The Tailored Adherence Incentives for Childhood Asthma Medications (TAICAM) Trial
The Tailored Adherence Incentives for Childhood Asthma Medications (TAICAM) Trial
Improving adherence to inhaled corticosteroids (ICS) medication in urban minority pediatric populations is a clinical and population health priority. Financial incentives have been shown as a compelling method to engage a high-risk asthma population in regular ICS use, but whether and how adherence can be maintained and lead to sustained high adherence trajectories is unknown.
Investigators propose to initially enroll 125 children into an initial 1-month run-in interval. Participants who successfully complete the run-in interval will be randomized into a six-month intervention with a six month follow-up period. Children will be ages 5-12, and must have two or more visits to any combination of the outpatient, Emergency Department (ED) or hospital setting in the past year for asthma exacerbations at Children's Hospital of Philadelphia (CHOP).
The study intervention will include daily automated medication reminders (either via text message or push reminder), an app to track daily medication use, and nominal incentives to promote daily controller use. Inhaled controller medication adherence and rescue medication use will be measured using electronic monitors affixed to the inhalers. Factors associated with differential adherence will be assessed using surveys administered during enrollment, the experiment interval (months 1 through 3), the observation interval (months 4 through 6), and study completion (months 12-13). Efficacy outcomes will include change in parent-reported asthma control and mean adherence to ICS between study arms during the experiment interval, as well as the observation interval.
Patients will be considered fully enrolled when they fulfill the requirements of the Run-in period (sensor data uploaded to research platform AND text message receipt confirmed by caregiver) and are subsequently randomized.
Inclusion Criteria:
Exclusion Criteria: