Part D Beneficiaries’ Incentives and Responses Under Preferred Pharmacy Networks

ABSTRACT

Objectives: The share of Medicare stand-alone prescription drug plans with a preferred pharmacy network has grown from less than 9% in 2011 to 98% in 2021. This article assesses the financial incentives that such networks created for unsubsidized and subsidized beneficiaries and their pharmacy switching.

Study Design: We analyzed prescription drug claims data for a nationally representative 20% sample of Medicare beneficiaries from 2010 through 2016.

Methods: We evaluated the financial incentives for using preferred pharmacies by simulating unsubsidized and subsidized beneficiaries’ annual out-of-pocket spending differentials between using nonpreferred and preferred pharmacies for all their prescriptions. We then compared beneficiaries’ use of pharmacies before and after their plans adopted preferred networks. We also examined the amount of money that beneficiaries left on the table under such networks, based on their pharmacy use.

Results: Unsubsidized beneficiaries faced substantial incentives—on average, $147 annually in out-of-pocket spending—and moderately switched toward preferred pharmacies, whereas subsidized beneficiaries were insulated from the incentives and demonstrated little switching. Among those who continued to mainly use nonpreferred pharmacies (half of the unsubsidized and about two-thirds of the subsidized), on average, the unsubsidized paid more out of pocket ($94) relative to if they had used preferred pharmacies, whereas Medicare bore the extra spending ($170) for the subsidized through cost-sharing subsidies.

Conclusions: Preferred networks have important implications for beneficiaries’ out-of-pocket spending and the low-income subsidy program. Further research is needed about the impact on the quality of beneficiaries’ decision-making and cost savings to fully evaluate preferred networks.

Am J Manag Care. 2023;29(4):180-186. https://doi.org/10.37765/ajmc.2023.89346

Takeaway Points

Preferred pharmacy networks leverage lower cost sharing to encourage Part D beneficiaries’ use of lower-cost pharmacies. We evaluate financial incentives and pharmacy switching under such networks.

• Unsubsidized beneficiaries faced substantial incentives, whereas subsidized beneficiaries were insulated due to the cost-sharing subsidy.
• There was moderate switching toward preferred pharmacies among the unsubsidized and little switching among the subsidized.
• Among those who continued to mainly use nonpreferred pharmacies, the unsubsidized paid more out of pocket relative to if they had used preferred pharmacies, whereas Medicare bore the extra spending for the subsidized.
• Preferred networks likely add to the complexity of Part D beneficiaries’ decision-making.

Prescription drug prices have received considerable policy attention recently. However, despite the intense policy interest in lowering drug prices, there has been very little attention paid to the variation in drug prices across different pharmacies, although evidence suggests that this variation is large,^1-3 not unlike the price differences observed across hospitals, physicians, and other types of providers.

There is a long history of health plans attempting to steer patients to lower-cost providers through preferred provider networks,⁴ including a robust literature that identifies 2 primary mechanisms through which they constrain costs: financially incentivizing patients to choose lower-cost, higher-value physicians and hospitals,^5-8 and giving plans more leverage in their negotiations with providers.^9-11 Additionally, recent efforts targeting value-based insurance design have attempted to promote the use of certain high-value therapeutic classes or generic drugs through the use of lower cost sharing, favorable tier placement, or formulary exclusion of brand-name drugs.^12-15 However, less is known about the impact of efforts to encourage patients to use lower-cost pharmacies.

In recent years, preferred pharmacy networks have emerged as a tool for plans to encourage the use of lower-cost pharmacies. The percentage of Medicare Part D stand-alone prescription drug plans (PDPs) with a preferred pharmacy network has grown rapidly from less than 9% in 2011 to 98% in 2021 (Figure 1). The use of preferred networks has also been expanding in other markets.¹⁶ In such networks, plans essentially divide retail pharmacies into 2 tiers: nonpreferred (or “standard”) pharmacies and preferred pharmacies, which presumably offer greater price concessions.17 In exchange, plans offer higher expected patient volume by incentivizing patients to use preferred pharmacies through lower cost sharing than they would face at nonpreferred pharmacies. eAppendix Table 1 (eAppendix available at ajmc.com) illustrates cost-sharing changes across tiers in major Part D plans—those enrolling 25,000 or more in our 20% Medicare beneficiary sample—that introduced a preferred network. They were generally in the form of co-pays and applied to the tiers except the highest (usually specialty) one. The differences between preferred pharmacies and nonpreferred could be large in relative terms for generic drugs (often on tiers 1 and 2). For example, from 2012 to 2013 for the AARP MedicareRx Preferred plan, the co-pay for a 30-day prescription of a tier 2 drug changed from $8 at all pharmacies to $5 at preferred and $10 at nonpreferred pharmacies.

