Healthcare organizations have undergone significant change, particularly in recent decades, leading to a significant increase in complexity. As a result, decision-making has become more challenging as healthcare managers have to deal with multiple interdependent factors (such as patient care, human resources, technology and infrastructure, financial and budget management, and regulatory compliance), often with incomplete or uncertain information. This paper aims to review studies on decision-making in healthcare management, linking these two concepts. Through a bibliometric analysis, this research identifies emerging trends in the field and ways to overcome difficulties in information management. Data were collected from the Scopus database (1140 documents) and analyzed using VOSviewer software. The study identifies two levels of decision-making, the clinical and the operational. The results show a sharp increase in research and highlight emerging trends related to artificial intelligence, machine learning and big data. These trends are transforming healthcare management, restructuring operations, improving decision-making, and ultimately improving patient care while reducing costs.