title: Do drug formulary policies reflect evidence of value?
abstract: OBJECTIVE
  To investigate the extent to which preferred drug lists and tiered formularies reflect evidence of value, as measured in published cost-utility analyses (CUAs).
  
  
  METHODS
  Using 1998-2001 data from a large registry of cost-effectiveness analyses, we examined the 2004 Florida Medicaid preferred drug list and the 2004 Harvard Pilgrim Pharmacy Program 3-tier formulary, and compared cost-utility ratios (standardized to 2002 US dollars) of drugs with preferred and nonpreferred status.
  
  
  RESULTS
  Few drugs on the formularies had any cost-utility data available. Of those that did, median cost-utility ratios were somewhat higher (less favorable) for Florida's preferred drugs compared with the nonpreferred drugs (25,465 dollars vs 13,085 dollars; P = .09). Ratios did not differ for drugs on tiers 1 and 2 of the Harvard Pilgrim formulary, although they were higher for tier 3 and for excluded drugs (18,309 dollars, 18,846 dollars, 52,119 dollars, and 22,580 dollars, respectively; P = .01). Among therapies reported to be cost-saving or to have cost-utility ratios below 50,000 dollars, 77% had favored status in Florida Medicaid and 73% in Harvard Pilgrim. Among dominated drug interventions (reported to be more costly and less effective than alternatives), 95% had favored status in Florida Medicaid and 56% in Harvard Pilgrim.
  
  
  CONCLUSIONS
  This study underscores the paucity of published cost-utility data available to formulary committees. Some discrepancies prevail between the value of drugs, as reflected in published cost-utility ratios, and the formulary placement policies of 2 large health plans.
authors.affiliation: Department of Health Policy and Management and Center for Risk Analysis, Harvard School of Public Health, Boston, MA 02115, USA. pneumann@hsph.harvard.edu
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Neumann
authors.forename: Pei-Jung
authors.initials: PJ
authors.lastname: Lin
authors.forename: Dan
authors.initials: D
authors.lastname: Greenberg
authors.forename: Marc
authors.initials: M
authors.lastname: Berger
authors.forename: Steven
authors.initials: S
authors.lastname: Teutsch
authors.forename: Edward
authors.initials: E
authors.lastname: Mansley
authors.forename: Milton C
authors.initials: MC
authors.lastname: Weinstein
authors.forename: Allison B
authors.initials: AB
authors.lastname: Rosen
mesh_terms: D001900:Boston; D017046:Cost Savings; D003362:Cost-Benefit Analysis; D003659:Decision Making, Organizational; D003669:Deductibles and Coinsurance / Q000191:economics; D016527:Drug Costs / Q000706:statistics & numerical data; D019317:Evidence-Based Medicine; D005431:Florida; D005569:Formularies as Topic / Q000592:standards*; D006291:Health Policy; D006301:Health Services Needs and Demand; D006801:Humans; D019458:Insurance Coverage; D007356:Insurance, Pharmaceutical Services; D008484:Medicaid / Q000458:organization & administration*; D016134:Organizational Policy; D017063:Outcome Assessment, Health Care; D018579:Patient Selection; D010606:Pharmacy and Therapeutics Committee / Q000458:organization & administration; D019057:Quality-Adjusted Life Years; D012042:Registries; D012052:Reimbursement, Incentive / Q000191:economics