A Cybersecurity-Centric Model for Predicting Electronic Health Records System Adoption for Sustainable Healthcare: A SEM-ANN Approach

Electronic Health Records (EHR) systems are critical for achieving healthcare sustainability, offering benefits such as improving care of the patient, enhanced management of data, and operational efficiency. Despite these advantages, the adoption of EHR systems remains a challenge, influenced by various technological, organizational, and individual factors. This study builds upon the UTAUT2 framework by incorporating cybersecurity considerations to offer a more comprehensive understanding of EHR adoption and its role in promoting sustainable healthcare. Data were collected from 374 healthcare professionals through purposive sampling and analyzed using a hybrid approach combining Structural Equation Modeling (SEM) and Artificial Neural Networks (ANN). The findings demonstrate that EHR use plays a key role in advancing healthcare sustainability by improving organizational efficiency and long-term resilience. Key factors influencing EHR adoption include confidentiality and possession/control, underscoring the importance of data privacy, security, and system ownership. Performance expectancy and social influence significantly impact adoption decisions, reflecting the role of usability, peer influence, and organizational dynamics. Additional factors such as integrity and facilitating conditions showed moderate importance, while hedonic motivation and availability were less critical. This study contributes to EHR adoption research by integrating cybersecurity and user experience factors, offering insights for healthcare organizations and policymakers. The findings highlight the need to prioritize data security and usability to enhance adoption. Future research could explore EHR adoption in diverse settings and examine evolving adoption dynamics.