APPLICATION OF UTAUT 3 MODEL TO PREDICT EMR ACCEPTANCE BY NURSES

Annisa Ambaravista Nasution; Ermi Girsang; Sri Lestari Ramadhani Nasution

doi:10.30602/jvk.v11i2.1818

APPLICATION OF UTAUT 3 MODEL TO PREDICT EMR ACCEPTANCE BY NURSES

Annisa Ambaravista Nasution, Ermi Girsang, Sri Lestari Ramadhani Nasution

Abstract

The implementation of an Electronic Medical Record (EMR) system plays an important role in improving the efficiency and quality of nursing services in hospitals. However, the level of user acceptance, especially nurses, is often a major challenge in its implementation. This study aims to analyze the factors that influence EMR acceptance by nurses at Graha Bunda Hospital using the Unified Theory of Acceptance and Use of Technology 3 (UTAUT3) approach. The method used is quantitative with an explanatory survey design. The study population included all active nurses at Graha Bunda Hospital, totaling 67 people, who were used as respondents through the total sampling technique. Data were collected through questionnaires and analyzed using the Partial Least Square (PLS) method with the help of SmartPLS software. The results of the analysis show that the variables of performance expectancy (β = 0.287; p < 0.05), effort expectancy (β = 0.224; p < 0.05), social influence (β = 0.231; p < 0.05), facilitating conditions (β = 0.265; p < 0.05), hedonic motivation, leadership and management, regulation and policy, technology readiness, and security & privacy have a significant influence on behavioral intention and use behavior. Moderating variables such as age, work experience, and level of volunteerism strengthen some of the relationships between variables. This study suggests that perceived usefulness, ease of use, organizational support, and technology readiness are key factors in EMR adoption. Hospitals need to focus on strengthening training, improving digital infrastructure, and creating a technology-based work culture to encourage optimal sustainability of EMR use

Keywords

Electronic Medical Record; UTAUT3; behavioral intention; use behavior; nurses; health technology

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DOI: https://doi.org/10.30602/jvk.v11i2.1818