Adrian Towse, MA, MPhil

To estimate the long-run average cost (LAC) for a typical drug, accounting for the effects of generic competition and medical cost offsets. 

Descriptive analysis of retrospective cross-sectional survey data.

 We estimated the LAC for a drug as the average price per unit paid over the lifecycle of the drug, discounted across all time periods using Medical Expenditure Panel Survey data, and accounted for the effects of generic competition and medical cost offsets attributable to the use of pharmaceuticals.

 The average market-weighted price fell rapidly after generic entry. As a result, the brand price in the year prior to generic market entry was 39% (95% confidence interval [CI], 37%-43%) higher than the LAC per 30-day supply or package. When accounting for medical cost offsets, the brand price in the year prior to generic market entry was 75% (95% CI, 69%-79%) greater than the LAC per 30-day supply or package. The brand price at launch was 11% more than the LAC, and 40% more than the LAC net after adjusting for medical cost offsets. 

 Branded drug prices might overstate the true long-run cost of pharmaceuticals by 40% to 75%, accounting for generic price reductions and medical cost offsets. To ensure that all drugs providing long-run value end up entering the marketplace, market access and other policy decisions should consider the full range of long-term costs—and not just prices&mdash;at a particular point in time.

Using Medicare Expenditure Panel Survey data (1996-2013), this study estimated the long-run average cost (LAC) for an average pharmaceutical, accounting for the effects of generic competition and medical cost offsets. 

Focusing on branded drug prices may significantly overstate the LAC. 

Accounting for patent expiration, the loss of exclusivity price and the launch price overstate the LAC by 39% and 11%, respectively, and the LAC net of medical cost offsets by 75% and 40%, respectively. 

To ensure that all drugs providing long-run value end up entering the marketplace, value assessments or related market access decisions should consider these long-term costs.

The policy debate over the price of prescription drugs continues to intensify. For example, the recent introduction of very expensive and highly effective treatments for hepatitis C, along with innovative therapies for many cancers, has deepened concern about patients’ ability to afford innovative medicines.

 However, the debate does not consider the effect of patent expiration and the loss of exclusivity on drug prices. The price of prescription drugs depends on the nature and consequences of generic competition. Criticism has swirled around a cadre of generic drug manufacturers inflating prices for long-established compounds that, for various reasons, lack generic competitors. For instance, the price of digoxin, an “ancient” treatment for heart failure and atrial fibrillation, deemed an essential medicine by the World Health Organization, doubled over 6 months.

 However, for many widely used drugs, generic competition reduced prices significantly—and swiftly. Patent expiration lowered the price of simvastatin by 89% in 5 years and the price of clopidogrel by 46% in 1 month.

 These conflicting anecdotes provide little guidance to policy makers about the extent to which patent expiration lowers the long-term cost of drugs. Much has been written about the ability of drugs for specific diseases to reduce the need for other medical costs, yet little is known about the extent these “cost offsets” lower long-term costs associated with the average drug.

To address these knowledge gaps, we estimated the long-term cost of prescription drugs to patients, accounting for patent expiration and medical cost offsets. Focusing on the price of a drug at a given point in time can help inform discussions on which patients should use a drug and what the aggregate costs will be at that point

However, the value of innovation depends on the long-term cost of a new drug, and this has not been quantified previously. 

Drugs add long-term value to society when each unit sold produces a long-term benefit that exceeds long-term cost. To facilitate the assessment of long-term value, we estimated the long-run average cost (LAC), defined as the long-run cost per unit of the drug. We derived a formula for the LAC that formalizes this intuition (

The formula expresses the LAC as an average cost per unit of a drug. To illustrate, imagine that a branded drug costs $5 per fill and its generic equivalent costs $1 per fill. Imagine further that, over the lifecycle of the drug, 1000 branded prescriptions are filled and 5000 generic prescriptions are filled. The LAC is given by the weighted average cost per fill, which equals: ($5 × 1000 + $1 × 5000) / (1000 + 5000) = $1.40. 

Apart from generic price reductions, there are 2 additional factors we incorporated into this simple framework. First, a given drug may be produced as multiple dosages or by multiple manufacturers. Thus, the LAC calculates prices and quantities across a number of different dosages and product types. Continuing with the example above, suppose the drug comes in 5-mg and 10-mg doses, and each dosage accounts for half of branded fills; the 5-mg dose costs $2.50 and the 10-mg dose costs $7.50. In this more complex setting, we continued with our principle that the LAC was given by the weighted average cost per fill, which equals: ($2.50 × 500 + $7.50 × 500 + $1 × 5000) / (500 + 500 + 5000) = $1.40.

Second, timing matters. Using a prescription today is worth more than delaying until tomorrow. In economic analysis, this is known as the social discount factor, which measures the rate at which consumer well-being decreases from delaying consumption. Following the economics literature, we employed a 3% annual discount rate.

 Continuing with the earlier example, suppose that our hypothetical drug was on patent for 1 year only, generics entered after that year, and all drugs sold in year 2 were generic. The discount factor would enter our LAC calculation (in italics) as follows: ($2.50 × 500 + $7.50 × 500 + $1 × 5000 

) = $1.68. Discounting lowers the contribution of future prescriptions and thus shifts up the LAC in the direction of current period prices. In the eAppendix, we demonstrated proof that the LAC, as formulated here, possessed the following desirable and intuitive property: a drug adds incremental value to society if, and only if, the value per prescription exceeds the LAC.

We next incorporated medical cost offsets in the LAC. We took the average reduction in cost per prescription occurring as a result of avoided nondrug medical costs from the literature. We applied this cost reduction to the LAC to derive the LAC net of medical cost offsets (LAC net). A formal expression for the LAC net can be found in the eAppendix. As an example, we supposed that our hypothetical drug saved 25 cents in medical costs per prescription sold. This cost offset would enter our calculation (in italics) as follows: ([$2.50 — 

] × 5000 × [1 — 0.03]) / (500 + 500 + 5000 × [1 – 0.03]) = $1.43. Notice that adding the cost offset brought down the LAC by exactly 25 cents. In our empirical analysis, we were particularly interested in how the LAC and the LAC net compared with the price of the drug at the time of generic entry and at launch. 

The first step was to estimate prices for a wide sample of drugs. The host database for the price analysis was the Medical Expenditure Panel Survey (MEPS) Prescribed Medicines File from 1996 to 2013.

 The MEPS data are nationally representative, with detailed information on healthcare use, expenditures, sources of payment, and health insurance coverage. It has a household component that provides respondents’ self-reported information, including utilization of prescribed medicines. 

We defined the year of loss of exclusivity (LOE) as the first year we observed utilization of a generic National Drug Code (NDC) for a drug. The sample of medicines included those drugs whose LOE occurred in 1997 or later. Within this sample, we observed drug prices as early as 17 years before LOE and up to 16 years after LOE. For example, if a drug lost exclusivity in 2000, we observed prices for 3 years pre-LOE and 14 years post LOE. There were no biologics present in the sample because we did not observe LOE before 2013. We also excluded vaccines, medical devices, prescribed vitamins, and drug classes not meant for immediate patient use. 

The MEPS Household Component and pharmacy follow-back surveys measured pharmacy transaction prices. Rebates paid by the manufacturer to the insurer (eg, through the Medicaid Drug Rebate Program or contractual agreements negotiated between manufacturers and private insurers) were excluded. Prior literature has estimated that MEPS aggregate drug spending figures are modestly higher (3%) than national benchmarks,

 possibly due to the exclusion of rebates and other potential sources of measurement error. We conducted a sensitivity analysis to assess the potential effect of passed-through rebates on our estimates by lowering MEPS branded drug prices by 10% during the exclusivity period.

For each instance of drug utilization in the MEPS, the database records the associated NDC. As a single drug may have multiple NDCs, we used the Medi-Span Electronic Drug File to create a crosswalk from the NDC number to a drug—dose level identifier and linked this crosswalk to the MEPS data by NDC. Medi-Span is a database of drug and clinical information including active ingredients, generic equivalents, and therapeutic class. 

Prices were aggregated from the NDC level up to the drug—dose level in 3 stages. First, as each MEPS respondent could have had multiple purchases of the same NDC within a year, we calculated the average price paid per individual by year and NDC. Then, we constructed the national average by computing the survey weighted average price for each NDC by year across users of that NDC. Lastly, we calculated the NDC utilization weighted average of each drug by dose (or package size), type (brand or generic), and year.

Our sample included 132 therapeutic classes, 259 drugs, and 1229 different drug—dose combinations. The sample contained all drugs that experienced LOE during the sample window, with the exception of the exclusions noted above. This covers a broad set of drugs for a wide variety of diseases. We observed prices and utilization of these drugs from 1997 to 2013. 

