Timely Ordering of Pharmacogenetic Testing

Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age6-18
SponsorThe Hospital for Sick Children

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

Qualifiers

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

Treatments tested in this trial

  • ML-based intervention

Treatment groups

275 Participants
are divided into 1 treatment group

Sponsors and collaborators