs in England, which should be taken into account for the successful implementation of these systems. For example, developers of ePHRs should involve patients in the process of designing the system to consider functions and features that fit patients’ preferences and skills to ensure systems are useful and easy to use. The proposed model accounted for 48% of the variance in UB, indicating the existence of other, as yet unidentified, factors that influence the adoption of ePHRs. Future studies should confirm the effect of the factors included in this model and identify additional factors. JMIR Publications 2019-07-31 /pmc/articles/PMC6693305/ /pubmed/31368442 http://dx.doi.org/10.2196/12373 Text en ©Alaa Abd-Alrazaq, Bridgette M Bewick, Tracey Farragher, Peter Gardner. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 31.07.2019. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Abd-Alrazaq, Alaa
Bewick, Bridgette M
Farragher, Tracey
Gardner, Peter
Factors Affecting Patients’ Use of Electronic Personal Health Records in England: Cross-Sectional Study
title Factors Affecting Patients’ Use of Electronic Personal Health Records in England: Cross-Sectional Study
title_full Factors Affecting Patients’ Use of Electronic Personal Health Records in England: Cross-Sectional Study
title_fullStr Factors Affecting Patients’ Use of Electronic Personal Health Records in England: Cross-Sectional Study
title_full_unstemmed Factors Affecting Patients’ Use of Electronic Personal Health Records in England: Cross-Sectional Study
title_short Factors Affecting Patients’ Use of Electronic Personal Health Records in England: Cross-Sectional Study
title_sort factors affecting patients’ use of electronic personal health records in england: cross-sectional study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6693305/
https://www.ncbi.nlm.nih.gov/pubmed/31368442
http://dx.doi.org/10.2196/12373
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