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3/12/2025 |
3:30 PM – 5:00 PM |
Urban
S29: Clinical Research Informatics: Managing new models, data, and infrastructure
Presentation Type: Podium Abstract
2025 Informatics Summit On Demand
Session Credits: 1.5
Session Chair:
Eric Hall, PhD, MBA, FAMIA - Nemours Children's Health
SmartState: An Automated Research Protocol Adherence System
2025 Informatics Summit On Demand
Presentation Time: 03:30 PM - 03:45 PM
Abstract Keywords: Informatics Research/Biomedical Informatics Research Methods, Machine Learning, Generative AI, and Predictive Modeling, Clinical and Research Data Collection, Curation, Preservation, or Sharing, Patient-centered Research and Care, Natural Language Processing
Primary Track: Data Science/Artificial Intelligence
Programmatic Theme: Digital Health Technologies for Patient Research
Developing and enforcing study protocols is crucial in medical research, especially as interactions with participants become more intricate. Traditional rules-based systems struggle to provide the automation and flexibility required for real-time, personalized data collection. We introduce SmartState, a state-based system designed to act as a personal agent for each participant, continuously managing and tracking their unique interactions. Unlike traditional reporting systems, SmartState enables real-time, automated data collection with minimal oversight. By integrating large language models to distill conversations into structured data, SmartState reduces errors and safeguards data integrity through built-in protocol and participant auditing. We demonstrate its utility in research trials involving time-dependent participant interactions, addressing the increasing need for reliable automation in complex clinical studies.
Speaker(s):
Samuel Armstrong, MS
University of Kentucky
Author(s):
Samuel Armstrong, MS - University of Kentucky; Mitchell Klusty, B.S. Computer Science - University of Kentucky; Aaron Mullen, B.S. - University of Kentucky; Jeffery Talbert, PhD - University of Kentucky; Cody Bumgardner, PhD - University of Kentucky;
2025 Informatics Summit On Demand
Presentation Time: 03:30 PM - 03:45 PM
Abstract Keywords: Informatics Research/Biomedical Informatics Research Methods, Machine Learning, Generative AI, and Predictive Modeling, Clinical and Research Data Collection, Curation, Preservation, or Sharing, Patient-centered Research and Care, Natural Language Processing
Primary Track: Data Science/Artificial Intelligence
Programmatic Theme: Digital Health Technologies for Patient Research
Developing and enforcing study protocols is crucial in medical research, especially as interactions with participants become more intricate. Traditional rules-based systems struggle to provide the automation and flexibility required for real-time, personalized data collection. We introduce SmartState, a state-based system designed to act as a personal agent for each participant, continuously managing and tracking their unique interactions. Unlike traditional reporting systems, SmartState enables real-time, automated data collection with minimal oversight. By integrating large language models to distill conversations into structured data, SmartState reduces errors and safeguards data integrity through built-in protocol and participant auditing. We demonstrate its utility in research trials involving time-dependent participant interactions, addressing the increasing need for reliable automation in complex clinical studies.
Speaker(s):
Samuel Armstrong, MS
University of Kentucky
Author(s):
Samuel Armstrong, MS - University of Kentucky; Mitchell Klusty, B.S. Computer Science - University of Kentucky; Aaron Mullen, B.S. - University of Kentucky; Jeffery Talbert, PhD - University of Kentucky; Cody Bumgardner, PhD - University of Kentucky;
Human-Centered Design of the Vanderbilt Algorithmovigilance Monitoring and Operations System
2025 Informatics Summit On Demand
Presentation Time: 03:45 PM - 04:00 PM
Abstract Keywords: Implementation Science and Deployment, Machine Learning, Generative AI, and Predictive Modeling, Advanced Data Visualization Tools and Techniques
Primary Track: Data Science/Artificial Intelligence
Programmatic Theme: Implementation Science and Deployment in Informatics: Enabling Clinical and Translational Research
As AI adoption in healthcare grows, there is an increasing need for continuous monitoring after implementation, known as algorithmovigilance. While existing tools provide some support, few systems enable comprehensive proactive oversight and governance of AI across a healthcare system. This study outlines the human-centered design process used to develop the Vanderbilt Algorithmovigilance Monitoring and Operations System (VAMOS). We describe key insights and design recommendations to guide the development of robust algorithmovigilance tools for healthcare institutions.
