The American Journal of Managed Care January 2006
Do Drug Formulary Policies Reflect Evidence of Value?
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 vs $13 085; 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, $18 846, $52 119, and $22 580, respectively; P = .01). Among therapies reported to be cost-saving or to have cost-utility ratios below $50 000, 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.
(Am J Manag Care. 2006;12:30-36)
Formularies with tiered copayment structures or preferred drug lists have become increasingly popular, as plans seek to provide financial inducements for enrollees to select the least expensive drugs while avoiding the restrictions of entirely closed formulary systems.1,2
Mounting evidence suggests that incentive-based formularies are associated with lower costs and smaller increases in drug utilization and expenditures compared with control groups.3-7 But researchers also have found that they are associated with undesirable effects: patients suddenly faced with higher copayments are more likely to switch medications or to discontinue medications entirely.7-9 Moreover, studies have found that cost sharing may be followed by reductions in the use of "essential" drugs, higher rates of serious adverse events, and increased use of emergency department visits and hospital days.9,10
In theory, plan formulary placement decisions should be guided by information about a drug's overall value or cost effectiveness. Ideally, drugs with favorable cost effectiveness would receive preferential formulary status (ie, physicians would have incentives to prescribe these drugs rather than nonpreferred drugs). Instead, observers complain that plans often base patient contributions on drugs' acquisition costs and, in fact, do not consider value in formulary placement decisions.1,11
However, there has been little empirical evidence on whether formulary policies actually reflect evidence of value in terms of cost effectiveness. The objective of this study was to examine whether the formulary drug-placement decisions of 2 large healthcare providers reflect the findings of published cost-utility analyses (CUAs). We acknowledge at the outset that this is an exploratory exercise whose purposes are to investigate the type and quality of cost-utility data available to formulary decision makers, and to further discussions about the need to move the healthcare system toward value-based benefit design.
To measure a drug's value, we focused on CUA, a special type of cost-effectiveness analysis in which health effects are measured in terms of quality-adjusted life years (QALYs) gained. Leaders in the field have recommended this outcome as the standard for cost-effectiveness research.12 Though not without limitations, CUAs are appealing as a measure of overall value for several reasons: they capture in a single measure gains from both prolongation and quality of life, they incorporate the value or preferences people place on different health outcomes, and they provide a common metric for comparing analyses of diverse interventions and conditions.13
DATA AND METHODS
Cost-utility Analyses of Drug Therapies
The Cost-Effectiveness Registry. Data on the cost effectiveness or value of drugs were derived from the Harvard Center for Risk Analysis Cost-Effectiveness Registry, a database of 539 original CUAs published in the public health and medical literature from 1976 through 2001. Cost-utility analyses were included if they were published in a MEDLINE-referenced journal and provided an original cost-utility estimate. Review papers and methodological papers were excluded. More detail about the registry is provided elsewhere.14,15
Briefly, 2 readers independently collected data on each article and then convened for a consensus review to resolve discrepancies. Data were collected on a wide range of items related to the methods used to estimate and report costs, health effects, preference weights, modeling assumptions, and study limitations. We also included a subjective assessment of overall study quality on a Likert-type scale from 1 (low) to 7 (high), which reflects readers' evaluation of the rigor, reasonableness, and usefulness of each analysis. Data on the cost-utility ratios associated with each intervention also were collected and standardized to 2002 US dollars.15
Drug Data in the Cost-utility Analysis Registry. For this study we focused on CUAs in the registry pertaining to pharmaceutical interventions (378 CUAs reporting 898 cost-utility ratios). To exclude potentially outmoded analyses, we further restricted the sample to studies published from 1998 through 2001, leaving a final sample of 112 studies and 266 cost-utility ratios (the number of ratios exceeds the number of studies because some analyses contain more than 1 ratio). The complete list of references is available from the authors.
Identifying Formulary Policies
We examined publicly available formularies of 2 healthcare providers, the Florida Medicaid preferred drug list and the Harvard Pilgrim Healthcare Pharmacy Program (HPHC) in Boston. These plans were chosen arbitrarily, based on the availability of formulary information, although we did set out to select plans representing different geographic regions and types of payers.
The Florida Medicaid program lists prescription products on a preferred drug list selected by the pharmaceutical and therapeutics committee as "efficacious, safe, and cost effective choices when prescribing for Medicaid patients."16 Our analysis used the March 22, 2004, updated list, which contained 1749 drugs.
