Systematic design and data-driven evaluation of social determinants of health ontology (SDoHO)
Yifang Dang and others, Systematic design and data-driven evaluation of social determinants of health ontology (SDoHO), Journal of the American Medical Informatics Association, Volume 30, Issue 9, September 2023, Pages 1465–1473.
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Presenters
Yifang Dang
Yifang Dang, who graduated magna cum laude in health sciences from Texas A&M Corpus Christi and gained master’s degree in biomedical informatics at the University of Texas Health Science Center at Houston, is deeply committed to bridging gaps in healthcare. After gaining practical experience at the Houston Health Department, she returned to academia for her PhD, where she developed a keen interest in Social Determinants of Health (SDoH). Recognizing discrepancies in this field, Yifang focuses on using ontologies to standardize SDoH data, aiming to adhere to FAIR principles and thereby promote health equity. With a foot in both practical and academic worlds, she hopes to make meaningful contributions to a more equitable healthcare landscape.
Cui Tao, PhD
Dr. Tao is the Dr. Doris Ross Professor of Biomedical Informatics at University of Texas Health Science Center at Houston (UTHealth), McWilliams School of Biomedical Informatics. She also directs the Center of Biomedical Semantics and Data Intelligence. She is an elected fellow of the American College of Medical Informatics and a recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE). Dr. Tao is an expert in AI and informatics with focus on big biomedical data normalization, integration, and analysis.
Dr. Tao and her team possess vast experience in constructing and assessing various biomedical ontologies. They have spearheaded the development of ontologies for diverse purposes, including drug repurposing, phenotyping, nutrition, vaccination, social networks, and more. In addition, they also focus on build innovative AI methods for different applications such as clinical decision support, clinical trial simulation, drug repurposing, vaccine/drug safety analysis, and patient-provider communication.
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.
Format
- 35-minute presentation by article author(s) considering salient features of the published study and its potential impact on practice
- 25-minute discussion of questions submitted by listeners via the webinar tools and moderated by JAMIA Student Editorial Board members.
Accreditation Statement
The American Medical Informatics Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.
Credit Designation Statement
The American Medical Informatics Association designates this live activity for a maximum of 1.0 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.