title: Using treatment algorithms for the effective management of treatment-resistant depression.
abstract: Increasingly, clinicians are looking to evidence-based medicine for information about treatment options. Treatment algorithms have been used with a variety of psychiatric disorders to assist physicians in making treatment decisions. The direct, prescriptive nature of algorithms also makes them suitable for use in treatment-resistant depression. Two major projects, the Texas Medication Algorithm Project and Sequenced Treatment Alternatives to Relieve Depression, have begun to address the questions of sequenced treatment options. Future directions for algorithm development and implementation are discussed.
authors.affiliation: Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas 75390-9101, USA. madhukar.trivedi@utsouthwestern.edu
authors.forename: M H
authors.initials: MH
authors.lastname: Trivedi
authors.forename: B A
authors.initials: BA
authors.lastname: Kleiber
mesh_terms: D000465:Algorithms; D000928:Antidepressive Agents / Q000627:therapeutic use; D015283:Citalopram / Q000627:therapeutic use; D019091:Critical Pathways / Q000706:statistics & numerical data; D003661:Decision Support Techniques; D003866:Depressive Disorder / Q000523:psychology / Q000628:therapy*; D004334:Drug Administration Schedule; D004359:Drug Therapy, Combination; D019317:Evidence-Based Medicine / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D010342:Patient Acceptance of Health Care; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data; D017367:Selective Serotonin Reuptake Inhibitors; D016896:Treatment Outcome
chemical_list: D000928:Antidepressive Agents; D015283:Citalopram; D017367:Selective Serotonin Reuptake Inhibitors