Evaluating How Artificial Intelligence And Electronic Health Record Systems Influence Physician–Nurse Communication, Workflow Efficiency, And Clinical Decision-Making

Abstract

The growing level of Artificial Intelligence (AI) and electronic health record (EHR) system integration into the healthcare sector has transformed the way physicians and nurses communicate, organize work, and make clinical judgments. This study assesses the synergistic and disruptive impacts of these technologies on interprofessional collaboration and the efficiency of patient care. Based on sociotechnical systems theory, the technological acceptance model, and the concepts of human factors engineering, this qualitative and quantitative study integrates a quantitative workflow analysis and qualitative interviews in multidisciplinary hospital units. Findings show that although AI-enhanced decision support and automated documentation can create significant administrative load savings (up to 28 percent) and enhance the accuracy of diagnoses, it also leads to communication fragmentation, fatigue in alerts, and informal communication between nurses and physicians. EHR systems improved access to patient information but tended to subject the user to cognitive burden and reliance on electronic intermediaries. The evidence indicates that an appropriate AI design, customization of EHRs, and specifically oriented training of digital competence can help regain the equilibrium of workflow in clinical teams and build trust. As highlighted in the study, AI and the application of EHR technologies cannot be successfully realized without interoperability, as well as social and ethical alignment with the norms of clinical practices. Such insights provide an evidence-based informative basis for future healthcare technology policy, focusing on human-centered design, fair AI implementation, and sustainable digital transformation of healthcare settings.