Speaker(s):
Megan Salwei, PhD
Vanderbilt University Medical Center
Author(s):
Sharon Davis, PhD - Vanderbilt University Medical Center; Carrie Reale, MSN, RN-BC - Vanderbilt University Medical Center; Laurie Novak, PhD - Vanderbilt University Medical Center Dept of Biomedical Informatics; Colin Walsh, MD MA - Department of Biomedical Informatics, Vanderbilt University; Scott Nelson, PharmD, MS, FAMIA, ACHIP - Vanderbilt University Medical Center; Russ Beebe, BA - Vanderbilt University Medical Center; Peter Embi, MD - VUMC;
2025 Informatics Summit On Demand
Presentation Time: 03:45 PM - 04:00 PM
Abstract Keywords: Implementation Science and Deployment, Machine Learning, Generative AI, and Predictive Modeling, Advanced Data Visualization Tools and Techniques
Primary Track: Data Science/Artificial Intelligence
Programmatic Theme: Implementation Science and Deployment in Informatics: Enabling Clinical and Translational Research
As AI adoption in healthcare grows, there is an increasing need for continuous monitoring after implementation, known as algorithmovigilance. While existing tools provide some support, few systems enable comprehensive proactive oversight and governance of AI across a healthcare system. This study outlines the human-centered design process used to develop the Vanderbilt Algorithmovigilance Monitoring and Operations System (VAMOS). We describe key insights and design recommendations to guide the development of robust algorithmovigilance tools for healthcare institutions.
Speaker(s):
Megan Salwei, PhD
Vanderbilt University Medical Center
Author(s):
Sharon Davis, PhD - Vanderbilt University Medical Center; Carrie Reale, MSN, RN-BC - Vanderbilt University Medical Center; Laurie Novak, PhD - Vanderbilt University Medical Center Dept of Biomedical Informatics; Colin Walsh, MD MA - Department of Biomedical Informatics, Vanderbilt University; Scott Nelson, PharmD, MS, FAMIA, ACHIP - Vanderbilt University Medical Center; Russ Beebe, BA - Vanderbilt University Medical Center; Peter Embi, MD - VUMC;
From Scanner to Science: Reusing Clinically Acquired Medical Images for Research
2025 Informatics Summit On Demand
Presentation Time: 04:00 PM - 04:15 PM
Abstract Keywords: Clinical and Research Data Collection, Curation, Preservation, or Sharing, Collaborative Workflow Systems, Data/System Integration, Standardization and Interoperability, Sustainable Research Data Infrastructure
Primary Track: Clinical Research Informatics
Programmatic Theme: Emerging Best Practices for Clinical Research Informatics Operations
Growth in the field of medical imaging research has revealed a need for larger volume and variety in available data. This need could be met using curated clinically acquired data, but the process for getting this data from the scanners to the scientists is complex and lengthy. We present a manifest-driven modular Extract, Transform, and Load (ETL) process named Locutus designed to appropriately handle difficulties present in the process of reusing clinically acquired medical imaging data. Based on four foundational assumptions about medical data, research data, and communication, Locutus presents a five-phase workflow for downloading, de-identifying, and delivering unique requests for imaging data. To date, this workflow has been used to process over 27,000 imaging accessions for research use. This number is expected to grow as technical challenges are addressed and the role of humans is expected to shift from frequent intervention to regular monitoring.
