Organizations are increasingly incorporating new strategies to ensure that the complex processes involved in the healthcare sector are comprehensively understood and enhanced. This includes the adoption of process mining (PM) and process simulation (PS), which have been used separately or in combination with one another in the healthcare field to assist decision-makers in process optimization. Although both PM and PS have provided a number of valuable contributions to healthcare, analysis in existing literature is lacking regarding analysis of the benefits, limitations, and tools derived from their combination thereof. The present article conducts a literature review, based on the PRISMA methodology, in which both disciplines are analyzed in terms of their application to healthcare. By reviewing distinct scholarly databases, 31 research studies were selected for analysis, from which it was possible to characterize case studies, techniques, tools, perspectives and algorithms, as well as to identify key limitations. The results indicate a stronger focus on medical fields including cardiology and emergency departments, with a preference for software tools, such as ProM, Disco, Arena, and CPN Tools. The use of real data predominates across the research studies, and the two most commonly identified and detailed limitations in the analysis relate to data quality issues and the involvement of healthcare experts throughout the analysis. Moreover, there is an increasing interest in the publications of papers on these topics within Latin America. Finally, through the findings of the present article have led the authors to propose several opportunities for future research. For example, the compilation of case studies in relation to medical fields that have been historically overlooked, and the availability of software that integrates PM and PS, in addition to the extent to which the usefulness of this combination may improve as a result in the field of healthcare.