CI

At a glance

ClinicalIndex Comparison Record
N/ACompleted· 536 enrolled
Drug / intervention
Clinical Decision Supportbehavioral
Likely dose
Not stated in record
Structured eligibility isn't available for this trial yet — see the full criteria in the Eligibility tab below.

Standardized by ClinicalIndex from the ClinicalTrials.gov record · verify against the source.

Search/NCT06033079
NCT06033079N/ACompleted
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Improving CarE for Community Acquired Pneumonia 1 (ICE-CAP1): Prognostic Decision Support

Vanderbilt University Medical Center·interventional·Posted Sep 13, 2023·Updated Dec 5, 2023

In Brief

A clinical study evaluating Clinical Decision Support for Pneumonia Childhood. Completed, enrolled 536 participants across 1 site.

Detailed Summary

Children with pneumonia presenting to the emergency department at Monroe Carell Jr. Children's Hospital at Vanderbilt or Children's Hospital of Pittsburgh will be potentially eligible for study. During intervention periods, providers caring for enrolled children will be presented with a detailed decision support strategy that emphasizes management in accordance with national guideline recommendations. The anticipated study duration is 24 months and, as this study does not include direct contact with enrolled subjects, there is no anticipated follow up.

Study Details

Study Typeinterventional
Allocation--
Masking--
Primary Purpose--
ConditionsPneumonia Childhood
CountriesUnited States
CollaboratorsNational Institute of Allergy and Infectious Diseases (NIAID), University of Pittsburgh Medical Center

Timeline

N/ACompletedFinished
202120222023202420252026
First PostedSep 13, 2023
Enrollment StartNov 20, 2020
Primary CompletionNov 30, 2022
TodayJul 2, 2026
Enrollment to primary: 2.0 yearsPosted 2.8 years ago

Interventions

Clinical Decision Supportbehavioral

For enrolled subjects assigned to the decision support arm, providers will receive prognostic information derived using our previously validated and best performing model. The decision support application will automatically calculate predicted risk for moderate (intensive care) and severe (respiratory failure or shock) outcomes using the parameters derived from the prognostic tool's regression equation. Outcome probabilities will be integrated into the decision support application and displayed within the EHR.