title: Relative effectiveness assessment of pharmaceuticals: similarities and differences in 29 jurisdictions.
abstract: OBJECTIVE
  Assessment of the effectiveness compared with alternative treatment(s) plays an important role in many jurisdictions in determining the reimbursement status of pharmaceuticals. This type of assessment is often referred to as a relative effectiveness assessment (REA) and is carried out by many jurisdictions. Increased sharing of information across jurisdictions may save costs and reduce duplication. The objective of this study was to explore the main similarities and differences in the major methodological aspects of REA in multiple jurisdictions.
  
  
  METHODS
  Data were gathered with a standardized data extraction form by searching publicly available information and by eliciting information from representatives at relevant organizations.
  
  
  RESULTS
  Of the initially included 35 jurisdictions, data were gathered for 29 jurisdictions. There seem to be substantial similarities on the choice of the comparator, the role of indirect comparisons, and preferred end points in REAs (except for the use of health state utilities). Jurisdictions, however, differ in whether effectiveness (usual circumstances of health care practice) is estimated in case no (comparative) effectiveness data are available and how this is done.
  
  
  CONCLUSIONS
  Some important methodological aspects for REA are approached in a similar way in many jurisdictions, indicating that collaboration on assessments may be feasible. Enhanced collaboration in the development of methods and best practices for REA between jurisdictions will be a necessary first step. Important topics for developing best practice are indirect comparisons and how to handle the gap between efficacy and effectiveness data in case good quality comparative effectiveness data are not yet available at the time of reimbursement decisions.
authors.affiliation: College voor zorgverzekeringen, Diemen, The Netherlands. skleijnen@cvz.nl
authors.forename: Sarah
authors.initials: S
authors.lastname: Kleijnen
authors.forename: Elisabeth
authors.initials: E
authors.lastname: George
authors.forename: Scott
authors.initials: S
authors.lastname: Goulden
authors.forename: Anne
authors.initials: A
authors.lastname: d'Andon
authors.forename: Pauline
authors.initials: P
authors.lastname: Vitré
authors.forename: Boguslawa
authors.initials: B
authors.lastname: Osińska
authors.forename: Rafal
authors.initials: R
authors.lastname: Rdzany
authors.forename: Steffen
authors.initials: S
authors.lastname: Thirstrup
authors.forename: Belen
authors.initials: B
authors.lastname: Corbacho
authors.forename: Bence Z
authors.initials: BZ
authors.lastname: Nagy
authors.forename: Hubert G
authors.initials: HG
authors.lastname: Leufkens
authors.forename: Anthonius
authors.initials: A
authors.lastname: de Boer
authors.forename: Wim G
authors.initials: WG
authors.lastname: Goettsch
mesh_terms: D057186:Comparative Effectiveness Research / Q000379:methods; D057225:Data Mining; D005060:Europe; D006801:Humans; D054539:Medication Therapy Management; D000091402:Prohibitins; D036301:Qualitative Research; D012062:Relative Biological Effectiveness