The impact of external reference pricing on pharmaceutical costs and market dynamics.
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ABSTRACT:
SUBMITTER: Voehler D
PROVIDER: S-EPMC10297733 | biostudies-literature | 2023 Dec
REPOSITORIES: biostudies-literature
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The impact of external reference pricing on pharmaceutical costs and market dynamics.
Voehler Dominic D Koethe Benjamin C BC Synnott Patricia G PG Ollendorf Daniel A DA
Health policy OPEN 20230324
Growth in the cost of prescription drugs in the US has generated significant interest in the use of external reference pricing (ERP) to tie prices paid for drugs to those in other countries. We used data from the Pricentric ONE™ database, an international drug pricing database, to examine product launch timing, launch price, and price changes from January 2010 - October 2021 in both ERP and non-ERP settings, with a focus on 100 high-priced drugs of interest to Medicare and Medicaid. We found tha ...[more]
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Project description:External reference pricing (ERP) is a price regulation tool widely used by policy makers in the European Union (EU) Member States (MS) to contain drug cost, although in theory, it may contribute to modulate prices up and down. The objective of this article was to summarise and discuss the main findings of part of a large project conducted for the European Commission ('External reference pricing of medicinal products: simulation-based considerations for cross-country coordination'; see www.ec.europa.eu/health/healthcare/docs/erp_reimbursement_medicinal_products_en.pdf) that aimed to provide an overview of ERP systems, both on processes and potential issues in 31 European countries (28 EU MS, Iceland, Norway, and Switzerland). A systematic structured literature review was conducted to identify and characterise the use of ERP in the selected countries, to describe its impact on the prices of pharmaceuticals, and to discuss the possible cross-country coordination issues in EU MS. This research was complemented with a consultation of competent authorities' and international organisations' representatives to address the main issues or uncertainties identified through the literature review. All selected countries applied ERP, except the United Kingdom and Sweden. Twenty-three countries used ERP as the main systematic criterion for pricing. In the majority of European countries, ERP was based on legislated pricing rules with different levels of accuracy. ERP was applied either for all marketed drugs or for specific categories of medicines; it was mainly used for publicly reimbursed medicines. The number of reference countries included in the basket varied from 1 to 31. There was a great variation in the calculation methods used to compute the price; 15 countries used the average price, 7 countries used the lowest price, and 7 countries used other calculation methods. Reported limitations of ERP application included the lack of reliable sources of price information, price heterogeneity, exchange rate volatility, and hidden discounts. Spill-over effect and downward price convergence have often been mentioned as ERP's consequences leading to pricing strategies from pharmaceutical companies. While ERP is widely used in Europe, processes and availability of price information vary from one country to another, thus limiting ERP implementation. Furthermore, ERP spill-over effect is a major concern of pharmaceutical firms leading to implementation of the so-called 'launch sequence strategies'.
| S-EPMC4802694 | biostudies-literature
Project description:Although the agricultural sector is globally a main emitter of greenhouse gases, thorough economic analysis of environmental and social externalities has not yet been conducted. Available research assessing agricultural external costs lacks a differentiation between farming systems and food categories. A method addressing this scientific gap is established in this paper and applied in the context of Germany. Using life-cycle assessment and meta-analytical approaches, we calculate the external climate costs of foodstuff. Results show that external greenhouse gas costs are highest for conventional and organic animal-based products (2.41€/kg product; 146% and 71% surcharge on producer price level), followed by conventional dairy products (0.24€/kg product; 91% surcharge) and lowest for organic plant-based products (0.02€/kg product; 6% surcharge). The large difference of relative external climate costs between food categories as well as the absolute external climate costs of the agricultural sector imply the urgency for policy measures that close the gap between current market prices and the true costs of food.
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Project description:IntroductionThe aim of the study was to evaluate, in a regulated generics market, the effect of the number of manufacturers of generic drugs on the amplitude of off-patent products price reduction and the price evolution of originators and generics after the patent expiry of pharmaceuticals dispensed by community pharmacies and reimbursed by the Italian National Health Service (INHS).MethodsThe AIFA "transparency list" was utilized to select unbranded and branded off-patent drug dispensed by community pharmacies and reimbursed by the Italian National Health Service between 2012 and 2018. The unbranded drug entry in the transparency list database was considered as a proxy of its patent expiry.ResultsA total of 42 different active ingredients were included in the analysis. The relative price per dose at time t of unbranded and branded drugs, considering as common denominator the price per dose a year before the patent expiry, (t-1) decreased with the increase of unbranded manufacturers. At the time of the patent expiry, the price of unbranded drugs was almost 50% less than that of branded drugs at t-1 and the price of branded drugs started to decrease before the first unbranded entry.ConclusionAn inverse relation between the number of generic drug entrants and the price of generics and originators was detected. The patent expiry determines a price decline, more concentrated in the first year of patent expiry.