We measured quantity as the number of prescription fills of a drug, dose (or package size), and type (brand or generic) per year. Quantities were aggregated up to the national level by summing the product of the MEPS survey weight and number of fills for each unique individual using a particular drug, dose, and type by year. 

Lastly, we estimated the direct medical cost offset per prescription fill. We conducted a targeted literature search for reviews and meta-analyses on the effects of pharmaceutical use on direct costs or medical/nonpharmaceutical spending. The goal was 2-fold: to estimate the direct cost offsets associated with pharmaceutical use and determine a plausible range of effects for medical cost offsets. We searched for estimates of the reduction in direct costs/medical expenditures associated with the use of a wide group of drugs, rather than only a few specific classes, for 1 month (30-day supply). 

Pharmaceutical Utilization and Prices Over Time

 illustrates that the average number of brand fills declined significantly after LOE (year post LOE of 0) and was more than offset by a concomitant increase in generic users in the following years. In the year generics entered the market, they captured 33% market share on average. This rapid capture of market share is consistent with previous research.

 After 5 and 10 years, generics possessed 74% and 77% of the market, respectively. 

 depicts the year-to-year time series for average brand or generic price relative to the price in the year before generic entry (LOE price). The average brand price increased throughout the drug’s lifecycle, but the average generic price tended to decrease for at least 10 years. The average generic price was 66% below the LOE price 5 years after generic entry and 80% below 10 years after generic entry. 

 presents the implications for the price of the average prescription (generic or branded) sold in the marketplace. This Figure demonstrates that the average market-weighted price fell rapidly after generic entry. In the year generics entered the market, the market price was 6% lower than the LOE price. After 5 years, it was 55% lower than the LOE price, and after 10 years, it was 71% lower.

Next, we explored the extent to which medical cost offsets reduced the long-term cost of pharmaceuticals. Our targeted literature search generated 13 articles on direct cost offsets associated with pharmaceutical use and/or pharmaceutical spending.

 Four of these studies contained information and estimates that allowed for the calculation of the effect of pharmaceutical use on medical (nonpharmacy) spending. Only 1 study, from the Congressional Budget Office (CBO), was representative of a large population (Medicare beneficiaries) and a broad set of therapeutic classes.

In 2012, the CBO estimated that a 1% increase in the number of prescriptions filled per year resulted in a 0.2% (95% confidence interval [CI], 0.1%&shy;-0.4%) decrease in medical expenditure per year. Based on the 2012 CBO study

 and information on the aggregate number of prescription fills and total healthcare expenditures in 2014, we estimated that each additional prescription filled (30-day supply) reduced medical expenditures by $94 per year ($8/month) (

 The cost savings in Medicare for specific chronic conditions, including diabetes and hypertension, were even higher.

We first calculated the LAC, which reflects the effects of generic entry and price declines. We reported this as a fraction of the LOE price and estimated that the LOE price was 39% (95% CI, 37%-43%) higher than the LAC per 30-day supply or package (

We calculated direct medical cost offsets of $94 per year ($8/month) then estimated the LAC net after applying this cost reduction to the drug prices in the data. On average, the LOE price was 75% (95% CI, 69%-79%) greater than the LAC net per 30-day supply or package. 

Pharmaceutical Costs Relative to Launch Prices

The analysis above compared the LOE price with LAC and LAC net. Another relevant comparison was to the brand price at launch. This calculation was more difficult, because the length of our sample window did not allow us to follow many drugs from launch well into the post—patent expiration period. As a rough approximation, we calculated the average percentage difference in price between the year prior to generic entry and the average year of launch. Using the FDA Orange Book Data, we found that for the average small molecule, 14 years elapse between the drug launch and the LOE. Moreover, according to Figure 3, the (real) brand price 14 years prior to generic entry was 80% of the price in the year just prior to generic entry. The LOE price was 39% more than the LAC and, thus, it follows that the launch price was 11% (= 1 – [0.8 × 139%]) more than the LAC. Similarly, the launch price is 40% (= 1 – [0.8 × 175%]) more than LAC net. 

