How effective is algorithm-guided treatment for depressed inpatients? results from the randomized controlled multicenter German algorithm project 3 trial
Publikation: Beitrag in Fachzeitschrift › Forschungsartikel › Beigetragen › Begutachtung
Beitragende
Abstract
Background: 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.Methods: 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). The fourth arm proposed medications and provided less specific recommendations based on a computerized documentation and expert system (CDES), the fifth arm received treatment as usual (TAU). ALGO included 3 different second-step strategies: Lithium augmentation (ALGO LA), antidepressant dose-escalation (ALGO DE), and switch to a different antidepressant (ALGO SW). Time to remission (21-item Hamilton Depression Rating Scale .9) was the primary outcome. Results: Time to remission was significantly shorter for ALGO DE (n = 91) compared with both TAU (n = 84) (HR = 1.67; P = .014) and CDES (n = 79) (HR = 1.59; P = .031) and ALGO SW (n = 89) compared with both TAU (HR = 1.64; P = .018) and CDES (HR = 1.56; P = .038). For both ALGO LA (n = 86) and ALGO DE, fewer antidepressant medications were needed to achieve remission than for CDES or TAU (P < .001). Remission rates at discharge differed across groups; ALGO DE had the highest (89.2%) and TAU the lowest rates (66.2%). Conclusions: A highly structured algorithm-guided treatment is associated with shorter times and fewer medication changes to achieve remission with depressed inpatients than treatment as usual or computerized medication choice guidance.
Details
Originalsprache | Englisch |
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Seiten (von - bis) | 721-730 |
Seitenumfang | 10 |
Fachzeitschrift | International journal of neuropsychopharmacology |
Jahrgang | 20 |
Ausgabenummer | 9 |
Publikationsstatus | Veröffentlicht - 1 Sept. 2017 |
Peer-Review-Status | Ja |
Externe IDs
PubMed | 28645191 |
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ORCID | /0000-0002-2666-859X/work/161890536 |
ORCID | /0000-0001-5398-5569/work/161890773 |
Schlagworte
ASJC Scopus Sachgebiete
Schlagwörter
- Antidepressants, German Algorithm Project, Medical Decision Making, Treatment Algorithms, Treatment-Resistant Depression