Generative artificial intelligence (AI) applications have enhanced democratization of information to the extent that industry professionals can automate routine tasks, gain insights from complex data and execute tasks more efficiently through generation of text, image, and audio content. Although these applications augment human capabilities, there are concerns about veracity of AI prompting, which results in hallucinations that could have dire consequences on clinical workflow of healthcare professionals. The impact of prompting patterns on optimization of clinical workflows at points-of-care remains nascent with limited evidence especially in healthcare sectors of sub-Saharan Africa. This review explores existing literature on how generative AI prompt engineering optimizes clinical workflow of healthcare professionals by adopting Arksey and O’Malley five-stage scoping review framework to analyze peer-reviewed publications. A comprehensive search strategy was conducted in scholarly databases, including PubMed, IEEE Xplore, and Google Scholar between 2019 and 2025. The study highlights AI prompt engineering strategies, how prompting affects clinical and administrative activities, and how limitations of generative AI prompting could be addressed. Evidence of generative AI prompt engineering are limited in SSA while the Global North and China are the most dominant regions in the discourse. Consultations, clinical decision support, record summaries and documentation, research and prescription recommendations are leading activities in which AI prompting is perceived as most significant. To conclude, this study provides insights for health managers, healthcare professionals, data scientists, ethicists, health IT experts, human-computer interaction practitioners, and researchers on standardizing integration of generative AI use at points-of-care.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)