title: The role of algorithms in the detection and treatment of depression in primary care.
abstract: Many depressed patients present to primary care physicians instead of psychiatrists, and several studies have found that primary care physicians underdiagnose and undertreat depression. Primary care physicians may fail to diagnose and treat depression for many reasons: depression as it appears in primary care is in many ways a different disease than that seen in the psychiatric setting, and the process of detecting and treating it is different as well. Primary care clinicians face 2 main tasks when addressing depression in routine practice: to accurately identify those patients who are most likely to benefit from antidepressant treatment and to provide the best treatment options possible in the limited time available per visit. Treatment algorithms can be useful, but they are often difficult to apply in primary care. This article reviews the evidence about the detection and treatment of depression in primary care, examines current research on the differences between the primary and specialty care environments, and discusses aspects of treatment guidelines and algorithms that are important to primary care physicians.
authors.affiliation: Briarwood Family Practice Center and the Department of Family Medicine, University of Michigan Health System, Ann Arbor, USA. mklinkma@umich.edu
authors.forename: Michael S
authors.initials: MS
authors.lastname: Klinkman
mesh_terms: D000465:Algorithms; D000928:Antidepressive Agents / Q000627:therapeutic use; D015897:Comorbidity; D003866:Depressive Disorder / Q000175:diagnosis* / Q000188:drug therapy / Q000628:therapy*; D006801:Humans; D017410:Practice Guidelines as Topic; D010818:Practice Patterns, Physicians'; D011320:Primary Health Care / Q000379:methods*; D011570:Psychiatry / Q000379:methods
chemical_list: D000928:Antidepressive Agents