Systematic design and data-driven evaluation of social determinants of health ontology (SDoHO)
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Presenters
Statement of Purpose
As the significance of Social Determinants of Health (SDoH) becomes increasingly acknowledged, non-medical factors surrounding us profoundly influence our health outcomes. In this growing field, our work serves as a pioneering effort to address the existing discrepancies and bring standardization, making the data utilizable for diverse applications. This article lays the foundational stone for our future endeavors, where our primary aim is to achieve data FAIRness—ensuring that SDoH data are Findable, Accessible, Interoperable, and Reusable for the advancement of health equity and more effective healthcare interventions.
Learning Objectives
- Familiarize with SDoH Concepts: The audiences will become familiar with the fundamental concept of Social Determinants of Health (SDoH) and related terms, enhancing their foundational understanding of the field.
- Understand SDoH Impact and Gaps: The audiences will learn how various SDoH factors influence human health and will gain awareness of existing gaps and disparities in the understanding or application of SDoH.
- Recognize Ontology's Role: The audiences will recognize the crucial role and function of ontology in standardizing and organizing SDoH data, enabling more robust research and applications.
- Learn SDoHO Construction and Evaluation: The audiences will understand how the SDoH Ontology (SDoHO) classes and properties were constructed and evaluated, providing a blueprint for replicating or building upon this work.
- Connect Ontology to Human Text: The audiences will be able to associate the functionalities of the ontology with simulated human text, understanding how ontology can help in the standardized representation of SDoH factors.
- Identify Future Research Factors: The audiences will be equipped to identify specific SDoH factors that should be considered and incorporated into their future research endeavors, fostering a more comprehensive approach to health-related studies.
These objectives aim to provide a well-rounded understanding of SDoH and data standardization techniques, enabling the audiences to apply these learnings in their own research and practice.