Speaker(s):
Remo M. S. Williams, MS
Children's Hospital of Philadelphia
Jenna Schabdach, PhD in Biomedical Informatics
Children's Hospital of Philadelphia
Author(s):
Jenna M. Schabdach, PhD, MS - Children's Hospital of Philadelphia; Remo M. S. Williams, MS - Children's Hospital of Philadelphia; Joseph Logan, MS - Children's Hospital of Philadelphia; Viveknarayanan Padmanabhan, MS - Children's Hospital of Philadelphia; Russell D'Aiello, MS - Children's Hospital of Philadelphia; Johnny Mclaughlin, BS - Children's Hospital of Philadelphia; Alexander K. Gonzalez, MS, MBA - Children's Hospital of Philadelphia; Edward M. Krause, MS - Children's Hospital of Philadelphia; Gregory E. Tasian, MD, MD, MSCE - Children's Hospital of Philadelphia; Susan Sotardi, MD, MS - Children's Hospital of Philadelphia; Aaron F. Alexander-Bloch, MD, PhD, MPhil - Children's Hospital of Philadelphia;
2025 Informatics Summit On Demand
Presentation Time: 04:00 PM - 04:15 PM
Abstract Keywords: Clinical and Research Data Collection, Curation, Preservation, or Sharing, Collaborative Workflow Systems, Data/System Integration, Standardization and Interoperability, Sustainable Research Data Infrastructure
Primary Track: Clinical Research Informatics
Programmatic Theme: Emerging Best Practices for Clinical Research Informatics Operations
Growth in the field of medical imaging research has revealed a need for larger volume and variety in available data. This need could be met using curated clinically acquired data, but the process for getting this data from the scanners to the scientists is complex and lengthy. We present a manifest-driven modular Extract, Transform, and Load (ETL) process named Locutus designed to appropriately handle difficulties present in the process of reusing clinically acquired medical imaging data. Based on four foundational assumptions about medical data, research data, and communication, Locutus presents a five-phase workflow for downloading, de-identifying, and delivering unique requests for imaging data. To date, this workflow has been used to process over 27,000 imaging accessions for research use. This number is expected to grow as technical challenges are addressed and the role of humans is expected to shift from frequent intervention to regular monitoring.
Speaker(s):
Remo M. S. Williams, MS
Children's Hospital of Philadelphia
Jenna Schabdach, PhD in Biomedical Informatics
Children's Hospital of Philadelphia
Author(s):
Jenna M. Schabdach, PhD, MS - Children's Hospital of Philadelphia; Remo M. S. Williams, MS - Children's Hospital of Philadelphia; Joseph Logan, MS - Children's Hospital of Philadelphia; Viveknarayanan Padmanabhan, MS - Children's Hospital of Philadelphia; Russell D'Aiello, MS - Children's Hospital of Philadelphia; Johnny Mclaughlin, BS - Children's Hospital of Philadelphia; Alexander K. Gonzalez, MS, MBA - Children's Hospital of Philadelphia; Edward M. Krause, MS - Children's Hospital of Philadelphia; Gregory E. Tasian, MD, MD, MSCE - Children's Hospital of Philadelphia; Susan Sotardi, MD, MS - Children's Hospital of Philadelphia; Aaron F. Alexander-Bloch, MD, PhD, MPhil - Children's Hospital of Philadelphia;
Empowering Precision Medicine for Rare Diseases through Cloud Infrastructure Refactoring
2025 Informatics Summit On Demand
Presentation Time: 04:15 PM - 04:30 PM
Abstract Keywords: Clinical Decision Support for Translational/Data Science Interventions, Data Mining and Knowledge Discovery, Data Integration, FHIR
Working Group: Clinical Research Informatics Working Group
Primary Track: Clinical Research Informatics
Programmatic Theme: Digital Health Technologies for Patient Research
Rare diseases affect approximately 1 in 11 Americans, yet their diagnosis remains challenging due to limited clinical evidence, low awareness, and lack of definitive treatments. Our project aims to accelerate rare disease diagnosis by developing a comprehensive informatics framework leveraging data mining, semantic web technologies, deep learning, and graph-based embedding techniques. However, our on-premises computational infrastructure faces significant challenges in scalability, maintenance, and collaboration. This study focuses on developing and evaluating a cloud-based computing infrastructure to address these challenges. By migrating to a scalable, secure, and collaborative cloud environment, we aim to enhance data integration, support advanced predictive modeling for differential diagnoses, and facilitate widespread dissemination of research findings to stakeholders, the research community, and the public and also proposed a facilitated through a reliable, standardized workflow designed to ensure minimal disruption and maintain data integrity for existing research project.
