Determinants of HMO Formulary
`Adoption Decisions
`David Dranove, Edward F. X. Hughes, and Mark Shanley
`
`Objective. To identify economic and organizational characteristics that affect the
`likelihood that health maintenance organizations (HMOs) include new drugs on their
`formularies.
`Data Sources. We administered an original survey to directors of pharmacy at 75
`HMOs, of which 41 returned usable responses. We obtained drug specific data from an
`industry trade journal.
`Study Design. We performed multivariate logistic regression analysis, adjusting for
`fixed drug effects and random HMO effects. We used factor analysis to limit the
`number of predictors.
`Data Collection Methods. We held initial focus groups to help with survey design.
`We administered the survey in two waves. We asked respondents to report on seven
`popular new drugs, and to describe a variety of HMO organizational characteristics.
`Principal Findings. Several HMO organizational characteristics, including nonprofit
`status, the incentives facing the director of the pharmacy, size and make up of the
`pharmacy and therapeutics committee, and relationships with drugs makers, all affect
`formulary adoption.
`Conclusions. There are many organizational factors that may cause HMOs to make
`different formulary adoption decisions for certain prescription drugs.
`Key Words. Formulary, managed care, pharmacoeconomics
`
`A drug formulary is a list of approved drugs.1 The term is historically
`associated with hospitals; a hospital pharmacy stocks those drugs on the
`hospital formulary and some nonformulary items.2 Today, formularies are an
`essential component of managed care.3 Most health maintenance organiza-
`tions (HMOs) provide greater coverage to patients who obtain drugs listed on
`their formularies.4 Some HMOs design their own formularies while others
`rely on third parties for formulary design. Regardless of how HMOs design
`their formularies, there is variation across HMOs in how they make adoption
`decisions for a given set of drugs. Some formularies are relatively ‘‘open’’ and
`include almost all FDA-approved drugs.5 Others are more restrictive, so that
`their HMOs pay for only one or two out of a class of competing drugs. This
`variation in formulary adoption decisions is, needless to say, important to
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`member satisfaction increases by 0.8 percent, then the chances of adoption
`increase to 78 percent.
`Health maintenance organizations tend to favor manufacturers whose
`representatives pay more visits. If representatives make four additional annual
`visits, the probability of formulary inclusion increases to 77 percent. This
`result could reflect endogeneity; that is, drug manufacturer representatives
`might make more visits to HMOs when they have products with a higher
`potential for adoption. However, the manufacturers of the drugs that we study
`sell many drugs besides those we analyze. Thus, we can take the number of
`visits as exogenous, and we interpret causality as running from visits to
`adoption. The makeup of the P&T committee and the sources of information
`that
`it relies upon also matter. Increasing the relative importance of
`management opinion versus the published literature by .25 increases the
`probability of adoption to 73 percent. Replacing two medical personnel on the
`P&T committee with two nonmedical personnel reduces the likelihood of
`adoption to 50 percent. This latter finding may reflect Fuchs’ ‘‘therapeutic
`imperative’’; that is, specialty physicians may argue for the full complement of
`therapeutic modalities in their specialty available on the formulary regardless
`of cost.28
`Lastly, we find that drug sales do not affect adoption decisions, but that
`drugs with more direct competitors have a greater chance of adoption. The
`addition of two direct competitors boosts the adoption probability to 69
`percent. This is consistent with competition forcing manufacturers to give
`larger rebates to encourage adoption.
`
`DISCUSSION
`
`Prior to the growth of managed care, pharmaceutical companies directed their
`marketing efforts at physicians and hospitals. With managed care, pharma-
`ceutical companies found that this was not sufficient. Now, they must convince
`MCOs to include their drugs on their formularies. Pharmaceutical companies
`have taken a number of steps to market their products to MCOs, including
`(1) MCO-specific sales forces, (2) disease-management programs, and (3) the
`establishment of in-house pharmacoeconomic programs. Managed care has
`also played a critical role in the development of direct-to-consumer (DTC)
`advertising. According to some pharmaceutical executives with whom we
`have spoken, one of the goals of DTC advertising is to get MCO enrollees to
`pressure their physicians to prescribe, and therein, their MCOs, to pay for
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`advertised drugs. Despite these efforts, pharmaceutical companies have had
`mixed success promoting their drugs to MCOs. The fact that some HMOs are
`willing to pay for drugs while others are not is a challenge for pharmaceutical
`companies. It is also a concern to patients, albeit not always a perceived one,
`because their access to drugs may depend on their choice of HMO. To the
`extent that MCOs believe that they use purely objective cost-benefit analyses
`to guide adoption decisions, the importance of organizational factors should
`be a concern.
`In this article, we have attempted to identify organizational factors that
`cause inter-HMO variation in formulary adoption decisions. We studied
`seven drugs that were not universally adopted upon initial
`launch. By
`estimating a fixed drug effects model, we controlled for the overall propensity
`of HMOs to adopt each drug and examined why there is inter-HMO variation
`in adoption probabilities for each drug. Our key finding is that organizational
`characteristics do matter. The ways in which HMOs structure their review
`process, how they reward their key decision makers, and their relationships
`with manufacturers all affect adoption decisions. As a result, two seemingly
`similar HMOs (same size, nonprofit status) will often make different decisions
`about drug adoption. For example, HMOs with large P&T committees are
`much less likely to adopt drugs, whereas HMOs that reward their pharmacy
`directors on the basis of overall medical costs, rather than just pharmacy costs,
`are more likely to adopt drugs.