As it is well understood that generic entry lowers prices, policy makers should consider the long-term cost of pharmaceuticals, rather than the cost at a particular point in time. We showed that these price reductions meaningfully lowered the average cost per prescription that patients pay over a drug’s lifetime. Branded drug prices were 11% above the LAC at launch and 39% above the LAC at patent expiration. Incorporating cost offsets brought these differentials to 40% and 75%, respectively, above the LAC net. Noting that long-run generic prices lie 80% below the branded price at patent expiration, the LAC net was roughly halfway between the pre-expiration branded price and the long-run generic price. 

Branded prices, generic prices, and the LAC all play important roles in economic decisions, which are made on the margin. Prices at a point in time matter to payers, who must decide if the benefit of treating 1 more patient outweighs the cost. The LAC and the LAC net, however, should matter to regulators, policy makers, and payers assessing whether a new drug can be marketed or reimbursed. In this context, overstating the eventual cost of a drug may lead to fewer drugs being made available, weaker incentives to innovate, and ultimately, fewer new drugs discovered. The use of the LAC and the LAC net could mitigate these effects by informing decision makers about the true value drugs add to society along all their lifecycle. For example, health technology assessments (HTAs) could include an assessment of the cost-effectiveness ratio that discounts the launch price—the most frequently used measure of drug cost&mdash;by 11% (excluding cost offsets) or 40% (including cost offsets). Not only should HTAs incorporate medical cost offsets, but they should also consider the long-run unit cost of a drug. 

As research has demonstrated, robust generic drug markets play a key role in holding down the LAC of drugs. Thus, policy makers should aim to mitigate barriers to entry for new generic drugs and ensure the continued safety of the generic drug supply. This is particularly relevant for specialized products that do not attract significant generic entry or competition. Recent events (eg, the 5000% overnight price increase of daraprim) demonstrate the importance of preserving competition within those market segments.

Medical cost offsets play a material role in holding down the LAC. This suggests the importance of taking an integrated view across pharmacy and medical benefits. Some have argued that standalone prescription drug insurers offer less-efficient benefit designs because they fail to internalize spillovers between prescription drugs and medical care.

Our estimate of the LAC may have overstated the actual LAC because we lacked data on rebates paid from manufacturers to payers. These may have been significant during the period of patent protection. Our analysis was also limited by the timeframe of the MEPS data. We were only able to characterize trends in price and utilization for drugs that lost exclusivity in 1997 or later; thus, we could only observe the first 15 years after LOE, even though many drugs were used for more than 15 years following LOE. On the other hand, we observed up to 16 years prior to LOE, likely covering the vast majority of the patent-protected period when market prices are highest. Therefore, our estimate might overstate the LAC. 

Our estimate covered only the population of drugs for which generics end up being used. Although this is not fully representative, this represented the vast majority of drug utilization. In 2013, for instance, drugs with generic alternatives represented at least 86.4% of prescription drug utilization in MEPS and these generic alternatives presented 81.0% of prescription drug utilization in MEPS. As some of the remaining 13.6% will inevitably include some patent-protected drugs that will eventually go generic, this is a conservative estimate of the fraction of use due to drugs with generic utilization. 

Another limitation concerns the estimate of direct cost offsets. Our estimate is based on a CBO study of medical cost offsets over a broad sample of drugs for Medicare beneficiaries.

 It is possible that cost offsets within Medicare may be different from the effects in the non-Medicare population. Future research might consider estimating cost offsets outside Medicare in a broad-based sample for comparison. We also took a conservative approach to measuring the cost offset effects of drugs. For example, the results of several studies suggest that pharmaceuticals produce financial benefits for employers by increasing the productivity of workers with chronic illnesses. Biologics for rheumatoid arthritis, antihistamines for allergies, selective serotonin reuptake inhibitors for depression, and triptans for migraine are commonly studied treatments that have been shown to increase productivity.

 However, as productivity estimates are highly specific to particular classes of drugs, we excluded them from our analysis and our estimate of the LAC net. Future research might explore drug class or disease state—specific LAC and LAC net values that reflect direct and indirect cost offsets.

Articles

This study found that brand price at launch and generic entry overstates long-run average pharmaceutical costs, with and without accounting for medical cost offsets.

What Do Pharmaceuticals Really Cost in the Long Run?

Risk-sharing agreements (RSAs) between drug manufacturers and payers link coverage and reimbursement to real-world performance or utilization of medical products. These arrangements have garnered considerable attention in recent years. However, greater use outside the United States raises questions as to why their use has been limited in the US private sector, and whether their use might increase in the evolving US healthcare system. 