Speaker(s):
Hui Li, Phd
University of Texas Health Science Center at Houston
Author(s):
2025 Informatics Summit On Demand
Presentation Time: 04:15 PM - 04:30 PM
Abstract Keywords: Clinical Decision Support for Translational/Data Science Interventions, Data Mining and Knowledge Discovery, Data Integration, FHIR
Working Group: Clinical Research Informatics Working Group
Primary Track: Clinical Research Informatics
Programmatic Theme: Digital Health Technologies for Patient Research
Rare diseases affect approximately 1 in 11 Americans, yet their diagnosis remains challenging due to limited clinical evidence, low awareness, and lack of definitive treatments. Our project aims to accelerate rare disease diagnosis by developing a comprehensive informatics framework leveraging data mining, semantic web technologies, deep learning, and graph-based embedding techniques. However, our on-premises computational infrastructure faces significant challenges in scalability, maintenance, and collaboration. This study focuses on developing and evaluating a cloud-based computing infrastructure to address these challenges. By migrating to a scalable, secure, and collaborative cloud environment, we aim to enhance data integration, support advanced predictive modeling for differential diagnoses, and facilitate widespread dissemination of research findings to stakeholders, the research community, and the public and also proposed a facilitated through a reliable, standardized workflow designed to ensure minimal disruption and maintain data integrity for existing research project.
Speaker(s):
Hui Li, Phd
University of Texas Health Science Center at Houston
Author(s):
Data Governance for a Novel Pet-Patient Data Registry
2025 Informatics Summit On Demand
Presentation Time: 04:30 PM - 04:45 PM
Abstract Keywords: Data/System Integration, Standardization and Interoperability, Secondary Use of EHR Data, Data Security and Privacy
Primary Track: Clinical Research Informatics
Programmatic Theme: Emerging Best Practices for Clinical Research Informatics Operations
Significant opportunities for understanding disease co-occurrence across species in coincident households remain untapped. We determined the feasibility of creating a pet-patient registry for analysis of health data from UCHealth patients and their pets who received care at the geographically-adjacent Veterinary Teaching Hospital (CSU-VTH). 12,115 matches were identified, indicating 29% of CSU-VTH clients or a household member were UCHealth patients. Given the favorable linkage results, we describe data governance considerations for establishing secure pet-patient registries.
Speaker(s):
Nadia Saklou, DVM, PhD
Colorado State University
Author(s):
Melissa Haendel, PhD - CU Anschutz; Kathleen Mullen, Postdoctoral fellow/DVM, MS - CU Anschutz; Tracy Webb, DVM, PhD - Colorado State University; Susan VandeWoude, DVM, DACLAM - College of Veterinary Medicine and Biomedical Sciences, Colorado State University; Sheila McMullan, MLS, JD - CVMBS, Colorado State University;
2025 Informatics Summit On Demand
Presentation Time: 04:30 PM - 04:45 PM
Abstract Keywords: Data/System Integration, Standardization and Interoperability, Secondary Use of EHR Data, Data Security and Privacy
Primary Track: Clinical Research Informatics
Programmatic Theme: Emerging Best Practices for Clinical Research Informatics Operations
Significant opportunities for understanding disease co-occurrence across species in coincident households remain untapped. We determined the feasibility of creating a pet-patient registry for analysis of health data from UCHealth patients and their pets who received care at the geographically-adjacent Veterinary Teaching Hospital (CSU-VTH). 12,115 matches were identified, indicating 29% of CSU-VTH clients or a household member were UCHealth patients. Given the favorable linkage results, we describe data governance considerations for establishing secure pet-patient registries.
