The Effects of Public Concern for Information Privacy on the Adoption of Health Information Exchanges (HIEs) by Healthcare Entities.


Journal

Health communication
ISSN: 1532-7027
Titre abrégé: Health Commun
Pays: England
ID NLM: 8908762

Informations de publication

Date de publication:
09 2019
Historique:
pubmed: 9 5 2018
medline: 9 6 2020
entrez: 9 5 2018
Statut: ppublish

Résumé

The implementation of Health Information Exchanges (HIEs) by healthcare organizations may not achieve the desired outcomes as consumers may request that their health information remains unshared because of information privacy concerns. Drawing on the insights of concern for information privacy (CFIP) literature, this work extends the application of CFIP to the HIE domain. This study attempts to develop and test a model centered on the four dimensions of CFIP construct (collection, errors, unauthorized access, and secondary use) and their antecedents to predict consumers' opt-in behavioral intention toward HIE in the presence of the perceived health status' effects. We conducted an online survey in the United States using 826 samples. The results demonstrate that the perceived health information sensitivity and computer anxiety meaningfully contribute to information privacy concerns and CFIP construct significantly impedes consumers' opt-in decision to HIEs. Interestingly, contrary to our expectation, perceived poor health status considerably attenuates the negative effects exerted by CFIP on opt-in intention. The model proposed by this study can be used as a useful conceptual tool by both further studies and practitioners to examine the complex nature of patients' reactions to information privacy threats associated with the use of HIE technology in the healthcare industry.

Identifiants

pubmed: 29737872
doi: 10.1080/10410236.2018.1471336
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1202-1211

Auteurs

Pouyan Esmaeilzadeh (P)

a Department of Information Systems and Business Analytics, College of Business, Florida International University.

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Classifications MeSH