Validating the B-COMPASS Model to Improve Patient Treatment Adherence and Healthcare Outcomes Across Multiple Diseases and European Countries

What this Trial Is About

This research aims to validate the B-COMPASS, a computational model developed by the BEAMER project to improve patient adherence to treatment across various diseases. Adherence to treatment is a widespread issue leading to increased healthcare use and premature death, with about half of medications not taken as prescribed. The study evaluates the models ability to predict adherence, identify patient support needs, and enhance healthcare engagement in six therapeutic areas, including cardiovascular, endocrinology, immunology, neurology, oncology, and rare diseases. Participants complete the BEAMER questionnaire, which the B-COMPASS uses to group patients based on their adherence needs and predict their adherence. Patients are randomized into a control group receiving standard care or an intervention group receiving enhanced engagement through educational materials for healthcare providers tailored to the patients B-COMPASS profile. Engagement occurs in person or by phone, depending on patient schedules, and healthcare providers may also be randomized to limit knowledge of the B-COMPASS in control groups. Participants are involved in two main data collections spaced from 2 weeks to 6 months apart, during which adherence measures, patient support needs, and perceptions of engagement are assessed. The study measures the accuracy, validity, and reliability of B-COMPASS predictions, its impact on adherence, patient and provider perceptions, and cost-effectiveness. The total participation timeline varies by site and disease area, with continuous monitoring of healthcare utilization and patient experience.

BEhavioral and Adherence Model for Improving Quality, Health Outcomes and Cost-Effectiveness of healthcaRe