Year: 2026 | Month: April-June | Volume: 11 | Issue: 2 | Pages: 60-68
DOI: https://doi.org/10.52403/gijhsr.20260207
Challenges in Electronic Health Record Implementation: User Acceptance, Data Interoperability, and Patient Care Quality
Blessing Emosho Ogeyemhe1, Efosa Bolaji Odigie1
1Department of Medical Laboratory Science, University of Benin, Nigeria.
Corresponding Author: E.B. Odigie
ABSTRACT
Electronic Health Records (EHRs) have become fundamental to modern healthcare systems, offering improved data management, enhanced clinical decision-making, and better coordination of patient care. Despite these advantages, their implementation remains challenged by issues related to user acceptance, system usability, and data interoperability. This review examines the key barriers influencing EHR adoption among healthcare professionals, including inadequate training, complex system design, workflow disruption, and resistance to change. Poor interoperability across diverse platforms further limits efficient data exchange, resulting in fragmented patient information and suboptimal clinical outcomes. Emerging technologies such as artificial intelligence, natural language processing, blockchain, and health information exchanges present promising opportunities to improve system functionality, facilitate seamless data integration, and support clinical workflows. Additionally, the incorporation of genomic data into EHR systems offers significant potential for advancing precision medicine and personalized healthcare delivery. Addressing these challenges requires a comprehensive approach that emphasizes user-centered system design, continuous professional training, supportive regulatory frameworks, and sustained technological innovation. Optimizing EHR implementation is essential for improving patient outcomes, increasing healthcare efficiency, and strengthening the overall quality, safety, and sustainability of healthcare delivery systems.
Keywords: Electronic Health Records (EHR), Healthcare Professional Adoption, Data Usability and Training, Data Interoperability, Patient Care Quality