Artificial Intelligence Integration in Community and Primary Healthcare: Advancing and Sustainable Community Nursing Practice

Salman Wasl Althobaiti & Prof. Dr. Faridah Mohd Said
Corresponding Author
PHD Candidate at Lincoln University College, Malaysia
Email: Salmanw.althobaiti@gmail.com

Abstract

The integration of artificial intelligence (AI) into community and primary healthcare settings represents a transformative shift in healthcare delivery, with profound implications for nursing practice. This review examines the current state of AI applications in primary care and community health settings, focusing specifically on how these technologies impact nursing roles, responsibilities, and patient care outcomes. A systematic search of literature published between 2020 and 2025 identified 25 relevant studies exploring AI implementation in primary healthcare contexts. The findings reveal that AI technologies are being deployed across diverse nursing functions, including clinical decision support, patient triage, chronic disease management, health promotion, and administrative tasks. While AI demonstrates significant potential to enhance nursing efficiency, improve diagnostic accuracy, and support patient self-management, several challenges persist, including concerns about clinical autonomy, ethical considerations, workforce preparedness, and the risk of exacerbating health inequities. This review highlights the need for comprehensive training programs, ethical frameworks, and collaborative implementation strategies to ensure that AI serves as a tool to augment rather than replace nursing expertise. As AI continues to evolve, nurses in community and primary care settings must be positioned as active stakeholders in technology design and deployment to ensure patient-centered, equitable healthcare delivery.

Keywords: artificial intelligence, primary healthcare, community nursing, nursing practice, clinical decision support, machine learning, digital health, patient care