Increases In List Prices Research Articles

Changes In Net Prices And Spending For Pharmaceuticals After The Introduction Of New Therapeutic Competition, 2011-19.

Previous research has demonstrated that the introduction of a new brand-name pharmaceutical competitor does not lower list prices for existing competitive therapies. However, no study has systematically evaluated the impact of new therapeutic competition on net prices of pharmaceutical products. We identified new therapies approved during the period 2013-17 that were competitors for existing treatments. We used a novel peer-reviewed algorithm to estimate the net prices of existing therapies. We implemented regression models to estimate changes in these net prices after the approval of the new therapeutic competition during the period 2011-19. Across twelve therapeutic classes with new drug entrants in 2013-17, the introduction of new therapeutic competition was associated with a 4.2percent decrease in annual net price growth. The introduction of new brand-name therapies in twelve therapeutic classes reduced net commercial spending on existing therapies by $10.4 billion-an 18.5percent reduction in projected spending absent therapeutic competition. Our findings demonstrate that new therapeutic competition allows pharmacy benefit managers to use formulary management to decrease net prices and reduce drug spending, contrary to observed trends in list price increases.

Association of Branded Prescription Drug Rebate Size and Patient Out-of-Pocket Costs in a Nationally Representative Sample, 2007-2018

Over the past decade, branded prescription drug manufacturers have substantially increased list prices while offering larger rebate payments to health care insurers. Whereas larger rebates can partially offset increases in list prices for insurers, patient out-of-pocket costs may be directly associated with list prices for individuals without insurance and indirectly associated with list prices for individuals with insurance through deductibles or coinsurance. To investigate the association between rebates and patient out-of-pocket costs and whether this association differs by coverage type (ie, Medicare, commercial, or uninsured) and before and after 2014. This cross-sectional study was conducted using data from the Medical Expenditure Panel Survey (MEPS) combined with pricing data for single-source branded drugs from SSR Health from 2007 through 2018. The study was conducted among a nationally representative sample of the noninstitutionalized civilian US population. Included individuals were respondents to MEPS with at least 1 prescription for a single-source branded drug who were covered by Medicare or commercial insurance or were uninsured during an entire year. Data analyses were conducted from August 2019 through March 2021. Estimated rebate size. Out-of-pocket costs per prescription were calculated, adjusting for year and drug. Among 38 131 individuals with at least 1 prescription, the mean age was 54 years (95% CI, 54 to 55 years), with 22 044 women (57.8%) and 29 086 White individuals (76.3%). The sample included 444 unique drugs with a survey-weighted total of 4.7 billion prescriptions. Estimated mean (SE) rebates increased from $34 ($1) per prescription in 2007 to $374 ($9) per prescription in 2018. The rebate sizes were associated with statistically significant mean out-of-pocket increases per branded prescription of $4 (95% CI, $4 to $4) from 2007 to 2013 and $11 (95% CI, $10 to $12) from 2014 to 2018. From 2014 to 2018, rebate sizes were associated with statistically significant mean increases in out-of-pocket costs per prescription of $13 (95% CI, $12 to $13) for individuals with Medicare, $6 (95% CI, $6 to $7) for individuals with commercial insurance, and $39 (95% CI, $34 to $44) for individuals without insurance. After adjusting for list prices, there was no association between rebates and out-of-pocket costs, with a change from 2014 to 2018 of -$0.01 (95% CI, -$0.04 to $0.02). These findings suggest that drug manufacturers may have provided larger rebates to insurers primarily by increasing list prices and that individuals without insurance had greater cost increases. The results emphasize the need for policy solutions that decouple list prices and out-of-pocket costs.

Correlation Between Changes in Brand-Name Drug Prices and Patient Out-of-Pocket Costs

List prices set by manufacturers for brand-name prescription drugs in the US have been increasing faster than inflation, although confidential manufacturer rebates offset some of these increases. Most commercially insured patients pay at least some out-of-pocket costs for prescription drugs, and higher patient spending is associated with lower adherence and worse health outcomes. To examine whether price changes for brand-name drugs are correlated with changes in patient out-of-pocket spending and whether this association varies by insurance benefit design. A cohort study of 79 brand-name drugs with available pricing data from January 2015 to December 2017 was conducted, with data obtained from a national commercial insurance claims database. Change in the list prices set by manufacturers and estimated net prices after rebates among non-Medicaid payers. Change in median out-of-pocket spending among all patients and stratified by insurance pharmacy benefit design, including high-deductible insurance plans and plans with any amount of deductibles or coinsurance. Among 79 drugs, median increases were 16.7% (interquartile range [IQR], 13.6%-21.1%) for list prices, 5.4% (IQR, -3.9% to 11.7%) for net prices, and 3.5% (IQR, 1.4%-9.1%) for out-of-pocket spending from 2015 to 2017. Changes in list prices were correlated with changes in net prices (r = 0.34; P = .002). Overall, changes in out-of-pocket spending were not correlated with changes in list prices (r = 0.14; P = .22) or net prices (r = 0.04; P = .71). Among 53.7% of patients who paid any drug deductible or coinsurance, median out-of-pocket spending increased by 15.0%, and changes were moderately correlated with changes in list prices (r = 0.38; P = .001) but not net prices (r = 0.06; P = .62). Some commercially insured patients who pay only prescription drug copayments appear to be insulated from increases in drug prices. However, more than half of patients pay deductibles or coinsurance and may experience substantial increases in out-of-pocket spending when drug prices increase. Among these patients, there was no evidence that manufacturer rebates to insurers are associated with patients' out-of-pocket spending. Policies to rein in unregulated annual increases in list prices for brand-name drugs may have important consequences for patient out-of-pocket spending.

