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Treatment algorithms are considered as key to improve outcomes by enhancing the quality of care. This is the first randomized controlled study to evaluate the clinical effect of algorithm-guided treatment in inpatients with major depressive disorder.
Inpatients, aged 18 to 70 years with major depressive disorder from 10 German psychiatric departments were randomized to 5 different treatment arms (from 2000 to 2005), 3 of which were standardized stepwise drug treatment algorithms (ALGO).
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In a previous single center study we found that a standardized drug treatment algorithm (ALGO) was more cost effective than treatment as usual (TAU) for inpatients with major depression. This report aimed to determine whether this promising initial finding could be replicated in a multicenter study.
Treatment costs were calculated for two time periods: the study period (from enrolment to exit from study) and time in hospital (from enrolment to hospital discharge) based on daily hospital charges.

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The Texas Medication Algorithm Project is an evaluation of an algorithm-based disease management program for the treatment of the self-declared persistently and seriously mentally ill in the public mental health sector.
To present clinical outcomes for patients with major depressive disorder (MDD) during 12-month algorithm-guided treatment (ALGO) compared with treatment as usual (TAU).
Effectiveness, intent-to-treat, prospective trial comparing patient outcomes in clinics offering ALGO with matched clinics offering TAU.

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Medication algorithms have been proposed as effective means to offer optimal treatment and improved outcome for patients with severe mental illness. This single-center prospective study compared the efficacy and effects on treatment prescriptions of an algorithm-guided treatment regimen with treatment as usual (TAU) in depressed inpatients.
Depressed inpatient participants were randomized to an algorithm-guided standardized stepwise drug treatment regimen (SSTR, n = 74) or TAU (n = 74).

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The Texas Medication Algorithm Project (TMAP) assessed the clinical and economic impact of algorithm-driven treatment (ALGO) as compared with treatment-as-usual (TAU) in patients served in public mental health centers. This report presents clinical outcomes in patients with a history of mania (BD), including bipolar I and schizoaffective disorder, bipolar type, during 12 months of treatment beginning March 1998 and ending with the final active patient visit in April 2000.
Patients were diagnosed with bipolar I disorder or schizoaffective disorder, bipolar type, according to DSM-IV criteria.

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