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Project description:Drug repurposing is a group of development strategies employed in order to overcome some of the hurdles innate to drug research and development. Drug repurposing includes drug repositioning, reformulation and combination. This study aimed to identify the determinants of successful market access outcome for drug repurposing in the United States of America (USA) and in Europe. The case studies of repurposing strategies were identified through a systematic review of the literature. Price information and reimbursement conditions for all the case studies were collected mainly through access of public datasources. A list of attributes that could be associated with market access outcome (price level and reimbursement conditions) was developed, discussed, and validated by an external expert group. Detailed information for all attributes was researched and collected for each case study. Bivariate regression models were conducted to identify factors associated with price change for all repurposing cases. A similar analysis was performed for reformulation and repositioning cases, in the USA and in Europe, separately. A significance level of 5% was used for all analyses. A total of 144 repurposing case studies were included in the statistical analysis for evaluation of mean price change. Combination cases (the combination of two or more individual drug components) were excluded from the statistical analysis due to the low number of cases retrieved. The main attributes associated with a significant price increase for overall repurposing cases were 'change in administration setting to hospital' (374%, p<0.0001), 'addressing unmet needs' (69%, p<0.05), 'reformulations belonging to Group 3'-that is, change in administration route (117%, p<0.001), and being a repurposed product with the 'same brand name' as the original product (65%, p<0.05). We found that the ability of the repurposed product to address unmet needs, a reformulation where the target product had a different administration route than the source product, and having a similar brand name for repurposed and original products, were variables that impacted a positive price change for repurposed drugs overall. Our research results also suggested that orphan designation could have a positive impact for repositioning in the USA, in particular. Although a change of administration from ambulatory to hospital setting seemed to be significantly correlated with a price increase for the target product, only one case was retrieved for this parameter; as such, it was not possible to infer a firm correlation between this parameter and a change in price.
| S-EPMC4865758 | biostudies-literature
Project description:Objective: The study compared the relative cost differences of similar orphan drugs among high and low GDP countries in Europe: Bulgaria, France, Germany, Greece, Hungary, Italy, Norway, Poland, Romania, Spain, Sweden, UK. Methods: Annual treatment costs per patient were calculated. Relative costs were computed by dividing the costs by each economic parameter: nominal GDP per capita, GDP in PPP per capita, % GDP contributed by the government, government budget per inhabitant, % GDP spent on healthcare, % GDP spent on pharmaceuticals, and average annual salary. An international comparison of the relative costs was done using UK as the reference country and results were analysed descriptively. Results: 120 orphan drugs were included. The median annual costs of orphan drugs in all countries varied minimally (cost ratios: 0.87 to 1.08). When the costs were adjusted using GDP per capita, the EU-5 and Nordic countries maintained minimal difference in median cost. However, the lower GDP countries showed three to six times higher relative costs. The same pattern was evident when costs were adjusted using the other economic parameters. Conclusion: When the country's ability to pay is taken into consideration, lower GDP countries pay relatively higher costs for similarly available orphan drugs in Europe.
| S-EPMC5645904 | biostudies-literature
Project description:This paper investigates the pricing problem of quanto options with market liquidity risk using the Bayesian method. The increasing volatility of global financial markets has made liquidity risk a significant factor that should be taken into consideration while evaluating option prices. To address this issue, we first derive the pricing formula for quanto options with liquidity risk. Next, we construct a likelihood function to conduct posterior inference on model parameters. We then propose a numerical algorithm to conduct statistical inferences on the option prices based on the posterior distribution. This proposed method considers the impact of parameter uncertainty on option prices. Finally, we conduct a comparison between the Bayesian method and traditional estimation methods to examine their validity. Empirical results show that our proposed method is feasible for pricing and predicting quanto options with liquidity risk, particularly for parameter estimations with a small sample size.