While pharmacy networks in their entirety are still subject to network breadth regulations and plans must contract with any pharmacy that accepts their terms and conditions, preferred networks provide plans additional leverage, which may have contributed to the recent growth of pharmacy price concessions to Part D plans, which have increased from $8.9 million in 2010 to $9.5 billion in 2020.¹⁸

Despite their considerable growth in market share and potential implications for Part D spending, little is known about the impact of preferred pharmacy networks in Part D. Although a prior study found a small shift toward preferred pharmacies and modest cost savings, it did not evaluate the financial incentives that beneficiaries faced and the financial consequences of their pharmacy choice. In this paper, we simulated the potential savings for beneficiaries from using only preferred vs only nonpreferred pharmacies, and we empirically assessed beneficiaries’ pharmacy choices and their financial consequences.

METHODS

Data and Sample

This study used beneficiary summary, Part D plan characteristics and tier cost-sharing files, and prescription drug event claims from a nationally representative 20% sample of Medicare beneficiaries from 2010 through 2016. The analyses focused on beneficiaries 65 years and older and in PDPs with a preferred network during 2011-2016, the period of dramatic increase in preferred network penetration among PDPs. We categorized beneficiaries as low-income subsidy (LIS) beneficiaries if they received Medicare LISs for premiums and cost sharing, and we required that beneficiaries’ LIS status remained unchanged during the year. Additional criteria included enrolling in the same plan for the entire year and filling at least 1 prescription.

We augmented these data with the First Databank drug database and Part D pharmacy network files obtained from CMS. The drug database provided information on whether a National Drug Code (NDC) is generic or brand name and its active ingredient. For each Part D plan in a given year, the pharmacy network files contained the National Provider Identifier of every network pharmacy and indicators for whether the pharmacy was a retail or mail order pharmacy and whether it was preferred. Additionally, to illustrate the most recent trend of preferred network implementation, we collected Part D landscape files and plan benefit design data from CMS for 2017-2021.

Financial Incentives

We evaluated the financial incentives for using preferred pharmacies by simulating beneficiaries’ annual out-of-pocket (OOP) spending differentials between using nonpreferred and preferred pharmacies for all their prescriptions. In addition to differential co-pays, predicted cost differences for an individual depend on their other plan characteristics such as deductible and gap coverage, utilization of drugs, and LIS status. To account for all these factors, we computed beneficiaries’ total OOP spending over the course of a year if all their retail claims had been at nonpreferred pharmacies and if all had been at preferred pharmacies. We assumed that substitution as a result of preferred networks occurred only among retail pharmacies, and thus the use of mail order pharmacies was unaffected (market share of mail order pharmacies was low and increased only slightly during the study period).

We assumed that point-of-sale total prices and drug tier cost sharing at preferred and nonpreferred pharmacies within a plan were fixed. Thus, we first constructed empirical formularies containing each plan-NDC dyad’s mean prices and co-pays/coinsurance rates separately for preferred, nonpreferred, and mail order pharmacies; information on whether the plan-NDC was generic or branded; whether the deductible applied to the plan-NDC; and whether it was covered in the coverage gap. We then ran each beneficiary’s claims through the formulary of the specific plan and plan characteristics including deductible, initial coverage limit, and catastrophic coverage threshold, and we calculated total claim costs and patient OOP payment for using a preferred and a nonpreferred pharmacy for each retail claim. For LIS beneficiaries, we applied cost-sharing rules specific to each eligibility category and additionally computed low-income cost-sharing subsidy (LICS) amounts for different pharmacies. Because their cost sharing is capped by law, their OOP payment differs at preferred and nonpreferred pharmacies only when the co-pay at preferred pharmacies is lower than their co-pay cap for a particular drug, and the difference does not exceed that cap. See the eAppendix for more detail about the simulation.

Analysis

We first assessed the financial incentives for using preferred instead of nonpreferred pharmacies. To do so, we first pooled all beneficiary-years in PDPs with a preferred network from 2011 through 2016. We identified such plans by checking whether their networks were divided into preferred and nonpreferred pharmacies and whether patient cost sharing differed accordingly. We then examined separately for non-LIS and LIS beneficiaries the distribution of patient OOP spending differentials between using nonpreferred and preferred pharmacies only. We excluded beneficiary-years with extreme values—that is, those with a differential in the top or bottom 0.5% of the distribution. For the LIS, we also assessed the distribution of the LICS differentials.