List Price Collusion

Firms sometimes collude by agreeing on increases in list prices. Yet, the efficacy of such list price collusion is subject to discussion as colluding firms might, in principle, deviate secretly from the elevated prices by granting their customers discounts. This article reviews cases of list price collusion in the USA and Europe, and it presents a theory of harm suggesting that a combination of anchoring, orientation on reference points, and loss aversion may render list price collusion effective in raising transaction prices—even if firms set transaction prices in a non-coordinated fashion.

Trends in list prices, net prices, and discounts of self-administered injectable tumor necrosis factor inhibitors.

BACKGROUND: List prices of tumor necrosis factor (TNF) inhibitors drastically increased during the last decade, but previous research has shown that half of these increases were offset by rising manufacturer discounts. It remains unclear to what extent manufacturers' discounts have offset increases in list prices of each self-administered injectable TNF inhibitor. Evaluating trends in net prices and discounts at the product level will be paramount in understanding the role of competition in the biologic market. OBJECTIVES: To (a) describe product-level changes in net prices of each self-administered injectable TNF inhibitor available in 2007-2019 and (b) quantify to what extent manufacturer discounts have offset increases in list prices. METHODS: We obtained 2007-2019 pricing data for etanercept, adalimumab, certolizumab, and golimumab from the investment firm SSR Health, which uses company-reported sales to estimate net prices and discounts for brand products manufactured by publicly traded companies. For each drug and year, we calculated annual costs of treatment for patients with rheumatoid arthritis based on list and net prices and discounts in Medicaid and other payers. RESULTS: From 2007-2019, list prices of etanercept and adalimumab increased by 293% and 295%, respectively; however, discounts offset 47% and 45% of these increases, leading to net price increases of 171% and 203%. List prices of golimumab and certolizumab increased by 183% and 182%, respectively, but with discounts offsetting 58% and 59% of these increases, net prices increased by 103% and 109%. Net prices of golimumab started to decrease after 2016, while net prices of adalimumab and certolizumab experienced their first drop in 2019. Across the study period, discounts in Medicaid and in other payers increased, respectively, from 21% to 85% and 6% to 32% for etanercept; from 26% to 88% and 19% to 35% for adalimumab; from 28% to 63% and 22% to 46% for golimumab; and from 29% to 83% and 27% to 47% for certolizumab. CONCLUSIONS: Despite growing manufacturer discounts, net prices of self-administered injectable TNF inhibitors still increased at a mean annual rate of 9.6% in 2007-2019. This led to net prices tripling for adalimumab and more than doubling for etanercept, golimumab, and certolizumab. DISCLOSURES: This study was funded by the Myers Family Foundation. Hernandez is funded by the National Heart, Lung and Blood Institute (grant number K01HL142847). Funding sources had no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. Hernandez has served on Pfizer's scientific advisory board. The other authors have nothing to disclose.

Assessment of Expected Out-of-Pocket Spending for Rheumatoid Arthritis Biologics Among Patients Enrolled in Medicare Part D, 2010-2019

The closure of the Medicare Part D coverage gap from 2010 to 2019 was intended to help decrease out-of-pocket costs for beneficiaries, especially those taking high-cost drugs. However, yearly increases in list prices and the introduction of newer and more expensive drugs may have limited savings for beneficiaries. To assess the association of closure in the Medicare Part D coverage gap with projected annual out-of-pocket costs from 2010 through 2019 for rheumatoid arthritis (RA) biologics. This cross-sectional analysis used data from the Medicare Formulary and Pricing Files for the first quarter (January 1 to March 31) in each calendar year from 2010 to 2019 for 17 RA biologic drug and strength combinations. Medicare Part D plan design and drug price by year. Expected annual out-of-pocket costs for 1 year of treatment. Among the 17 drug and strength combinations assessed, list prices increased each year for every product, with a mean increase of 160% for the 6 drugs available during the entire study period. For the 6 products available during the entire study period, projected mean (SD) annual out-of-pocket costs were 34% (2%) lower in 2011 than in 2010 ($6108 in 2010 to $4026 in 2011) but only 21% (8%) lower in 2019 ($4801) because of yearly increases in list price. All 4 products with higher out-of-pocket costs in 2019 than in the first year available entered the market between 2011 and 2015. For all products studied, the percentage of money spent in the catastrophic phase increased each year and was a mean (SD) of 22% (14%) higher in 2019 than in 2010 or the year first available. Although beneficiaries experienced large reductions in out-of-pocket spending from 2010 to 2011, more than half of those savings were lost by 2019 because of annual increases in list prices, even as the coverage gap continued to close in subsequent years.

