title: Using treatment algorithms to bring patients to remission.
abstract: Many patients treated with antidepressants fail to achieve full remission, and the costs, both social and economic, of response without remission as well as residual symptoms are high. Patients who experience incomplete remission to antidepressant treatment are candidates for a sequential treatment approach involving treatment options such as switching, augmentation, or combination of antidepressants. Recently, the number of alternatives for treatment has increased substantially. Algorithms and treatment guidelines that synthesize current data and research provide clinicians with a structure when changes in treatment strategy are necessary. Guidelines and algorithms are not designed to take away the clinician's autonomy but instead are intended to provide support for treatment decisions, and effective ones allow for a wide degree of flexibility. It can be easily argued that the use of algorithms with the associated decision support tools increases the role of the clinician in assessment of the clinical status and subsequent treatment choices.
authors.affiliation: St. Paul Hospital, University of Texas Southwest Medical School, Dallas 75235-9101, USA. madhukar.trivedi@utsouthwestern.edu
authors.forename: Madhukar H
authors.initials: MH
authors.lastname: Trivedi
mesh_terms: D000465:Algorithms; D000928:Antidepressive Agents / Q000627:therapeutic use*; D003131:Combined Modality Therapy; D003661:Decision Support Techniques; D003663:Decision Trees; D003866:Depressive Disorder / Q000188:drug therapy / Q000628:therapy*; D004359:Drug Therapy, Combination; D006801:Humans; D011613:Psychotherapy; D013813:Therapy, Computer-Assisted; D016896:Treatment Outcome
chemical_list: D000928:Antidepressive Agents