Exploring Determinants of Electronic Medical Record (EMR) Ac-ceptance Using the Technology Acceptance Model (TAM): A Sys-tematic Literature Review

Abstrak

Background: Digital transformation in the healthcare sector has accelerated the implementation of Electronic Medical Records (EMR) to improve service quality and operational efficiency. However, the level of EMR acceptance among healthcare professionals still varies, indicating that technological readiness alone is not sufficient to ensure successful adoption.Objective: This study aims to analyze the determinants of EMR adoption based on a synthesis of empirical evidence using the Technology Acceptance Model (TAM) frameworkMethods: A systematic literature review was conducted following the PRISMA guidelines. A total of 20 empirical studies published between 2020 and 2025 were selected through systematic identification, screening, eligibility assessment, and quality assessment. The reviewed studies examined key TAM variables, including perceived usefulness (PU) and perceived ease of use (PEOU), as well as external factors such as management support, training, information technology infrastructure readiness, social influence, and digital literacy.Results: The synthesis reveals that PU and PEOU are the most consistent and significant determinants of both the intention to use and actual use of EMR systems. PEOU (Perceived Examination of Use/System Usefulness) often emerges as an initial determinant that influences PU (Perceived Use/User Usefulness), thereby indirectly reinforcing behavioral intent. Organizational factors generally do not have a direct influence on intention, but play an important role in shaping users' perceptions of the usefulness and ease of use of the system. Social factors and digital literacy were found to be increasingly relevant in collaborative and technology-based healthcare environments. Conclusion: Findings indicate that successful EMR implementation depends not only on technical readiness but also on organizational strategies and user capacity-building interventions. During the digital adoption transition phase, prioritizing system usability and ongoing training is essential to increase acceptance. Further research is recommended to integrate TAM (Technology Acceptance Model) with other behavioral theories, such as UTAUT (Uniform Teaching and Understanding/Information Technology), to better understand the dynamics of EMR acceptance in the context of mandatory policies, particularly in Indonesia following the implementation of PMK No. 24 of 2022.