Nurse practitioners' involvement and experience with AI-based health technologies: A systematic review

Background: Artificial intelligence (AI) is emerging in healthcare in various forms, including AI-based clinical decision support systems, machine learning, computer vision, natural language processing, big data analytics and AI-enhanced robotics. Given their potential impact on clinical processes and decision-making, AI-based health technologies (AIHT) are now seen to have a transformative effect on the nursing and medical professions, and on advanced nursing practice in particular.Aims: While nurse practitioners (NPs) are increasingly called upon to play a crucial role in improving the healthcare provided to the population, little is known about the nature, extent and outcomes of their involvement and experience with AIHT. This study's research objectives are twofold. First, it aims to characterize NPs' involvement and experience with AIHT in terms of the functional and clinical attributes of the AIHT-based systems and applications that have emerged in advanced nursing care settings, and of the clinical tasks of NPs targeted for support by these systems and applications. Second, it aims to characterize this involvement and experience with AIHT in terms of its expected impacts on the clinical activities and performance of NPs, and of its potential outcomes for NPs' patients and for the general population. Method: We thus contribute to advanced practice nursing research by carrying out an initial evaluation of the role played by NPs in the emergence of these technologies, by means of a systematic review of the literature.Findings: This review demonstrates that NPs, acting alone or in collaboration with physicians and other healthcare professionals, participate in the development and evaluation of various AI-based decision-making and predictive tools in primary, hospital and emergency care settings. This participation involves NPs as diagnostic and therapeutic experts whose clinical activities, decision-making and performance can be significantly impacted by their adoption and assimilation of AIHT.