Algorithms For Treatment of Major Depressive Disorder: Efficacy and Cost-Effectiveness

Author:

Bauer Michael1,Rush A.234,Ricken Roland5,Pilhatsch Maximilian1,Adli Mazda56

Affiliation:

1. Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Medical Faculty, Technische Universität Dresden, Dresden, Germany

2. Duke-National University of Singapore, Singapore

3. Department of Psychiatry, Duke University Medical School, Durham, NC, USA

4. Department of Psychiatry, Texas Tech Health Science Center, Permian Basin, TX, USA

5. Department of Psychiatry and Psychotherapy, Charité – Universitätsmedizin Berlin, Campus Mitte, Germany

6. Fliedner Klinik Berlin, Center for Psychiatry, Psychotherapy and Psychosomatic Medicine, Berlin, Germany

Abstract

AbstractIn spite of multiple new treatment options, chronic and treatment refractory courses still are a major challenge in the treatment of depression. Providing algorithm-guided antidepressant treatments is considered an important strategy to optimize treatment delivery and avoid or overcome treatment-resistant courses of major depressive disorder (MDD). The clinical benefits of algorithms in the treatment of inpatients with MDD have been investigated in large-scale, randomized controlled trials. Results showed that a stepwise treatment regimen (algorithm) with critical decision points at the end of each treatment step based on standardized and systematic measurements of response and an algorithm-guided decision-making process increases the chances of achieving remission and optimizes prescription behaviors for antidepressants. In conclusion, research in MDD revealed that systematic and structured treatment procedures, the diligent assessment of response at critical decision points, and timely dose and treatment type adjustments make the substantial difference in treatment outcomes between algorithm-guided treatment and treatment as usual.

Publisher

Georg Thieme Verlag KG

Subject

Pharmacology (medical),Psychiatry and Mental health,General Medicine

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