The HPHC categorizes medications into 1 of 3 tiers. Patients make the lowest copayment for drugs on tier 1, which consists of generic drugs approved by the US Food and Drug Administration (FDA). Tier 2 drugs are brand-name drugs granted preferred status (and a moderate copayment) by HPHC based on reviews of their relative safety, effectiveness, and cost.17 Tier 3 contains nonpreferred drugs for which patients make the highest copayment. The actual copayment amount varies, depending on which benefit design is selected by the beneficiaries' employer group. Some prescription medications are excluded from coverage, such as Avage (tazarotene) for skin conditions and the weight-loss treatments Meridia (sibutramine) and Xenical (orlistat).
We examined the relationship between the placement of drugs on formularies and evidence of value, as reflected in published cost-utility ratios. Specifically, we investigated whether the drugs on Florida Medicaid's preferred lists had lower (ie, more favorable) cost-utility ratios than those with nonpreferred status. Similarly, we investigated whether drugs on HPHC's lower tiers (reflecting lower copayments) had more favorable cost-utility ratios than those on higher tiers.
We compared the median cost-utility ratios between preferred and nonpreferred drugs in the Florida Medicaid program, and among drugs with different tier classifications on the HPHC formulary. We used the Wilcoxon rank sum and Kruskal-Wallis nonparametric tests because of heteroskedasticity and heavily skewed ratio distributions.18 We also sought to find examples of drugs with good overall cost effectiveness or value that were not on preferred lists or favorable tiers, and conversely whether preferred lists or favorable tiers contained drugs with unfavorable cost effectiveness. These "discordant" pairs were then reviewed to explore possible reasons for discrepancies. Note that we excluded from our analysis combination therapies (drug A + drug B) for which the plan pays only partially (either drug A or B). For example, a CUA might analyze etoposide plus cisplatin versus gemcitabine in patients with metastatic non-small-cell lung cancer. In the Harvard Pilgrim Health Plan, etoposide is covered, while cisplatin is not.
The 266 cost-utility ratios in our sample (representing 102 drugs) covered a wide range of disease categories, most commonly infectious diseases (31%), malignancies (17%), musculoskeletal and rheumatologic diseases (13%), and cardiovascular disease (13%) (Table 1). The majority (59%) were drugs for chronic diseases (treatment course of 18 months or longer). In terms of sponsorship, 33% came from studies funded by the pharmaceutical industry and 25% from government-funded studies; in 34%, the funding source could not be determined from the article.
Of the 266 cost-utility ratios pertaining to these 102 drugs, 150 (56%) were in the 0-$50 000 per QALY range (a range often cited as representing good value for money);19 43 (16%) were more than $100 000 per QALY; and 25 (9%) each were cost saving or dominated (ie, meaning the cost of the drug in question was higher and its health effects lower than its comparator) (Figure 1).
Of 1749 drugs on the Florida Medicaid preferred list, 102 drugs (5.8%) had any recently published data from CUAs. Median cost-utility ratios for drugs on Florida Medicaid's preferred list ($25 465) were higher than those on the nonpreferred list ($13 085) (P = .09, Wilcoxon rank sum test) (Table 2). Median ratios for drugs on tiers 1, 2, and 3 of the HPHC plan were $18 309, $18 846, and $52 119, respectively, and $22 580 for excluded drugs (P = .01 by the Kruskal-Wallis test, meaning that at least 1 tier had either a higher or a lower median cost-utility ratio than the other tiers).
Figure 2 show the distributions of cost-utility ratios according to preferred/nonpreferred status in the Florida Medicaid plan. The figure shows, for example, that for drugs on the preferred list, 29 cost-utility ratios (17% of the total number of cost-utility ratios for drugs on the preferred list) were more than $100 000 and an additional 20 were dominated; in contrast, for nonpreferred drugs, 2 ratios were cost saving and 32 were between 0 and $50 000. Figure 3 shows an analogous distribution for cost-utility ratios of drugs on the various HPHC tiers. In some instances, drugs reported to have good value received unfavorable tier placement (eg, for drugs on tier 3, 1 cost-utility result was cost saving and QALY improving, and 19 ratios were less than $50 000), and drugs with poor value received favorable tier placement (5 ratios for tier 1 were more than $100 000 per QALY and 7 ratios for tier 1 drugs reflected dominated interventions).
Where cost-utility ratios were available for Florida Medicaid, 64% of preferred drugs (111 of 173 ratios) and 72% (34 of 47) of nonpreferred drugs had ratios below $50 000, whereas for HPHC, those percentages were 71% (115 of 163) and 58% (42 of 73), respectively (where preferred is defined as tier 1 or 2).
The quality of CUAs varied slightly across formulary placement categories. For example, the quality score was 4.3 for CUAs of drugs on the Florida Medicaid preferred drug list vs 4.5 for CUAs of drugs on the nonpreferred list (P = .049). For the HPHC formulary, the quality score was 4.4 for CUAs of drugs on tiers 1 and 2 and 5.4 for CUAs of drugs on tier 3 (P = .002) (data not shown).