What Do Pharmaceuticals Really Cost in the Long Run?

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.
Published Online: August 22, 2017
Darius Lakdawalla, PhD; Joanna P. MacEwan, PhD; Robert Dubois, MD, PhD; Kimberly Westrich, MA; Mikel Berdud, PhD; and 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. 

Study Design: Descriptive analysis of retrospective cross-sectional survey data.

Methods: 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.

Results: 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. 

Conclusions: 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—at a particular point in time.

Am J Manag Care. 2017;23(8):488-493
Takeaway Points

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.1-4 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.5 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.6,7 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. 


Conceptual Framework

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 (eAppendix, available at ajmc.com). 

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.8 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 – 0.03]) / (500 + 500 + 5000 × [1 – 0.03]) = $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 – $0.25] × 500 + [$7.50 – $0.25] × 500 + [$1 – $0.25] × 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. 

Measuring Market Prices

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 2013.9 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,10 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. 

Measuring Quantity

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. 

Measuring Cost Offsets

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