title: The estimation of utility weights in cost-utility analysis for mental disorders: a systematic review.
abstract: OBJECTIVE
  To systematically review approaches and instruments used to derive utility weights in cost-utility analyses (CUAs) within the field of mental disorders and to identify factors that may have influenced the choice of the approach.
  
  
  METHODS
  We searched the databases DARE (Database of Abstracts of Reviews of Effects), NHS EED (National Health Service Economic Evaluation Database), HTA (Health Technology Assessment), and PubMed for CUAs. Studies were included if they were full economic evaluations and reported quality-adjusted life-years as the health outcome. Study characteristics and instruments used to estimate utility weights were described and a logistic regression analysis was conducted to identify factors associated with the choice of either the direct (e.g. standard gamble) or the preference-based measure (PBM) approach (e.g. EQ-5D).
  
  
  RESULTS
  We identified 227 CUAs with a maximum in 2009, 2010, and 2012. Most CUAs were conducted in depression, dementia, or psychosis, and came from the US or the UK, with the EQ-5D being the most frequently used instrument. The application of the direct approach was significantly associated with depression, psychosis, and model-based studies. The PBM approach was more likely to be used in recent studies, dementia, Europe, and empirical studies. Utility weights used in model-based studies were derived from only a small number of studies.
  
  
  CONCLUSIONS
  We only searched four databases and did not evaluate the quality of the included studies.
  
  
  CONCLUSIONS
  Direct instruments and PBMs are used to elicit utility weights in CUAs with different frequencies regarding study type, mental disorder, and country.
authors.affiliation: Department of Health Economics and Health Services Research, Hamburg Center for Health Economics, University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany, mi.sonntag@uke.de.
authors.forename: Michael
authors.initials: M
authors.lastname: Sonntag
authors.forename: Hans-Helmut
authors.initials: HH
authors.lastname: König
authors.forename: Alexander
authors.initials: A
authors.lastname: Konnopka
mesh_terms: D003362:Cost-Benefit Analysis; D016208:Databases, Factual; D017048:Health Care Costs; D006801:Humans; D016015:Logistic Models; D008390:Markov Chains; D001523:Mental Disorders / Q000191:economics* / Q000628:therapy; D019057:Quality-Adjusted Life Years; D013673:Technology Assessment, Biomedical / Q000191:economics*