We then evaluated whether these financial incentives affected beneficiaries’ pharmacy choice. Specifically, this analysis focused on comparing beneficiaries’ use of preferred pharmacies in the year prior and plans’ first year of preferred networks (see eAppendix Table 2 for descriptive statistics of the sample). We defined “preferred pharmacies in the year prior” as those that would go on to be preferred in the subsequent year—after the preferred pharmacy network was first introduced. We focused just on the first year after the introduction of the preferred pharmacy network due to substantial year-to-year changes in pharmacies’ preferred status within a plan. To do so, we further restricted the sample to beneficiaries who remained in their plan when it implemented a preferred network and whose LIS status and zip code remained unchanged during the 2 years. There were 1,230,532 beneficiary-years, among which 28% were represented by LIS beneficiaries. Then, for each 2-year pair, we mapped pharmacies’ preferred status in a given plan in the postimplementation year to the preimplementation year, and calculated 2 measures of preferred pharmacy use each year for non-LIS and LIS beneficiaries: preferred pharmacies’ claim share and the percentage of beneficiaries filling the majority of their prescriptions at preferred pharmacies. Next, to obtain preimplementation and postimplementation means for these measures, we weighted the first measure by total number of claims and the second measure by total number of beneficiaries.

Because we found moderate switching toward preferred pharmacies among the non-LIS beneficiaries and little switching among the LIS beneficiaries, we examined beneficiaries’ forgone savings based on their pharmacy use. We categorized non-LIS and LIS beneficiaries as “majority preferred” if they filled the majority (more than half) of their prescriptions in a given year at preferred pharmacies. We categorized them as “majority nonpreferred” and “majority mail order” similarly. We excluded beneficiaries for whom none of these types accounted for the majority of their claims, because they accounted for only 3% of the sample. For each group, we then assessed the distribution of forgone savings for beneficiaries and Medicare. We calculated forgone savings, or overspending, for a beneficiary as the difference between their actual OOP spending and their simulated OOP spending if they had used preferred pharmacies for all retail claims, holding drug utilization fixed. Similarly, for LIS beneficiaries, we also computed forgone savings for Medicare as the difference between the actual LICS and the simulated subsidy if the beneficiary had used preferred pharmacies for all retail claims.

RESULTS

The financial incentives for using preferred pharmacies differed for non-LIS and LIS beneficiaries. As Table 1 shows, over the course of a year, the OOP spending differential between filling all prescriptions at nonpreferred and preferred pharmacies was sizable for about half of non-LIS beneficiaries. On average, the potential OOP differential for non-LIS beneficiaries was $147 (23% of their mean OOP spending). The distribution was right skewed, with a median of $98 and a 75th percentile of $214, suggesting that many non-LIS beneficiaries could have reaped large savings by using preferred pharmacies. In contrast, because their cost sharing was set by law rather than by their plan, differential co-pays in preferred networks had minimal consequences for LIS beneficiaries, with 48% of them having zero OOP spending differential. Instead, Medicare shouldered those differentials, which equaled $190 on average for the LICS program (10% of the mean LICS amount).

Facing these financial incentives, non-LIS beneficiaries moderately increased their use of preferred pharmacies in the first year of preferred networks, whereas LIS beneficiaries demonstrated minimal pharmacy switching. Among non-LIS beneficiaries in the year prior to preferred network implementation, 28.5% of claims were filled at pharmacies that would go on to become preferred pharmacies in the following year (we note that there was no particular financial incentive to use these “to-be-preferred” pharmacies in the preimplementation year). After implementation of preferred pharmacy networks, this share increased by 3.2 percentage points (Figure 2). In contrast, among LIS beneficiaries, only 22.5% of claims were filled at “to-be-preferred” pharmacies in the preimplementation year, which was relatively unchanged post implementation (22.0%). The patterns were similar for the percentage of beneficiaries using preferred pharmacies for more than half of their prescription fills.

