Efficacy of an Algorithm-Guided Treatment Compared With Treatment as Usual

Abstract

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). The SSTR regimen included sleep deprivation, antidepressant monotherapy, lithium augmentation, monoamine oxidase inhibitor therapy, or electroconvulsive therapy guided by scores on the clinician-rated Bech-Rafaelsen Melancholia Scale. The primary outcome was time to remission (defined as a Bech-Rafaelsen Melancholia Scale score of < or =7). Secondary outcomes were remission rates, number of changes in treatment strategies (types), and the number of different prescribed medications over the treatment period. Patients receiving SSTR had a significantly shorter time to remission (7.0 +/- 0.9 weeks vs 12.3 +/- 1.8 weeks for TAU). Compared with that in remitters in SSTR, the number of strategy changes was significantly higher in TAU remitters (3.0 +/- 2.7 and 1.0 +/- 1.5) and had more psychotropic medications (fix agents: 3.0 +/- 1.5 and 1.9 +/- 1.1; optional agents: 1.5 +/- 1.0 and 0.9 +/- 0.7). Although more patients dropped out of the SSTR group (33 of SSTR, 12 of TAU), the probability of remission tended to be higher in SSTR. Algorithm-guided treatment produces better outcomes and less frequent medication changes than TAU. A systematic, stepwise, measurement-based approach to the treatment of depressed inpatients is warranted.