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Developing a Childhood Asthma Risk Passive Digital Marker
Sponsor: Indiana University
Summary
Underdiagnosis and undertreatment is a major problem in childhood asthma management, especially in preschool-aged children. Current prognostic approaches using risk-score based tools have poor-to-modest accuracy, are impractical, and have limited evidence of efficacy in clinical settings and hence are not widely used in practice. The objective of the study is to determine the usability, acceptability, feasibility, and preliminary efficacy of the childhood asthma passive digital marker (PDM) among pediatricians. The study will include practicing pediatricians within the IU Health Network.
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
INTERVENTIONAL
Enrollment
34
Start Date
2024-06-01
Completion Date
2025-06-16
Last Updated
2026-07-21
Healthy Volunteers
Yes
Conditions
Interventions
Childhood Asthma Passive Digital Marker
A childhood asthma Passive Digital Marker (PDM) is an ML algorithm that is able to retrieve and synthesize pre-existing "passively" collected mother/child dyad prognostic data in "digital" electronic health record (EHR) to provide an objective and quantifiable "marker" of a child's risk (probability) and associated pathophysiological phenotype to inform clinician decision-making at point-of-care.
Locations (1)
Indiana University
Indianapolis, Indiana, United States