 To understand current trends, success factors, and challenges in the use of RSAs, we conducted a review of RSAs, interviews, and a survey to understand key stakeholders’ experiences and expectations for RSAs in the US private sector.

Trends in the numbers of RSAs were assessed using a database of RSAs. We also conducted in-depth interviews with stakeholders from pharmaceutical companies, payer organizations, and industry experts in the United States and European Union. In addition, we administered an online survey with a broader audience to identify perceptions of the future of RSAs in the United States. 

Most manufacturers and payers expressed interest in RSAs and see potential value in their use. Due to numerous barriers associated with outcomes-based agreements, stakeholders were more optimistic about financial-based RSAs. In the US private sector, however, there remains considerable interest—improved data systems and shifting incentives (via health reform and accountable care organizations) may generate more action.

 In the US commercial payer markets, there is continued interest among some manufacturers and payers in outcomes-based RSAs. Despite continued discussion and activity, the number of new agreements is still small.

	This research assessed whether risk-sharing agreements between US commercial payers and pharmaceutical companies may become of greater interest with improved data systems and shifting incentives (via health reform and accountable care organizations). Key findings: 

		While such agreements offer numerous advantages to payers, pharmaceutical companies, patients, and society, their growth remains stagnant in the United States, due in large part to the additional effort required to implement and adjudicate risk-sharing agreements as compared to traditional rebates. 

		In the US private sector, however, there remains considerable interest: improved data systems and shifting incentives may generate more action.

Risk-sharing agreements (RSAs) between drug manufacturers and payers—also called performance-based risk-sharing arrangements (PBRSAs), managed entry agreements, patient access schemes, and coverage with evidence development (CED), among other terms&mdash;link coverage and reimbursement levels to real-world performance or utilization of medical products.

 These arrangements have garnered considerable attention in recent years: a recent analysis of the University of Washington Performance-Based Risk-Sharing (PBRS) Database,

 including 148 arrangements over the last 2 decades, concluded that although the overall pace of adoption seems to be slowing, several new countries have begun to implement RSAs.

 In the United States, the largest number of arrangements has been in the Medicare program; the uptake of private sector RSAs seems stagnant despite growing interest in the general principle of “paying for performance.” The aim of this study was to assess the state of and prospects for private sector RSAs in the United States, considering by comparison experiences from other countries, most commonly involving public payers.

RSAs offer a number of potential advantages,

including: 1) reducing the risk to payers of making a suboptimal purchase; 2) providing earlier access to medications for patients; 3) creating international pricing efficiency, especially in a world with external reference pricing and parallel trade; and 4) generating evidence on what works in the real world. These potential advantages, coupled with the higher volume of use outside the United States, raise questions as to why they have seen limited use in the United States,

 as well as what arrangements might gain traction with the new emphasis on accountable care organizations (ACOs), which operate under stronger incentives to manage patient care efficiently.

Previous work in this area has characterized the types of RSAs, trends in their adoption, economic incentives and rationale, and the drivers and barriers for adoption, but has not focused on current thinking in the US private sector. A broad distinction has been made between “outcomes-based” RSAs and “financial-based” RSAs. For the former, the manufacturer provides or agrees to rebates, refunds, or price adjustments if their product fails to meet agreed-upon clinical outcome targets. For the latter, reimbursement is tied to financial measures (eg, total sales) or to utilization. Here, we focus on the US private sector marketplace and particularly on the level of interest in outcomes-based agreements; specifically, we sought to understand the barriers to and drivers of developing private sector RSAs in the United States. We also explored whether the current situation reflects a broader demand by regulators and payers for greater real-world data and comparative evidence.

To assess the validity of the general perception of the lack of uptake of RSAs in the United States, we conducted a review of the University of Washington’s PBRS Database to assess the number of US agreements and trends in the number of agreements over time. For comparison, we also examined the number of agreements for the rest of the world. At the time of the study, the database included information on RSAs initiated from January 1993 to December 2013, with information on the parties participating in the arrangement, the type of arrangement, and details of the arrangement and/or outcomes, as available.

