title: Quality-assessed reviews of health care interventions and the database of abstracts of reviews of effectiveness (DARE). NHS CRD Review, Dissemination, and Information Teams.
abstract: OBJECTIVE
  Database of Abstracts of Reviews of Effectiveness (DARE) (http:@www.york.ac.uk/inst/crd/) at the NHS Centre for Reviews and Dissemination provides a unique international resource of structured summaries of quality-assessed reviews of health care interventions. These reviews have been identified from searches of electronic databases and by hand-searching journals. This paper describes and summarizes the DARE database, including the topic areas covered and the review methods used.
  
  
  METHODS
  The first 480 structured abstracts on the DARE database were summarized. Data were extracted from each database field and coded for analysis.
  
  
  RESULTS
  Most of the systematic reviews investigated the effectiveness of treatments: 54% investigated the effectiveness of medical therapies, and 10% assessed surgical interventions. Around two-thirds used meta-analytic methods to combine primary studies. The quality of the reviews was variable, with just over half of the reviews (52%, n = 251) having systematically assessed the validity of the included primary studies. Narrative reviews were more likely than meta-analyses to reach negative conclusions (42% vs. 25%, p = .0001). The 21 reviews that reported drug company funding were more likely to reach positive conclusions (81% vs. 66%, p = .15).
  
  
  CONCLUSIONS
  The DARE database is a valuable source of quality-assessed systematic reviews, and is free and easily accessible. It provides a valuable online resource to help in filtering out poorer quality reviews when assessing the effectiveness of health technologies.
authors.forename: M
authors.initials: M
authors.lastname: Petticrew
authors.forename: F
authors.initials: F
authors.lastname: Song
authors.forename: P
authors.initials: P
authors.lastname: Wilson
authors.forename: K
authors.initials: K
authors.lastname: Wright
mesh_terms: D000043:Abstracting and Indexing; D015982:Bias; D016208:Databases, Factual; D019317:Evidence-Based Medicine; D006801:Humans; D015201:Meta-Analysis as Topic; D009862:Online Systems; D015203:Reproducibility of Results; D012107:Research Design / Q000592:standards*; D012196:Review Literature as Topic; D013673:Technology Assessment, Biomedical / Q000458:organization & administration*; D016896:Treatment Outcome; D006113:United Kingdom