title: Algorithms for optimizing the treatment of depression: making the right decision at the right time.
abstract: Medication algorithms for the treatment of depression are designed to optimize both treatment implementation and the appropriateness of treatment strategies. Thus, they are essential tools for treating and avoiding refractory depression. Treatment algorithms are explicit treatment protocols that provide specific therapeutic pathways and decision-making tools at critical decision points throughout the treatment process. The present article provides an overview of major projects of algorithm research in the field of antidepressant therapy. The Berlin Algorithm Project and the Texas Medication Algorithm Project (TMAP) compare algorithm-guided treatments with treatment as usual. The Sequenced Treatment Alternatives to Relieve Depression Project (STAR*D) compares different treatment strategies in treatment-resistant patients.
authors.affiliation: Department of Psychiatry and Psychotherapy, Charité - University Medicine Berlin, Campus Charité-Mitte (CCM), Berlin, Germany. mazda.adli@charite.de
authors.forename: M
authors.initials: M
authors.lastname: Adli
authors.forename: A J
authors.initials: AJ
authors.lastname: Rush
authors.forename: H-J
authors.initials: HJ
authors.lastname: Möller
authors.forename: M
authors.initials: M
authors.lastname: Bauer
mesh_terms: D000465:Algorithms; D000928:Antidepressive Agents / Q000627:therapeutic use*; D002985:Clinical Protocols; D003657:Decision Making; D003663:Decision Trees; D003866:Depressive Disorder / Q000175:diagnosis / Q000188:drug therapy*; D018450:Disease Progression; D006801:Humans
chemical_list: D000928:Antidepressive Agents