To understand current trends, success factors, and challenges in the use of RSAs, we conducted key informant interviews and an online survey to understand key stakeholders’ experiences with RSAs both inside and outside the United States as well as lessons for the US private sector situation. We used purposive sampling to identify 16 key stakeholders from pharmaceutical companies, payer organizations, and industry experts in the United States and European Union. We developed the interview guide and survey based on previous work in the area

 and through iterative review and revision by a group of content experts. The key informant interviews consisted of in-depth, 1-hour telephone interviews conducted between October 2013 and May 2014. Interview topics included: experience with RSAs, motivating factors, administrative considerations, effectiveness of agreements, and potential for use in the future (

). To identify themes from the interviews, we assessed the number of interviewees who stated or generally agreed with key statements across all interviews.

The survey was administered via the Web in May 2014, and consisted of 8 questions that asked respondents about their expectations for the future of RSAs in the United States and to identify and rank key barriers to their use (

). We identified themes by assessing the number of respondents who provided similar answers to the surveys. We invited a convenience sample of 37 individuals to complete the survey. Given the small sample size, we summarized responses using descriptive statistics.

Our review of the PBRS Database identified 148 RSAs worldwide from the late 1990s and 2013. Only 18 of the 148 total arrangements in the University of Washington Database, or 12.2%, represent US RSAs: 11 of these were public sector coverage with evidence development schemes, while only 7 were private sector RSAs. A review of the number of agreements annually suggests a little growth in the number of agreements in the United States. To date, RSAs have been more frequently employed in single-payer systems across Europe, Canada, and Australia.

Of the 16 individuals targeted for our key stakeholder interviews, we were able to schedule and conduct interviews with 14 (87.5%). The 14 in-depth interviews included 9 interviews with US stakeholders and 5 interviews with EU stakeholders. Of these, 7 were from pharmaceutical companies, 5 were currently or previously employed by payer/government organizations, and 2 were subject matter experts. We received 15 responses to our survey (response rate of 40.5%), including 10 responses from individuals from pharmaceutical companies, 3 from payers/pharmacy benefit managers, and 2 from other nonprofits and consultancies. The majority of respondents (93.3%) were from the United States.

In general, our interviews suggest that while there is interest in RSAs, there has been limited use in the United States due to difficulties in implementing and carrying out such agreements. The majority of interviewees (12 of 14) were cautiously to mildly optimistic about the future potential for outcomes-based RSAs to be adopted in the United States. To illustrate the basis of this position, selected comments and quotations from interviews are shown in 

, and are organized to represent comments ranging from more optimistic, to cautious, to more pessimistic. Roughly half of manufacturers and payers expressed interest in outcomes-based RSAs and see value in their use; almost all were optimistic about the use of financial-based RSAs. In general, due to the difficulty in implementing and executing outcomes-based RSAs, interviewees indicated an interest in more financial-based RSAs (eg, utilization or financial capitation) but less interest in clinical and health outcomes-based RSAs.

Outcomes-based agreements, while attractive to some, were perceived by interviewees to be difficult to execute and as having high transaction costs. Interview respondents were skeptical about being able to use outcomes-based RSAs, citing challenges in implementing and executing outcomes-based RSAs that would mitigate their potential in the United States, particularly given the fragmented payer system with patient movement across plans, as well as the current lack of data infrastructure that limits feasibility and, to some extent, interest in measuring long-term outcomes. Interview respondents indicated that simpler, financial-based agreements, on the other hand, have had demonstrated success. The survey responses corroborated the general support for financial-based RSAs seen in the interviews: 80% of respondents stated that the use of financial-based RSAs in the United States would grow.

The interviews suggest that the perceived value of an RSA versus a traditional discount mechanism depends on the product, disease area, and availability of the necessary data infrastructure. The manufacturers we interviewed stated that they would use RSAs as a way to differentiate and demonstrate the effectiveness of their product versus competitors. RSAs are typically not used in a US setting when a product is first to market or the market leader, but are more attractive to manufacturers when there is competition. The manufacturer seeks to secure beneficial formulary placement or gain market share. They can also be a mechanism to increase patient compliance.

