How effective is algorithm-guided treatment for depressed inpatients? results from the randomized controlled multicenter German algorithm project 3 trial

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Mazda Adli - , Charité – Universitätsmedizin Berlin, Center for Psychiatry, Psychotherapy and Psychosomatic Medicine (Author)
  • Katja Wiethoff - , Charité – Universitätsmedizin Berlin (Author)
  • Thomas C. Baghai - , Charité – Universitätsmedizin Berlin, University of Regensburg (Author)
  • Robert Fisher - , East London NHS Foundation Trust (Author)
  • Florian Seemüller - , kbo-Lech-Mangfall-Klinik Garmisch-Partenkirchen (Author)
  • Gregor Laakmann - , Ludwig Maximilian University of Munich (Author)
  • Peter Brieger - , kbo-Isar-Amper-Clinics Munich (Author)
  • Joachim Cordes - , Heinrich Heine University Düsseldorf (Author)
  • Jaroslav Malevani - , Heinrich Heine University Düsseldorf (Author)
  • Gerd Laux - , InnKlinikum (Altötting, Mühldorf, Burghausen, Haag) (Author)
  • Iris Hauth - , St. Joseph Hospital Berlin Tempelhof (Author)
  • Hans Jürgen Möller - , Ludwig Maximilian University of Munich (Author)
  • Klaus Thomas Kronmüller - , LWL Clinics Gütersloh (Author)
  • Michael N. Smolka - , Department of Psychiatry and Psychotherapy (Author)
  • Peter Schlattmann - , Friedrich Schiller University Jena (Author)
  • Maximilian Berger - , Heinrich Heine University Düsseldorf (Author)
  • Roland Ricken - , Charité – Universitätsmedizin Berlin (Author)
  • Thomas J. Stamm - , Charité – Universitätsmedizin Berlin (Author)
  • Andreas Heinz - , Charité – Universitätsmedizin Berlin (Author)
  • Michael Bauer - , Department of Psychiatry and Psychotherapy (Author)

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

Original languageEnglish
Pages (from-to)721-730
Number of pages10
JournalInternational journal of neuropsychopharmacology
Volume20
Issue number9
Publication statusPublished - 1 Sept 2017
Peer-reviewedYes

External IDs

PubMed 28645191
ORCID /0000-0002-2666-859X/work/161890536
ORCID /0000-0001-5398-5569/work/161890773

Keywords

Keywords

  • Antidepressants, German Algorithm Project, Medical Decision Making, Treatment Algorithms, Treatment-Resistant Depression