Rationale and design of theStudy of aTele-pharmacyIntervention forChronic diseases toImproveTreatment adherence (STIC2IT): A cluster-randomized pragmatic trial

    loading  Checking for direct PDF access through Ovid

Abstract

Background

Approximately half of patients with chronic cardiometabolic conditions are nonadherent with their prescribed medications. Interventions to improve adherence have been only modestly effective because they often address single barriers to adherence, intervene at single points in time, or are imprecisely targeted to patients who may not need adherence assistance.

Objective

To evaluate the effect of a multicomponent, behaviorally tailored pharmacist-based intervention to improve adherence to medications for diabetes, hypertension, and hyperlipidemia.

Trial design

The STIC2IT trial is a cluster-randomized pragmatic trial testing the impact of a pharmacist-led multicomponent intervention that uses behavioral interviewing, text messaging, mailed progress reports, and video visits. Targeted patients are those who are nonadherent to glucose-lowering, antihypertensive, or statin medications and who also have evidence of poor disease control. The intervention is tailored to patients' individual health barriers and their level of health activation. We cluster-randomized 14 practice sites of a large multispecialty group practice to receive either the pharmacist-based intervention or usual care. STIC2IT has enrolled 4,076 patients who will be followed up for 12 months after randomization. The trial's primary outcome is medication adherence, assessed using pharmacy claims data. Secondary outcomes are disease control and health care resource utilization.

Conclusion

This trial will determine whether a technologically enabled, behaviorally targeted pharmacist-based intervention results in improved adherence and disease control. If effective, this strategy could be a scalable method of offering tailored adherence support to those with the greatest clinical need.

Related Topics

    loading  Loading Related Articles