Treating depression in staff-model versus network-model managed care organizations

OBJECTIVE: To compare primary care providers' depression-related knowledge, attitudes, and practices and to understand how these reports vary for prov iders in staff or group-model managed care organizations (MCOs) compared wi th network-model MCOs including independent practice associations and prefe rred provider organizations. DESIGN: Survey of primary care providers' depression-related practices in 1 996, SETTING AND PARTICIPANTS: We surveyed 410 providers, from 80 outpatient cli nics, in 11 MCOs participating in four studies designed to improve the qual ity of depression care in primary care. MEASUREMENTS AND MAIN RESULTS:We measured knowledge based on depression gui delines, attitudes (beliefs about burden, skill, and barriers) related to d epression, and reported behavior. Providers in both types of MCO are equall y knowledgeable about treating depression (better knowledge of pharmacologi c than psychotherapeutic treatments) and perceive equivalent skills in trea ting depression. However, compared with network-model providers, staff/grou p-model providers have stronger beliefs that treating depression is burdens ome to their practice. While more staff/group-model providers reported time limitations as a barrier to optimal depression treatment, more network-mod el providers reported limited! access to mental health specialty referral a s a barrier. Accordingly, these staff/group-model providers are mole likely to treat patients with major depression through referral (51% vs 38%) or t o assess but not treat (17% vs 7%), and network-model providers are mole li kely to prescribe antidepressants (57% vs 6%) as first-line treatment. CONCLUSIONS: Whereas the providers from staff/group-model MCOs had greater access to and relied more on referral, the providers from network-model org anizations were more likely to treat depression themselves. Given varying a ttitudes and behaviors, improving primary care for the treatment of depress ion will require unique strategies beyond enhancing technical knowledge for the two types of MCOs.