The Influence of Perceived Usefulness and Perceived Ease of Use on the Utilization of Electronic Medical Records: A Systematic Literature Review
DOI:
https://doi.org/10.35451/sn46mj50Keywords:
Elektronik, rekam medis, penerimaan, teknologi, technology, acceptance, Electronic, medical recordsAbstract
The utilization of Electronic Medical Records (EMR) is a crucial component of digital transformation in the healthcare sector to improve efficiency, accuracy, and quality of services. However, the success of EMR implementation largely depends on acceptance by end users, particularly healthcare professionals. The Technology Acceptance Model (TAM) is widely used to explain technology acceptance through two main constructs, namely Perceived Ease of Use (PEOU) and Perceived Usefulness (PU). Nevertheless, empirical studies examining the influence of PEOU and PU on EMR utilization have reported inconsistent findings. This study aims to analyze the influence of PEOU and PU on EMR utilization across various healthcare service contexts based on recent empirical evidence. A systematic literature review was conducted following the PRISMA guidelines. Literature searches were performed in the Scopus, ScienceDirect, PubMed, and Google Scholar databases for publications from 2019 to 2024 using relevant keywords and Boolean operators. The article selection process involved screening titles, abstracts, and full texts based on PICOS criteria, resulting in 13 quantitative studies included from a total of 196 identified articles. The narrative synthesis revealed three main patterns. First, PEOU was found to have a more significant influence than PU, particularly during the early stages of EMR adoption. Second, PU emerged as a stronger predictor of sustained EMR utilization. Third, several studies indicated that PEOU and PU contributed relatively equally to EMR acceptance. These variations reflect the complexity of interactions among user characteristics, organizational factors, and implementation contexts. In conclusion, both PEOU and PU play important roles in EMR utilization, with their relative influence varying according to the adoption phase and healthcare service conditions.
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