Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/52946
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dc.contributor.authorTavares, Jorge-
dc.contributor.authorOliveira, Tiago-
dc.date.accessioned2018-11-26T23:26:58Z-
dc.date.available2018-11-26T23:26:58Z-
dc.date.issued2018-11-19-
dc.identifier.otherPURE: 6477810-
dc.identifier.otherPURE UUID: 8828bbf5-9feb-4c9e-908b-253b4dcc2075-
dc.identifier.otherScopus: 85056692068-
dc.identifier.otherPubMed: 30455169-
dc.identifier.otherWOS: 000451771400001-
dc.identifier.otherORCID: /0000-0001-6523-0809/work/59471977-
dc.identifier.urihttp://www.scopus.com/inward/record.url?scp=85056692068&partnerID=8YFLogxK-
dc.descriptionTavares, J., & Oliveira, T. (2018). New Integrated Model Approach to Understand the Factors That Drive Electronic Health Record Portal Adoption: Cross-Sectional National Survey. Journal Of Medical Internet Research, 20(11), [e11032]. DOI: 10.2196/11032-
dc.description.abstractBACKGROUND: The future of health care delivery is becoming more patient-focused, and electronic health record (EHR) portals are gaining more attention from worldwide governments that consider this technology as a valuable asset for the future sustainability of the national health care systems. Overall, this makes the adoption of EHR portals an important field to study. OBJECTIVE: The aim of this study is to understand the factors that drive individuals to adopt EHR portals. METHODS: We applied a new adoption model that combines 3 different theories, namely, extended unified theory of acceptance and use of technology, health belief model, and the diffusion of innovation; all the 3 theories provided relevant contributions for the understanding of EHR portals. To test the research model, we used the partial least squares causal modeling approach. We executed a national survey based on randomly generated mobile phone numbers. We collected 139 questionnaires. RESULTS: Performance expectancy (beta=.203; t=2.699), compatibility (beta=.530; t=6.189), and habit (beta=.251; t=2.660) have a statistically significant impact on behavior intention (R2=76.0%). Habit (beta=.378; t=3.821), self-perception (beta=.233; t=2.971), and behavior intention (beta=.263; t=2.379) have a statistically significant impact on use behavior (R2=61.8%). In addition, behavior intention (beta=.747; t=10.737) has a statistically significant impact on intention to recommend (R2=69.0%), results demonstrability (beta=.403; t=2.888) and compatibility (beta=.337; t=2.243) have a statistically significant impact on effort expectancy (R2=48.3%), and compatibility (beta=.594; t=6.141) has a statistically significant impact on performance expectancy (R2=42.7%). CONCLUSIONS: Our research model yields very good results, with relevant R2 in the most important dependent variables that help explain the adoption of EHR portals, behavior intention, and use behavior.en
dc.language.isoeng-
dc.rightsopenAccess-
dc.subjectadoption-
dc.subjecteHealth-
dc.subjectelectronic health records-
dc.subjectpatient portals-
dc.subjectpatients-
dc.subjectHealth Informatics-
dc.subjectSDG 3 - Good Health and Well-being-
dc.titleNew Integrated Model Approach to Understand the Factors That Drive Electronic Health Record Portal Adoption-
dc.typearticle-
degois.publication.issue11-
degois.publication.titleJournal of Medical Internet Research-
degois.publication.volume20-
dc.peerreviewedyes-
dc.identifier.doihttps://doi.org/10.2196/11032-
dc.description.versionpublishersversion-
dc.description.versionpublished-
dc.title.subtitleCross-Sectional National Survey-
dc.contributor.institutionNOVA Information Management School (NOVA IMS)-
dc.contributor.institutionInformation Management Research Center (MagIC) - NOVA Information Management School-
Aparece nas colecções:NIMS: MagIC - Artigos em revista internacional com arbitragem científica (Peer-Review articles in international journals)

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