About this trial
The goal of this trial is to learn if a machine learning (ML) model can help optimize drug therapy in the pediatric population. The main question\[s\] it aims to answer are whether a machine learning model predicting receipt of a targeted medication within the next three months:
* Increases the offering of pharmacogenetic testing prior to receipt of a targeted medication * Increases the number of patients with pharmacogenetic results prior to receipt of a targeted medication * Increases the number of patients who have alteration in medication choice or dose based on pharmacogenetic results
This trial only focuses on the prediction and provision of participants with a high-risk of receiving a medication with a pharmacogenetic indication in the next three months.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Inpatient at The Hospital for Sick Children
Between 6 months to 18 years old
Disqualifiers
Prior pharmacogenetic testing and/or prior receipt of a targeted medication
Current Intensive Care Unit (ICU) admission
Expected hospital discharge is prior to midnight on the day of admission
Trial design
Single group
Treatments tested in this trial
ML-based intervention
Other interventionA ML-based model will predict and identify participants that are at high-risk of receiving a targeted medication within three months after their hospital admission date.
Treatment groups
Trial outcomes
Primary outcomes
Proportion of Patients with Pharmacogenetic Testing
The primary outcome will be the proportion of patients with pharmacogenetic testing offered among those who receive a medication with a pharmacogenetic indication within three months of prediction time. Testing must be offered prior to receipt of the first targeted medication.
Secondary outcomes
Number of patients with pharmacogenetic results available prior to receipt of targeted medication
Measured via chart review
Number of patients who have alteration in medication choice or dose based on pharmacogenetic results
Measured via chart review
Sponsors and contacts
Click on the lead sponsor to view all of their trials.