Developing comprehensive hypertension ontology: Addressing data integration gaps to improve healthcare results

Abstract

Objective: Therefore, the objective of this study was to design hypertension ontology with the aim of improving integration of data, representation of knowledge and better decision making in hypertension management. Methods: First, we performed a systematic literature review (SLR) across ten different databases aiming at capturing the essential concepts. Using this extracted data a Hypertension Ontology (HPO) was created in Protégé which was loaded and published on BioPortal for availability. Results: HPO contains 114 classes and five properties that structure the risk factors, symptoms, diagnosis, and treatment. It improves knowledge discovery, data sharing capabilities, and surpasses existing hypertension-related ontologies in functionality. Conclusion: HPO facilitates standardized hypertension management in a research context and clinical practices. Next Steps will be integration of Real-world data and Interoperability to HER.