Changes in Patient-Reported, EHR-Integrated Social Risk Factors among Rheumatology Outpatients

Presentation Time: 03:15 PM - 03:27 PM

Abstract Keywords: Patient / Person Generated Health Data (Patient Reported Outcomes), Health Equity, Public Health, Healthcare Quality, Precision Medicine
Primary Track: Applications
Programmatic Theme: Clinical Research Informatics

Social risk factors (SRFs) are associated with many adverse clinical outcomes, but the degree to which SRFs change over time is not well-understood. In a specialty outpatient population, 341 individuals completed more than one SRF screening. SRFs remained stable over time, with no significant differences between visits in individual domains or proportions of individuals endorsing more than two SRFs. Results highlight the need for interventions to address SRFs and guidelines regarding SRF screening frequency.

Speaker:
Lauren Seidler, BS
Washington University School of Medicine

Lauren Seidler, MS
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Authors:
Daphne Lew, PhD, MPH - Washington University School of Medicine; Patrice Odom, BS - Washington University School of Medicine; Amy McQueen, PhD - Washington University School of Medicine; Seth Eisen, Md, MSc - Washington University School of Medicine; Alfred Kim, MD, PhD - Washington University School of Medicine;

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Cross Biobank Comparison of Phenomic Profiles

Presentation Time: 03:27 PM - 03:39 PM

Abstract Keywords: Precision Medicine, Data Standards, Phenomics and Phenome-wide Association Studies
Primary Track: Applications
Programmatic Theme: Clinical Informatics

The All of Us (AoU) Research Program and UK Biobank (UKBB) boast a wealth of EHR data, which can be harnessed to refine cohort selection via rule-based phenotyping algorithms. The Observational Health Data Sciences and Informatics (OHDSI) Phenotype Library (PL) hosts many complex phenotyping rules. Here, we compare prevalence for 423 OHDSI PL cohorts in AoU and UKBB. For three select diseases (T2D, COPD, Acute MI), we analyze differences in demographics, social determinants of health (SDOH), geographic prevalence, and genome-wide association study (GWAS) results. We found that AoU has a significantly higher prevalence for 80% of phenotypes compared to UKBB. We also found that for the select diseases, SDOH variables between the two biobanks differ significantly. Findings for each of these three diseases confirm known geographic regions of high risk. Additionally, GWAS in UKBB discovered more genes associated with each of the three diseases than GWAS in AoU.

Speaker:
Abigail Newbury, MA
Columbia University Department of Biomedical Informatics

Authors:
Abigail Newbury, MA - Columbia University Department of Biomedical Informatics; Xinzhuo Jiang, MS - Columbia University Department of Biomedical Informatics; Karthik Natarajan, PhD - Columbia University Dept of Biomedical Informatics; Gamze Gursoy, PhD - Columbia University;

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Exploring and Comparing Existing Natural Product Databases Towards Whole Person Health Research

Presentation Time: 03:39 PM - 03:51 PM

Abstract Keywords: Artificial Intelligence, Controlled Terminologies, Ontologies, and Vocabularies, Data Standards, Knowledge Representation and Information Modeling
Primary Track: Foundations

Natural products (NPs) are essential in drug discovery, chemical biology, and medicinal chemistry. Despite their widespread use, NP data remains fragmented across various databases, limiting their utility for whole person health research, which requires comprehensive, interoperable resources. This study explores and compares three major NP databases: COCONUT, NP-MRD, and GSRS, assessing their scope, structural representation, metadata completeness, and accessibility. COCONUT provides extensive chemical diversity, NP-MRD emphasizes spectral and physical property data, and GSRS focuses on regulatory classification. Despite their strengths, overlap between databases is moderate to small, and significant gaps remain in integrating medical and pharmaceutical information. Improved interoperability and harmonization are needed to support advanced computational models for whole person health. Our findings highlight critical gaps and opportunities to enhance NP database integration, laying the groundwork for developing comprehensive resources that better support data-driven investigations of natural products.

Speaker:
Xiaoyi Chen, PhD
Imagine Institute of Genetic Diseases, Paris, France | University of Minnesota, Twin Cities, MN, USA

Authors:
Meijia Song, BSN - University of Minnesota; Yu Hou, PhD - University of Minnesota; Rubina Rizvi, MD, PhD, FAMIA - University of Minnesota; Jeffrey Bishop, PharmD, MS - University of Minnesota; Piper Ranallo, PhD - University of Minnesota; Thomas Hoye, PhD - University of Minnesota; Rui Zhang, PhD, FAMIA, FACMI - University of Minnesota, Twin Cities;

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Developing Common Data Elements for Food Allergy Clinical Trials

Presentation Time: 03:51 PM - 04:03 PM

Abstract Keywords: Data Standards, Interoperability and Health Information Exchange, Standards
Primary Track: Foundations
Programmatic Theme: Clinical Research Informatics

Despite the significant clinical, economic, and quality-of-life burden of food allergy, research in the field is limited by the lack of established common data elements (CDEs). Although the National Institutes of Health has developed a repository for CDEs, CDEs for food allergy are not well represented. The purpose of this study was to develop CDEs for food allergy to provide the consistency that is required for cross-talk between data obtained by diverse studies.

Speaker:
Shruti Sehgal, MD (Hom), MS
Northwestern University

Authors:
Shruti Sehgal, MD (Hom), MS - Northwestern University; Justin Starren, MD, PhD, FACMI - University of Arizona; Kyle Cattin, BA - Northwestern University; Lucy Bilaver, PhD - Northwestern University; Alkis Togias, MD - Division of Allergy, Immunology and Transplantation of the National Institute of Allergy and Infectious Diseases; Ruchi Gupta, MD, MPH - Northwestern University;

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Growth of Epic Cosmos and Epic Research: Implications for Conducting and Publishing Biomedical Research

Presentation Time: 04:03 PM - 04:15 PM

Abstract Keywords: Data Sharing, Delivering Health Information and Knowledge to the Public, Legal, Ethical, Social and Regulatory Issues
Primary Track: Applications
Programmatic Theme: Clinical Informatics

We examined peer-reviewed and other scientific publications as well as research briefs posted on epicresearch.org that report analyses of Epic Cosmos data. Of 257 Epic Research briefs and 53 peer-reviewed and other scientific publications, we identified ten scientific publications directly associated with Epic Research briefs. We summarize manually extracted data about the articles, and discuss positives and negatives of this expansive data platform and associated novel method of dissemination of knowledge.

Speaker:
Katrina Romagnoli, PhD, MS, MLIS
Geisinger

Authors:
Tierney Lyons, MLS - Geisinger College of Health Sciences; Michelle Meyer, PhD, JD - Geisinger College of Health Sciences; David Vawdrey, PhD - Geisinger;

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Extracting Adverse Events Posted in ClinicalTrials.gov Results Database for Evidence Synthesis

Presentation Time: 04:15 PM - 04:27 PM

Abstract Keywords: Clinical Decision Support, Patient Safety, Data Standards, Real-World Evidence Generation, Cancer Prevention
Primary Track: Applications

Adverse event (AE) data in ClinicalTrials.gov provide valuable insights for safety evaluation, but challenges remain in extracting and standardizing this information for large-scale evidence synthesis. We developed CTG Safety, an automated pipeline that structures AE data using standardized terminologies. To demonstrate its utility, we analyzed secondary malignancies in CAR-T therapy trials. By enabling rapid, targeted analysis of AE data, the database supports efficient safety assessments and data-driven decision-making.

Speaker:
Zitao Liang, Undergraduate
Peking University

Authors:
Zitao Liang, Undergraduate - Peking University; Jian Du - Peking University;

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