Cloud-Based Registry: Advancing CDH Research & Collaboration

Poster Number: P57
Presentation Time: 05:00 PM - 06:30 PM

Abstract Keywords: Bioinformatics, Clinical Guidelines, Data Sharing, Pediatrics, Clinical Decision Support, Clinical Guidelines, Patient / Person Generated Health Data (Patient Reported Outcomes), Disease Models
Working Group: Clinical Decision Support Working Group
Primary Track: Applications
Programmatic Theme: Clinical Informatics

Background: Congenital diaphragmatic hernia (CDH), a rare anomaly causing partial or complete diaphragm absence, hinders lung development in newborns, with an incidence of 1 in 2,500 to 1 in 3,000 live births. Established in 1995, the Congenital Diaphragmatic Hernia Study Group (CDHSG) collects global data, advocating for multidisciplinary management across 147 centers worldwide. To address data management gaps, we aim to create a scalable, secure, and accessible cloud infrastructure for CDH patient data. This initiative seeks to foster global collaboration, enable predictive modeling for patient outcomes, and advance personalized treatment strategies for CDH. We constructed the CDH registry on a cloud platform providing efficient database management, machine learning, data analysis, encryption, access control, a user-friendly web interface, and an API for data exchange. This design enhances usability and information dissemination within and beyond the CDH community.
By June 2023, the CDH Study Group (CDHSG) had registered over 14,000 patients globally, establishing a leading CDH patient database. Initial analyses have revealed insights into treatment outcomes determinants and opportunities for clinical practice enhancements. The scalable infrastructure supports ongoing data repository expansion and the integration of advanced analytics, including machine learning predictive models for outcome estimation based on patient traits and treatments. The CDHSG consolidates patient data from various sources, including clinical diagnoses, longitudinal studies, registries, and electronic health records. Future plans involve leveraging the database and foster connections with other organizations. Standardizing and amalgamating data aim to develop tools accessible to the wider community, expediting drug development and other advancements.

Speaker(s):
jinlian wang, PhD
UTHealth

Author(s):
Hui Li, Phd - University of Texas Health Science Center at Houston; Matthew Harting, MD, PhD - McGovern Medical School at the University of Texas Health Science Center at Houston; Hongfang Liu, PhD - University of Texas Health Science Center at Houston;