Patient-Engaged AI: The Nursing Path to Health Equity

Artificial intelligence (AI) technology in healthcare has emerged as a highly effective tool for enhancing health data analysis and patient engagement. Recent research examining patients' use of AI applications for self-managing health demonstrates notable benefits but also raises multiple concerns, including exacerbation of health disparities. Furthermore, limited information is available regarding nurses' interactions with patient-engaged AI (PEAI) and its impact on the nurse-patient relationship.

Developing new theoretical frameworks is essential to strengthening the evidence base for AI in nursing practice. The proposed middle-range theory constitutes a significant advancement toward delineating domains of nursing research to define AI utilization within the nurse-patient relationship and addressing health disparities.

Walker and Avant's steps were used to construct the theory, define concepts, and synthesize the literature and models.

An integrated theory-building synthesis identified 28 articles, from which five key themes emerged as crucial for mitigating health equity gaps: communication, end-user trust and perceptions, technology and design, self-management, and ethics and privacy. These impact patient engagement and, in turn, are influenced by health literacy.

Nursing research and practice are positioned to contribute critical evidence to close health disparities and redefine the nurse-patient relationship within the transformative context of the AI revolution.