`We should make several caveats about our findings. First, we only
`examined HMOs that develop their own formularies. The factors that
`influence their adoption decisions may differ from those in HMOs that
`outsource formulary development. Second, we examined a snapshot in time.
`It is possible that the adoption rates for drugs increase over time. This suggests
`that it would be valuable to study adoption rates over time as well as in cross-
`section. Third, we intentionally studied ‘‘controversial’’ drugs;
`that
`is,
`commonly prescribed drugs with variable rates of adoption. Virtually all
`drugs are less controversial than those that we studied, suggesting that there is
`substantial agreement among HMO formularies. Fourth, some of our
`predictor variables, such as the size of
`the P&T committee, may be
`endogenous to the overall goals of the HMO. Thus, an HMO that wishes to
`forestall drug adoption may enlarge its P&T committee. If so, then the
`observed negative effect of the size of the committee on adoption may be a
`reflection of the HMO’s overall objectives rather than a result of the size of the
`committee per se. Fifth, even though many of our predictor variables are
`statistically significant and have substantial magnitudes, our models fail to
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`explain the majority of the variation among formulary adoption decisions.
`There are clearly additional sources of variation left to be identified. Finally,
`we note that since we performed our study, many HMOs have moved to more
`complex formulary structures, with multiple copayment levels that depend on
`different levels of ‘‘preferred’’ status. This might make it more difficult to
`predict whether drugs will be included on a formulary, and at what level of
`coverage.
`What are the implications of our results for pharmacy directors and
`other participants in formulary adoption decisions? The upward pressure on
`pharmaceutical costs in managed care will only raise the stakes of formulary
`adoption decisions. Our findings suggest that many adoption decisions are
`based on organizational factors, rather than objective cost-benefit analyses.
`HMOs must review their internal systems to assure that they are making
`objective assessments of costs and benefits. The upward pressure on drug costs
`has also pressured some HMOs to adopt more complex drug benefits
`characterized by, for example, three or more tiers of copayments. At one level,
`the use of multiple tiers reduces the significance of the initial formulary
`adoption decision. But, it ushers in more complexity, as pharmacy decision
`makers must determine both whether to include a drug on their formulary and
`the appropriate tier on which to put it.
`It is reasonable to expect that some level of inter-HMO variation in
`adoption decisions will persist. The HMOs are unlikely to become the same
`size, adopt identical objectives, or interpret evidence on drug benefits and
`costs in the same way. Since variation across HMO formularies is likely to
`persist, the question arises of its consequences for consumers. Variation in
`adoption decisions for drugs that have close therapeutic substitutes is unlikely
`to have important clinical consequences, provided that at least one of the class
`of drugs is on the formulary. However, variation in adoption decisions for
`therapeutically unique products may adversely affect some patients, especially
`if patients are unaware of the drug’s formulary status at the time they select
`their HMO, or are offered no choice of HMO by their employer. Research to
`determine the medical and economic impact of formulary variation would
`appear appropriate.
`Our findings have relevance to pharmaceutical companies as well. We
`have shown that some HMOs are harder to ‘‘crack’’ than others, and may
`require greater sales and marketing effort. At the same time, individual sales
`personnel should not be penalized if they fail to get adoption at particular
`HMOs. Relationships between drug manufacturers and HMOs influence
`adoption decisions. Therefore, investing in these relationships can yield
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`long-term benefits to pharmaceutical firms. Interestingly, mergers within the
`pharmaceutical industry can affect adoption decisions by changing personal
`selling relationships between manufacturers and HMOs.
`Although we have not developed or tested a normative model, our
`findings do have some normative implications. To the extent that there is an
`‘‘optimal’’
`formulary based on objective benefit-cost data, our findings
`indicate that some HMOs do not achieve it. Over time, some HMOs may
`move toward such a formulary by learning from their own experiences and
`the experiences of others about the effects of organizational factors on
`adoption decisions. More and better scientific information will also help
`HMOs develop formularies that best balance benefits and costs.
`
`ACKNOWLEDGMENT
`
`We are grateful to Hoerchst Marion Roussel for generously supporting this
`project.
`
`NOTES
`
`1. Ito and Blackburn (1995) define a managed care formulary as ‘‘a listing of
`prescription medications which are preferred for use by a health plan.’’
`2. Goldberg (1997) discusses the origins of formularies and describes different types
`currently in use. See Sloan et al. (1993) for a discussion of the effectiveness of
`hospital formularies.
`3. According to one report, in 1997 formularies were a component of more than
`90 percent of all managed care plans. See Sax (1999). All of the managed care
`plans studied by Lyles et al. (1997) report that they use a formulary.
`4. A 2000 survey by the Kaiser Family Foundation and the Health Research and
`Educational Trust reports that 58 percent of workers in HMOs face a formulary
`that restricts which drugs are covered.
`5. Goldberg (1997).
`6. Concerns about response rates limited our analysis to seven drugs. We chose large
`selling drugs because of the heightened interest among pharmaceutical companies
`and HMOs about the adoption of such drugs.
`7. There are many articles describing selective contracting in more detail. For
`example, see Glied (2000).
`8. Taniguchi (1995).
`9. Aventis (2000).
`10. Browne (1995).
`11. Sarpong (1999) documents substantial variation in the training of P&T committee
`members.
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