Algorithms for optimizing the treatment of depression: making the right decision at the right time.
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.
Duke Scholars
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DOI
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Related Subject Headings
- Psychiatry
- Humans
- Disease Progression
- Depressive Disorder
- Decision Trees
- Decision Making
- Clinical Protocols
- Antidepressive Agents
- Algorithms
- 1115 Pharmacology and Pharmaceutical Sciences
Citation
Published In
DOI
ISSN
Publication Date
Volume
Start / End Page
Location
Related Subject Headings
- Psychiatry
- Humans
- Disease Progression
- Depressive Disorder
- Decision Trees
- Decision Making
- Clinical Protocols
- Antidepressive Agents
- Algorithms
- 1115 Pharmacology and Pharmaceutical Sciences