Authors:
Navya Martin Kollapally
1
;
Yan Chen
2
and
James Geller
1
Affiliations:
1
Department of Computer Science, New Jersey Institute of Technology, Newark, U.S.A.
;
2
Department of Computer Information Systems, Borough of Manhattan Community College, New York, U.S.A.
Keyword(s):
Healthcare Inequity, Ontology, Minority, Taxonomy, Ontology Evaluation.
Abstract:
Healthcare inequity, as defined by the World Health Organization (WHO), is a systemic difference in healthcare services received by different population groups, based on race, ethnicity, gender, sexual orientation, etc. The Covid-19 pandemic has heightened the awareness of differences in care received by racial and ethnic minorities in the US. We have investigated the physical, psychological, and emotional harm that people of colour were exposed to during this time. It is necessary to record data about unequal treatment to identify and eradicate existing institutional racism in healthcare. Electronic Health Records (EHRs) rely to a high degree on “coded” terms from terminologies and ontologies. Such a biomedical ontology can be used for standardization, integration and sharing of data, knowledge reuse, decision support, etc. No ontology for racial differences exists in US healthcare. This motivation leads us to the development of such an ontology to record the physical, emotional, an
d psychological effects resulting from differences in treatment that citizens receive, based on their identity. Differences exist not only inside of healthcare organizations, but also occur even before entering them. We present the first version of such a Health Ontology for Minority Equity (HOME) along with ontology evaluation methods that we applied.
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