Based on our interviews, US payers leverage—or would like to leverage&mdash;RSAs as a way to reduce uncertainty about a product’s clinical value, performance, or budget impact, as they allow payers and patients to gain experience with the medication. As payers and regulators are often interested in different types of data, at the time of launch, a product’s impact on costs and comparative effectiveness is often not well understood. Ultimately, payers expressed interest in RSAs as they allow payers to ensure that the price of a drug is more closely aligned to its value. During our interviews, payers indicated interest in RSAs for products that are more costly (eg, specialty drugs, biologics, combination products) and for disease areas for which cost consequences are substantial. Payers are not interested in engaging in RSAs for undifferentiated products where there is no real or perceived advantage.

 lists potential barriers to implementing RSAs that were identified during the interviews. The implementation and execution of RSAs is perceived to present a significant administrative burden that requires a substantial time investment. Further, outcomes-based agreements require significant payer and provider infrastructure: if payers lack the databases required to track individual patients, outcomes-based RSAs are difficult. Additional challenges that were mentioned include a) the need for adequately trained staff, b) the risk to pharmaceutical companies associated with being responsible for outcomes when they cannot control the way a drug is prescribed or used, c) the management of consequences in terms of changing preferred drugs and denying coverage for drugs, and d) the identification of outcomes that are meaningful but measurable within a reasonable time frame.

We tested the barriers identified during the interviews with a broader audience in the survey by asking respondents to rate and rank from the list of barriers provided in Figure 4 and any additional barriers not listed. The interview themes were consistent with the top barriers identified in the survey (

). The significant additional effort associated with RSAs was selected as the number 1 barrier to the use of RSAs in the United States by 33% of respondents and as the number 2 barrier by 27% of respondents. Inadequate data infrastructure was cited as the number 1 barrier by 27% of respondents and as the number 2 barrier by 33% of respondents. Other barriers that were selected as one of the top 3 hindrances to conducting RSAs in the United States included: federal (Medicaid) best price (40% ranked this as one of the top 3 barriers), significant resources/costs of adjudication (40%), challenges in measuring relevant outcomes (27%), and difficulty in reaching contractual agreement (27%).

While not necessarily barriers, there were several logistical challenges highlighted during our interviews that may be a consideration for both payers and pharmaceutical companies when evaluating opportunities for RSAs. The number of agreements in place with a given payer or for a given class of drugs is a key consideration. While payers expressed interest in having multiple agreements for competing products, pharmaceutical manufacturers indicated this becomes a complex arrangement that they are reluctant to enter. Further, only large payers are likely to have the capability for multiple, simultaneous agreements, given the burden of negotiation, data collection, monitoring, and adjudication of RSAs. Another key consideration is duration, as payers and manufacturers agree that short-term deals are not desirable given the considerable investment in evidence development. On the other hand, they state that long-term deals are also not desirable given the costs and risks involved. Both parties acknowledge that medium-term deals (18-36 months) are the right balance trading off the sizable up-front investment and a preference to execute agreements reasonably fast.

Access to clinical data was stated as a key barrier to the use of RSAs; scenarios where clinical data are more readily available make RSAs more feasible. For instance, interviewees indicated it may be easier to measure health outcomes for drugs that are administered in settings where there are more immediate clinical data available (eg, the hospital setting), where drugs are administered in person, or when data are already being collected as part of ongoing processes (eg, performance measurement via the Healthcare Effectiveness Data and Information Set). Complex outcomes might be more easily measured where there is an active provider (eg, patient-centered medical homes). Similarly, interviewees stated outcomes-based RSAs can be most successful where the infrastructure is robust to collect such data, such as in single payer or closed settings including integrated delivery networks. Drug cost as a share of total episode cost can also be a factor.

A key success factor is the need for manufacturers to understand the amount of risk they are undertaking when entering into an RSA. Manufacturers feel they should be able to reasonably predict plausible outcomes of the agreement and assess the level of risk; for example, what level of compliance is required and to what extent the clinical trial population differs from the real-world population.

There are a few scenarios that are considered prohibitive to successful RSAs. Both parties indicated that trust is a critical component of agreements between pharmaceutical companies and payers. It is imperative that both parties trust the data: clear agreements on data validation and analysis are important to create trust in the data.

Certain types of agreements can also be problematic. For instance, manufacturers expressed that population-based agreements are perceived to be risky because there are many unknowns around compliance, prescribing, and so forth. Manufacturers are reluctant to take on risk when they cannot predict how their product will be used in the population. Agreements that involve the manufacturer paying for nonpharmaceutical costs are difficult to execute, as payers do not generally have the systems or data to support such agreements. Both parties shy away from agreements in disease areas where there are many different treatment paradigms or the relevant outcome is an intermediary outcome, because it can be challenging to attribute the outcome to the product in question.

