Predicting Health Care Providers' Acceptance of a Personal Health Record Secure Messaging Feature

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BACKGROUND: Personal health records (PHRs) can facilitate patient-centered communication through the secure messaging feature. As health care organizations in the Kingdom of Saudi Arabia implement PHRs and begin to implement the secure messaging feature, studies are needed to evaluate health care providers' acceptance.

OBJECTIVE: The aim of this study was to identify predictors of health care providers' behavioral intention to support the addition of a secure messaging feature in PHRs using an adapted model of the Unified Theory of Acceptance and Use of Technology as the theoretical framework.

METHODS: Using a cross-sectional survey design, data on acceptance of secure messaging features in PHRs were collected from health care providers working at the Ministry of National Guard Health Affairs between April and May 2021. The proposed model was tested using partial least squares structural equation modeling in SmartPLS.

RESULTS: There were 224 participants: female (66.5%), 40 to 49 years of age (39.9%), nurses (45.1%), and those working more than 10 years in the organization (68.8%). Behavioral intention to support the addition of a secure messaging feature was significantly influenced by performance expectancy (β = 0.21, p = 0.01) and attitude (β = 0.50, p < 0.01), while other predicting factors, such as effort expectancy, social influence, and facilitating condition, did not significantly affect the intention. Furthermore, age, years of experience, and professional role did not moderate the relationships.

CONCLUSION: Health care professionals will support introducing a secure messaging feature in the PHRs if they serve the intended purpose. Considering attitude also plays a significant role in acceptance, it is necessary to arrange for training and support, so that caregivers, health care providers, and the patients become familiar with the benefits and expected outcomes of using the feature.

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:13

Enthalten in:

Applied clinical informatics - 13(2022), 1 vom: 13. Jan., Seite 148-160

Sprache:

Englisch

Beteiligte Personen:

Yousef, Consuela C [VerfasserIn]
Salgado, Teresa M [VerfasserIn]
Farooq, Ali [VerfasserIn]
Burnett, Keisha [VerfasserIn]
McClelland, Laura E [VerfasserIn]
Abu Esba, Laila C [VerfasserIn]
Alhamdan, Hani S [VerfasserIn]
Khoshhal, Sahal [VerfasserIn]
Aldossary, Ibrahim [VerfasserIn]
Alyas, Omar A [VerfasserIn]
DeShazo, Jonathan P [VerfasserIn]

Links:

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Themen:

Journal Article

Anmerkungen:

Date Completed 23.03.2022

Date Revised 10.02.2023

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1055/s-0041-1742217

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM336718403