Because many beneficiaries used a mix of preferred and nonpreferred pharmacies—as described in Figure 2—the empirical forgone savings tended to be lower than the simulated potential savings from filling all prescriptions at preferred or nonpreferred pharmacies described earlier. Nonetheless, the actual use of nonpreferred pharmacies was linked to significant forgone savings for some non-LIS beneficiaries and for Medicare. Among the non-LIS beneficiaries, majority preferred and majority mail order beneficiaries had minimal forgone savings, with the means close to $0 and the 75th percentiles around $20, whereas majority nonpreferred beneficiaries (51% of the sample) overspent considerably by continuing to visit nonpreferred pharmacies (Table 2). Had they used preferred pharmacies, they could have on average saved $94, which amounted to 12% of their mean OOP spending, and a quarter of them left $172 or more on the table. In comparison, LIS beneficiaries using nonpreferred pharmacies (64% of the sample) incurred overspending to Medicare instead of themselves. Relative to the situation where they switched all fills to preferred pharmacies, Medicare on average paid an extra of $170 in LICS (8% of the mean LICS amount) for them, and the amount reached $275 or more for a quarter of them. As a result, LICS bore a higher share of the costs for them than for majority preferred beneficiaries (42% vs 38%).

DISCUSSION

We found that non-LIS and LIS beneficiaries faced different financial incentives in preferred pharmacy networks and had different pharmacy switching responses. For the non-LIS beneficiaries, the incentives created by the differential co-pays were substantial, with potential mean beneficiary savings estimated to be $147 based on using preferred pharmacies only rather than nonpreferred pharmacies only. However, in the first year of preferred networks being implemented by a given plan, non-LIS beneficiaries’ use of preferred pharmacies increased only moderately (from 28.5% of claims to 31.7%) among those who stayed in their plan. In contrast, because their cost sharing was capped statutorily, the LIS beneficiaries faced minimal incentive and did not seem to switch toward preferred pharmacies.

One reason why we observed moderate pharmacy switching among the non-LIS beneficiaries may be that we focused on plans’ first year of preferred network implementation. The magnitude may grow as beneficiaries’ exposure and experience increase over time.^7,19 In addition, some beneficiaries might fail to fully understand the impact on their spending or lack convenient access to preferred pharmacies. Some might also have a higher willingness to pay for convenience, services, and the relationship with their pharmacist.

Consequently, among non-LIS beneficiaries who remained in their plan when a preferred network was implemented, half incurred higher OOP spending because they still mostly used nonpreferred pharmacies. They had forgone savings of $94 on average, which was 12% of their mean OOP spending, and a quarter of them had $172 or more in forgone savings.

Put in the broader context of Part D beneficiaries’ decision-making, the forgone savings also raises concerns about preferred networks causing additional complexity for beneficiaries. The mean forgone savings here is about a quarter of that due to less-than-optimal plan choice in Part D.^20-23 Beneficiaries may have nonmonetary reasons for using nonpreferred rather than preferred pharmacies. Nevertheless, the comparison underscores the financial significance of pharmacy choice in the environment of preferred networks: A beneficiary may leave a nontrivial amount of money on the table if they fail to account for their pharmacy’s preferred status. Therefore, such networks add another layer of complexity to beneficiaries’ decision-making, when they are already having difficulty navigating a complex menu of options,^24,25 and the year-to-year variation we observed of a pharmacy’s preferred status even within a plan would exacerbate that. Indeed, preferred networks caused much confusion to beneficiaries in their early days.²⁶ Therefore, although Medicare Plan Finder allows beneficiaries to compare drug prices across pharmacies after they click through to a particular plan, to aid decision-making, it should incorporate information on each plan’s preferred pharmacies when displaying the list of plans. It is also necessary for future research to assess how these networks affect the quality of beneficiaries’ plan and pharmacy choices, as the prior literature on Part D plan choice has covered only the periods before the emergence of preferred networks, and it is important for policy makers to consider that when evaluating the pros and cons of preferred networks.

For roughly two-thirds of the LIS beneficiaries who remained in their plan when a preferred network was implemented, Medicare bore the financial burden in the form of higher LICS as a result of their use of nonpreferred pharmacies. Medicare overspent an average of $170 in LICS (8% of the mean subsidy amount) for them. This likely had an effect on the growing expenditures of the LIS program,²⁷ although not as large as that of the rising drug prices, and the significance of this overspending may increase, given recent proposals to expand the eligibility for the program.²⁸ In addition, our results of LICS taking up a higher share of the costs of nonpreferred pharmacy users suggest that preferred networks may allow plans to off-load some risk of the spending of LIS beneficiaries to Medicare, because they seldom switch to preferred pharmacies. This issue relates to the broader discussion on the decreasing plan liability and proposals to realign the incentives to manage spending in Part D.^29,30 Preferred networks’ net effect on government spending on Part D, though, would also depend on the magnitude of the cost savings in the form of potentially lower total net drug prices.