Future Prospects: Barriers, Health Reforms, and Policy

This study confirms that very few private sector RSAs have been implemented in the United States; while payers and pharmaceutical companies remain interested in these types of agreements, various challenges restrict the types of situations in which they can be feasibly employed. Also, because of the effort required, payer and pharmaceutical respondents are less enthusiastic about outcomes-based agreements and more optimistic about simpler, financial-based agreements.

Although the global growth in RSAs seems to have slowed, several countries maintain robust programs, particularly Italy and Sweden, and interest is growing in Latin America and Asia. There has also been a broad shift to financial-based agreements for several reasons. Our research suggests that public payers, especially outside the United States, are attracted to making arrangements with manufacturers, first and foremost, to obtain an effectively lower price in a world where reference pricing and the prospect of parallel trade make differential (or tiered) pricing difficult. And, of course, this can benefit patients by providing earlier and broader market access. Second, few countries have an adequate data infrastructure to operate outcomes-based schemes efficiently.

The history of RSAs in the United States is dominated by the Medicare experience with CED. Although the interest remains, it seems to have waned. The growth in visible private RSAs in the United States seems to have stalled, but our interviews suggest growing interest and some new activity. There are multiple barriers in the United States—most prominently, the additional effort needed to negotiate and maintain these agreements relative to traditional rebates. The challenge of measuring individual-level outcomes in a claims-oriented data infrastructure makes operationalizing RSAs difficult because of the lack of relevant clinical outcomes contained in these data. Medicaid best price (and the similar 340B Drug Pricing Program) provisions, which link mandated discounts for public sector programs to private sector prices, are considered complications, but would seem to be manageable in a well-designed contract; notwithstanding, several interviewees regarded this as a major barrier.

If a medicine covered by an RSA does not perform as anticipated by the manufacturer and a price discount ensues, the reduced prices could be perceived as a new best price and made available to all Medicaid purchasers. In the case of Medicare, we were told that provisions around the Medicare 5-star rating program, which ties payment to achievement of certain quality metrics in health plans, have made adherence programs—a kind of outcomes-based program&mdash;attractive to payers. The preference for a short-term horizon of 18 months to 3 years being the most practicable arrangement in the US private health system, because it reduces long-term liability for manufacturers and payers, and limits the feasibility of RSAs in some disease areas.

Our interviewees were generally pessimistic as to whether the growth of ACOs would have any positive impact in the near term, since many ACOs are in the initial development and market experimentation phase

; however, they may well bring a new orientation to risk-sharing that will support the future development of pharmaceutical RSAs.

The ISPOR PBRSA Task Force emphasized that better information about what works in medicine is a global public good,

 but it still appears that the RSAs being developed in the United States will be confidential ones, with the knowledge gained only shared inadvertently or sporadically, rather than by design. Both payers and manufacturers have competitors, and they have some incentive to be “free riders” rather than developing innovative pricing schemes that yield knowledge on best medical practice. One of our payer interviewees—a national medical director for a major US payer&mdash;made this revealing and somewhat encouraging comment:

“If we learn something about a pharmaceutical by looking at our own data and we decide that we are going to use that information to make coverage determinations, it is our policy that we make that public (publish in a peer-reviewed journal). If the coverage decision is based on an economic analysis, that may be kept private; however, if the decision is based on something clinical, it has to be available for physicians and patients to evaluate.”

This suggests an important dichotomy between clinical and economic evidence, though they clearly become related when combined in a cost-effectiveness ratio or other assessment of value. It is not clear if this distinction is sustainable given that the recent joint American Heart Association and American College of Cardiology Task Force on Value and Cost called for consideration of cost-effectiveness in establishing clinical treatment guidelines in cardiology.

The growing emphasis on comparative effectiveness research in the United States, including the establishment of the Patient-Centered Outcomes Research Institute,

 are testimony to the fact that the country is investing more in generating real-world evidence on clinical outcomes and their related economic implications. In principle, RSAs will generate some of this information, but if the results remain confidential, the new knowledge will, at best, slowly diffuse through a healthcare system that aspires to become a “learning healthcare system.” This raises the question of the need for greater public policy intervention. The following question was not part of our remit in this study, but we should be asking: Are there other policy tools or incentives that could be used to encourage and leverage US private sector RSAs to reveal their lessons for the greater good of the system and all patients?

Assessment of current trends, success factors, and challenges in the use of risk-sharing agreements in the US private sector.

Adrian Towse, MA, MPhil

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