Speaker(s):
Nadia Saklou, DVM, PhD
Colorado State University
Author(s):
Melissa Haendel, PhD - CU Anschutz; Kathleen Mullen, Postdoctoral fellow/DVM, MS - CU Anschutz; Tracy Webb, DVM, PhD - Colorado State University; Susan VandeWoude, DVM, DACLAM - College of Veterinary Medicine and Biomedical Sciences, Colorado State University; Sheila McMullan, MLS, JD - CVMBS, Colorado State University;
A Standardized Guideline for Assessing Extracted Electronic Health Records Cohorts: A Scoping Review
2025 Informatics Summit On Demand
Presentation Time: 04:45 PM - 05:00 PM
Abstract Keywords: Cohort Discovery, Informatics Research/Biomedical Informatics Research Methods, Secondary Use of EHR Data, EHR-based Phenotyping
Primary Track: Clinical Research Informatics
Programmatic Theme: Emerging Best Practices for Clinical Research Informatics Operations
Assessing how accurately a cohort extracted from Electronic Health Records (EHR) represents the intended target population, or cohort fitness, is critical but often overlooked in secondary EHR data use. This scoping review aimed to (1) identify guidelines for assessing cohort fitness and (2) determine their thoroughness by examining whether they offer sufficient detail and computable methods for researchers. This scoping review follows the JBI guidance for scoping reviews and is refined based on the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR) checklists. Searches were performed in Medline, Embase, and Scopus. From 1,904 results, 30 articles and 2 additional references were reviewed. Nine articles (28.13%) include a framework for evaluating cohort fitness but only 5 (15.63%) contain sufficient details and quantitative methodologies. Overall, a more comprehensive guideline that provides best practices for measuring the cohort fitness is still needed.
Speaker(s):
Nattanit Songthangtham, PhD Health Informatics
University of Minnesota Twin Cities
Author(s):
Ratchada Jantraporn, MSN, RN - University of Minnesota School of Nursing; Elizabeth Weinfurter, MLIS - University of Minnesota; Gyorgy Simon, PhD; Wei Pan, PhD - University of Minnesota; Sripriya Rajamani, MBBS, MPH, PhD, FAMIA - University of Minnesota; Steve Johnson, PhD - University of Minnesota;
2025 Informatics Summit On Demand
Presentation Time: 04:45 PM - 05:00 PM
Abstract Keywords: Cohort Discovery, Informatics Research/Biomedical Informatics Research Methods, Secondary Use of EHR Data, EHR-based Phenotyping
Primary Track: Clinical Research Informatics
Programmatic Theme: Emerging Best Practices for Clinical Research Informatics Operations
Assessing how accurately a cohort extracted from Electronic Health Records (EHR) represents the intended target population, or cohort fitness, is critical but often overlooked in secondary EHR data use. This scoping review aimed to (1) identify guidelines for assessing cohort fitness and (2) determine their thoroughness by examining whether they offer sufficient detail and computable methods for researchers. This scoping review follows the JBI guidance for scoping reviews and is refined based on the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR) checklists. Searches were performed in Medline, Embase, and Scopus. From 1,904 results, 30 articles and 2 additional references were reviewed. Nine articles (28.13%) include a framework for evaluating cohort fitness but only 5 (15.63%) contain sufficient details and quantitative methodologies. Overall, a more comprehensive guideline that provides best practices for measuring the cohort fitness is still needed.
Speaker(s):
Nattanit Songthangtham, PhD Health Informatics
University of Minnesota Twin Cities
Author(s):
Ratchada Jantraporn, MSN, RN - University of Minnesota School of Nursing; Elizabeth Weinfurter, MLIS - University of Minnesota; Gyorgy Simon, PhD; Wei Pan, PhD - University of Minnesota; Sripriya Rajamani, MBBS, MPH, PhD, FAMIA - University of Minnesota; Steve Johnson, PhD - University of Minnesota;