Much research has been done in the last few decades in clinical research, medicine, life sciences, etc. leading to an exponential increase in the generation of data. Managing this vast information not only requires integration of the data, but also a means to analyze, relate, and retrieve it. Ontology, in the field of medicine, describes the concepts of medical terminologies and the relation between them, thus, enabling the sharing of medical knowledge. Ontology-based analyses are associated with a risk that errors in modeling may deteriorate the results' quality. Identifying flawed practices or anomalies in ontologies is a crucial issue to be addressed by researchers. In this paper, we review the negative sides of ontology in the field of medicine. Our study results show that ontologies are perceived as a mere tool to represent medical knowledge, thus relying more on the computer science-based understanding of medical terms. While this approach may be sufficient for data entry systems, in which the users merely need to browse the hierarchy and select relevant terms, it may not suffice the real-world scenario of dealing with complex patient records, which are not only grammatically complex, but also are sometimes documented in many native languages. In conclusion, more research is required in identifying poor practices and anomalies in the development of ontologies by computer scientists within the field of medicine.