This study examines an approach for improving clinician and patient participation in collaborative care to treat depression among people from racial and ethnic minority groups.
What is the research about?
Using implementation science and user centered design methods, the research team will design a multi-level intervention for sustaining collaborative care models. This will include developing and refining an interactive SDM tool to help patients and clinicians decide together if collaborative care for depression is the right treatment approach for the patient. Using a provider level cluster randomized control trial in 5 primary care clinics, the research team will assess the effectiveness of the strategy (technical assistance for care managers, provider education, and an automated SDM process for patients) on provider behavior and patient enrollment in collaborative care, as well as patient adherence to depression treatment and impact on depressive symptoms.
Collaborative care for depression in primary care incorporates depression care managers who provide antidepressant adherence counseling and/or psychotherapy for patients. Collaborative care has been found to greatly improve depression remission, particularly for people from racial and ethnic minority groups, as well as reduce mortality and healthcare costs. However, clinician referral rates to collaborative care and patient engagement rates remain low.
SDM is a collaborative process in which patients and clinicians work together to make healthcare decisions informed by evidence, the care team’s knowledge and experience, and the patient's values, goals, preferences, and circumstances. Family members and caregivers also play an important role in SDM.
Results from this study are forthcoming. Current and future publications from this grant will be posted .
Primary Care Relevance
This study has the potential to produce a scalable electronic SDM (eSDM) tool to effectively improve the sustainability of collaborative care programs.
´óÏóÊÓƵPrimary Care Priority Area
Harnessing data and technology to conduct research on characteristics of primary care that may influence patient outcomes, such as whole person care, care coordination, continuity of care, and comprehensiveness of care.
