Societal or institutional identity assignments often create a disconnect between patients and healthcare providers, perpetuating biases in medical treatment. Addressing this gap is essential for fostering equitable and respectful care for all individuals, transcending societal norms. This study evaluates the limitations and ambiguities in existing semantic terminologies, specifically within LOINC and SNOMED CT, as applied to the Diversity Minimal Item Set (DiMIS) diversity domains. Suitability of SNOMED CT and LOINC was assessed using the scoring system ISO/TS 21564, and intercoder reliability was evaluated between two independent mapping specialists. The analysis revealed that while the majority of data items had either a complete or partial equivalent in SNOMED CT or LOINC, while 34% and 19% of items, respectively, could not be mapped. Intercoder reliability was low, potentially due to the limited percentage of concepts with equivalent meaning (30% for LOINC and 36% for SNOMED CT). These findings highlight critical gaps where current terminologies inadequately represent diverse identities, emphasizing the need for updates and enhancements to support evolving, patient-defined descriptors within a rapidly changing medical data landscape.