Developing a Childhood Asthma Risk Passive Digital Marker

Study Overview
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Brief Summary
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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.

Official Title
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Developing a Childhood Asthma Risk Passive Digital Marker

Conditions
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Pediatric Asthma

Intervention / Treatment
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* Other: Childhood Asthma Passive Digital Marker


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: • Practicing pediatricians within the IU Health Network Exclusion Criteria: • Non-practicing pediatricians within the IU Health Network

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Screening
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Single


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| No Intervention: Control Clinicians - post test only<br>N=25 control pediatric clinicians, who will receive the post test only. Each clinician will be presented with 10 randomly selected vignettes of 10 children [5 with and 5 without asthma] and asked to provide a prediction of a child's asthma risk at 6-10 years. | |
| Experimental: PDM Intervention Clinicians - post test only<br>N=25 intervention pediatric clinicians, who will receive the post test only. Using the PDM, each clinician will be presented with 10 randomly selected vignettes of 10 children [5 with and 5 without asthma] and asked to provide a prediction of a child's asthma risk at 6-10 years. | Other: Childhood Asthma Passive Digital Marker<br>* 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.<br>* Other names: Passive Screening Test (PDM);|
| No Intervention: Control Clinicians - pre and post test<br>N=25 control pediatric clinicians, who will receive the pre and post test. Each clinician will be presented with 10 randomly selected vignettes of 10 children [5 with and 5 without asthma] and asked to provide a prediction of a child's asthma risk at 6-10 years. | |
| Active Comparator: PDM Intervention Clinicians - pre and post test<br>N=25 intervention pediatric clinicians, who will receive the pre and post test. Using the PDM, each clinician will be presented with 10 randomly selected vignettes of 10 children [5 with and 5 without asthma] and asked to provide a prediction of a child's asthma risk at 6-10 years. | Other: Childhood Asthma Passive Digital Marker<br>* 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.<br>* Other names: Passive Screening Test (PDM);|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Perceived PDM acceptance | Perceived PDM acceptance will be measured using a Behavioral Intention scale (BIS). | 8 to 12 months | 
| Perceived PDM usability | Perceived Usability will be measured using a modified Simplified System Usability Scale (SUS). | 8 to 12 months | 
| Study feasibility | Percent of successful study enrollment of eligible clinicians (>80%) | 8 to 12 months | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Prognostic accuracy | % correct clinician predictions at pre and post test | 3 to 12 months | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Pediatric Asthma, Early Detection, Screening, Passive Digital Marker, Risk Factors