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Pharmacopsychiatry 2003; 36: 222-229
DOI: 10.1055/s-2003-45134
Original Paper
© Georg Thieme Verlag Stuttgart · New York

Algorithms for Optimizing the Treatment of Depression: Making the Right Decision at the Right Time

M. Adli1 , A. J. Rush2 , H.-J. Möller3 , M. Bauer1
  • 1Department of Psychiatry and Psychotherapy, Charité - University Medicine Berlin, Campus Charité-Mitte (CCM), Berlin, Germany
  • 2Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas, USA
  • 3Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-Universität, München, Germany
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Publication History

Publication Date:
15 December 2003 (online)

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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.

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Mazda Adli, MD

Charité - University Medicine Berlin

Campus Charité-Mitte (CCM)

Schumannstr. 20/21

10117 Berlin

Germany

Phone: +4-30-450-517 146

Fax: 030-450-517 962

Email: mazda.adli@charite.de

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