Changes in List Prices, Net Prices, and Discounts for Branded Drugs in the US, 2007-2018

Most studies that have examined drug prices have focused on list prices, without accounting for manufacturer rebates and other discounts, which have substantially increased in the last decade. To describe changes in list prices, net prices, and discounts for branded pharmaceutical products for which US sales are reported by publicly traded companies, and to determine the extent to which list price increases were offset by increases in discounts. Retrospective descriptive study using 2007-2018 pricing data from the investment firm SSR Health for branded products available before January 2007 with US sales reported by publicly traded companies (n = 602 drugs). Net prices were estimated by compiling company-reported sales for each product and number of units sold in the US. Calendar year. Outcomes included list and net prices and discounts in Medicaid and other payers. List prices represent manufacturers' price to wholesalers or direct purchasers but do not account for discounts. Net prices represent revenue per unit of the product after all manufacturer concessions are accounted for (including rebates, coupon cards, and any other discount). Means of outcomes were calculated each year for the overall sample and 6 therapeutic classes, weighting each product by utilization and adjusting for inflation. From 2007 to 2018, list prices increased by 159% (95% CI, 137%-181%), or 9.1% per year, while net prices increased by 60% (95% CI, 36%-84%), or 4.5% per year, with stable net prices between 2015 and 2018. Discounts increased from 40% to 76% in Medicaid and from 23% to 51% for other payers. Increases in discounts offset 62% of list price increases. There was large variability across classes. Multiple sclerosis treatments (n = 4) had the greatest increases in list (439%) and net (157%) prices. List prices of lipid-lowering agents (n = 11) increased by 278% and net prices by 95%. List prices of tumor necrosis factor inhibitors (n = 3) increased by 166% and net prices by 73%. List prices of insulins (n = 7) increased by 262%, and net prices by 51%. List prices of noninsulin antidiabetic agents (n = 10) increased by 165%, and net prices decreased by 1%. List price increases were lowest (59%) for antineoplastic agents (n = 44), but discounts only offset 41% of list price increases, leading to 35% increase in net prices. In this analysis of branded drugs in the US from 2007 to 2018, mean increases in list and net prices were substantial, although discounts offset an estimated 62% of list price increases with substantial variation across classes.

Housing prices and the optimal time-on-the-market decision

This paper provides a model for housing prices based on a seller solving the optimal time-on-the market problem. Given the seller’s optimal time-on-the market, analytical expressions are provided for both the expected time-on-the-market and the sales price. These expressions facilitate the computation of comparative statics. Consistent with economic intuition, we show that (i) both the expected time-on-the market and sales price decrease as interest rates increase, (ii) the expected time-on-the market increases and the expected sales price decreases as offer activity declines, and (iii) the expected time-on-the market and expected sales price both increase as the list price increases.

Housing Prices and the Optimal Time-on-The-Market Decision

This paper provides a model for housing prices based on a seller solving the optimal time-on-the market problem. Given the seller's optimal time-on-the market, analytical expressions are provided for both the expected time-on-the-market and the sales price. These expressions facilitate the computation of comparative statics. Consistent with economic intuition, we show that (i) both the expected time-on-the market and sales price decrease as interest rates increase, (ii) the expected time-on-the market increases and the expected sales price decreases as offer activity declines, and (iii) the expected time-on-the market and expected sales price both increase as the list price increases.

The Trade-off Between the Selling Price of Residential Properties and Time-on-the-Market: The Impact of Price Setting

When a house is placed on the market, the seller must choose the initial offer price. Setting the price too high or too low affects the marketability of the property. While there is near universal agreement that the seller faces a trade-off between selling at a higher price and selling in less time, there is less agreement about how to measure this trade-off. This paper offers a framework for analysis and shows that an increase in the list price increases expected time-on-the-market (TOM). Because house buyers must solve a type of signal extraction problem, the effect of a higher list price is magnified for houses in a market segment having a low predicted variance of the list price. This paper also shows that the list price of houses which are withdrawn before sale has a higher mean and variance, and that the possibility of withdrawal censors information about the time-on-the-market.