However, it is unclear how much cost savings preferred networks generate and how much of those savings are passed through to beneficiaries. Despite moderate pharmacy switching, other evidence seems to suggest that preferred networks have been lucrative for plans. Based on point-of-sale prices, Starc and Swanson estimated cost savings of around 2% as a result of such networks.¹⁷ The fast-growing pharmacy price concessions may be the other important component of the cost savings. However, we were unable to causally estimate the cost savings because detailed pharmacy fee data were proprietary. Additionally, similar to the case of manufacturer rebates, it is unclear to what extent higher pharmacy fees benefit beneficiaries, although they do save some money at the pharmacy counter when visiting preferred pharmacies and the fees help keep premiums low.¹⁸ Therefore, it is important for researchers and policy makers to uncover the magnitude of cost savings from preferred pharmacy networks and the distribution of the savings among beneficiaries, Medicare, and plans.

Limitations

First, by using current-year claims to simulate beneficiaries’ spending in different pharmacy use situations, we implicitly assumed that pharmacy choice—and cost sharing resulting from that—had no impact on utilization. We performed a sensitivity analysis by simulating based on prior-year claims for a subset of the sample who were in the same plan during each 2-year period, and the results were similar. Second, the analyses of pharmacy switching focused on plans that transitioned to a preferred network, thus excluding new plans that entered Part D with a preferred network. Nevertheless, due to the high level of inertia in Part D plan enrollment,^23,24,31 the enrollment in the latter plans was only one-fifth of that in the former. Third, the analyses also excluded beneficiaries exiting their plan at the implementation of a preferred network, who used preferred pharmacies less frequently in the year prior (eAppendix Table 3). To the extent that plan switching negatively correlated with the willingness to switch pharmacies, the analyses might slightly overestimate the shift toward preferred pharmacies. Finally, this study did not use data beyond 2016. More recent trends of financial incentives and beneficiaries’ shift toward preferred pharmacies are important topics for future research. Also, our analyses did not include Medicare Advantage (MA) beneficiaries, because only 21% of MA beneficiaries were in plans with a preferred network by 2016. Future research should examine MA plans using more recent data, given the growth of MA enrollment and the recent increase in preferred networks in MA.

CONCLUSIONS

The emergence of preferred pharmacy networks is an important yet understudied recent development in Medicare Part D. The financial incentives to use preferred pharmacies, pharmacy switching, and the financial consequences of continuing to use nonpreferred pharmacies differed between non-LIS and LIS beneficiaries. Further research is needed on their impact on the quality of beneficiaries’ decision-making and cost savings in order to fully assess the costs and benefits of preferred pharmacy networks.

Author Affiliations: Sol Price School of Public Policy (JX), Leonard D. Schaeffer Center for Health Policy & Economics (ET, GJ), and Department of Pharmaceutical and Health Economics, School of Pharmacy (ET, GJ), University of Southern California, Los Angeles, CA; now with Johns Hopkins Bloomberg School of Public Health (JX), Baltimore, MD.

Source of Funding: This work was supported by the Oakley Endowed Fellowship from the USC Graduate School and USC Schaeffer Center for Health Policy & Economics.

Author Disclosures: Dr Xu reports receiving grant support from Arnold Ventures outside the scope of this work. Dr Trish reports receiving consulting fees from Centene related to litigation for out-of-network services, receiving consulting fees from Cedars-Sinai Health System related to value-based care and health care policy, serving as an expert witness for Varian Medical Systems and Mallinckrodt, receiving compensation from Cornerstone Research for her work as an expert, and receiving grant support from Arnold Ventures and the Commonwealth Fund outside the scope of this work. Dr Joyce reports no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (JX, ET, GJ); acquisition of data (GJ); analysis and interpretation of data (JX, ET, GJ); drafting of the manuscript (JX, ET, GJ); critical revision of the manuscript for important intellectual content (JX, ET, GJ); and supervision (ET, GJ).

Address Correspondence to: Jianhui Xu, PhD, Johns Hopkins Bloomberg School of Public Health, 624 N Broadway, Room 513A, Baltimore, MD 21205. Email: jxu123@jhu.edu.

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