Objective: This study aims to map and analyze how Knowledge Management has been applied in the medical field over the past two decades, identifying consolidated practices, theoretical gaps, and opportunities for integration with emerging technologies. Theoretical Framework: The research is grounded in classical Knowledge Management models (Nonaka Wiig, 1997; Dalkir, 2023) and recent contributions addressing embodied knowledge, organizational learning, and digital transformation in healthcare (Hadjimichael et al., 2024; França et al., 2025). Method: A systematic and bibliometric review was conducted using the PICOC protocol across five indexed databases (PubMed, Scopus, ISI Web of Science, SciELO, and Emerald). The search focused on Knowledge Management-related terms in medical contexts, resulting in a corpus of 317 articles published between 2005 and 2025. Results and Discussion: Knowledge Management is primarily applied in hospital and public health settings, with a strong emphasis on knowledge sharing. Knowledge creation and transfer are underrepresented, as are links to clinical outcomes. Most studies are descriptive, with limited causal analysis. Artificial intelligence, big data, and ontologies appear as emerging but underexplored themes. Research Implications: Future research should connect Knowledge Management to quality and safety metrics, develop specialty-specific models, and explore the role of Knowledge Management in governing AI and data-driven systems in medicine. Originality/Value: This study offers the first comprehensive synthesis of Knowledge Management practices in the medical domain, highlighting critical gaps and proposing a research agenda to strengthen Knowledge Management strategic role in healthcare delivery.
Rengel et al. (Tue,) studied this question.