| S-EPMC10538701 | biostudies-literature
Project description:BackgroundThe soaring costs of anti-cancer drugs pose a threat to the sustainability of cancer care. The pricing strategy chosen by manufacturers can impact the costs of oral anti-cancer drugs during dose modifications, but this issue remains under-recognized in the literature. In general, with the flat pricing strategy, there is a single fixed price for each tablet regardless of dosage strength, whereas with linear pricing, the price of each tablet increases with its dose. We hypothesize that flat pricing will have increased drug costs compared to linear pricing during dose reductions since the cost remains fixed despite decreased dose requirements. This practice may have significant financial implications considering the high costs, extensive utilization, and frequent occurence of dose reductions with anti-cancer drugs. METHODS: Oral anti-cancer drugs reviewed by the pan-Canadian Oncology Drug Review program between 2011 and 2018 were identified. The cost per mg and cost per 28-day cycle were calculated for dose levels -2 to +2. The percent change in cost per mg and cost per cycle during dose modifications from the standard dose were calculated. We conducted Mann-Whitney U and Fisher-exact tests to compare the association between drug costs during dose reductions and pricing strategy.ResultsIn this study, 30 oral anti-cancer drugs for use in 41 indications were analyzed; 44% of drugs used linear pricing and 56% used flat pricing. Dose reductions increased the mean cost per mg for drugs with linear pricing by 14.7% (range: 0%-50%) at dose level -1 and 17.2% (range: 0%-50%) at dose level -2 and flat pricing by 60.8% (range: 19%-100%) at dose level -1 and 99.1% (range: 0%-300%) at dose level -2. The cost per mg was significantly increased in drugs using flat pricing compared to linear pricing when dose reduction to either level -1 (P = 0.010) or level -2 (P = 0.006) occurred. The mean cost per cycle was decreased for drugs using linear pricing by 20.9% (range: -40% to 0%) at dose level -1 and 48.7% (range: -60% to -25%) at dose level -2 and flat pricing by 0.8% (range -6% to 0%) at dose level -1 and 11.0% (range: -50% to 100%) at dose level -2. The cost per cycle was significantly decreased in drugs with linear pricing compared to flat pricing when the standard dose is reduced to either dose level -1 (P = 0.005) or dose level -2 (P = 0.026).ConclusionsOverall, flat pricing had significantly greater costs compared to linear pricing during dose reductions of anti-cancer drugs. While there is a general expectation that the cost of drugs should decrease with dose reduction, drugs with flat pricing were generally found to have increased cost per mg and no change in the cost per cycle. The resultant increased spending on drug acquisition (despite purchasing lower doses) lead to financial wastage, which has significant implications on cost-effectiveness considerations and budgets. Future economic evaluations should take into consideration the hidden costs associated with dose reductions of flat priced drugs.
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Project description:The dairy sector in the European Union (EU) has experienced policy changes and market shocks recently. Using the global vector autoregressive (GVAR) model, this paper explores regional market integration, the feedback between market shocks and price dynamics, and the link between EU's cheese export markets and energy market. This paper assesses and compares which influencing factors are typically associated with intra-EU and extra-EU cheese export price movement with regards to shocks to crude oil price, farm-gate raw milk price, and consumer price index (CPI) for food and cheese production of six representative EU member states, respectively. Using generalized impulse response functions, this paper finds that EU's internal cheese export market is not well integrated, while EU's external market is well integrated, with France as an exception. It also finds that the external cheese export market is vulnerable to shocks from the energy market compared to the internal market. Raw milk prices from the upstream supply chain have strong spill-over effects on EU's internal cheese export market, yet their impact on extra-EU cheese export prices is relatively less significant. The movement patterns of extra-EU cheese export prices of Ireland and the UK show similar patterns in the long run. It is concluded that the dynamics of cheese export prices in the internal and external markets of the EU are different under market shocks.
| S-EPMC8909711 | biostudies-literature
Project description:BackgroundPharmaceutical spending has been increasing rapidly for years and is higher than ever before. To control the rising costs, countries are implementing regulatory frameworks such as (internal) reference pricing, price cuts or generics substitution. Internal reference pricing establishes a reference price within a country which serves as the maximum level of reimbursement for a group of pharmaceuticals. Price setting in the German market is especially relevant for many European countries, which use Germany as a reference country for their own price setting.MethodsWe evaluate pharmaceutical price dynamics for not reference priced pharmaceuticals (NRPs) as well as for reference priced pharmaceuticals (RPs) in Germany-referring to the internal reference price system. 64,862 medication packs have been extracted from the German pharmaceutical pricing register Lauer-Taxe. For each pack, we extracted detailed data on the company, manufacturer rebates, pharmacy retail prices, reference prices, co-payments, import quotas, and discount agreements. We then investigated price setting and dynamics of NRPs vs. RPs for all 14 indication areas by ATC code level 1.ResultsThe average manufacturer price per pack was 604.84€ for NRPs and 112.11€ for RPs. Similar differences were found for the wholesale price and the pharmacy retail price. The reference price was-as expected-0.00€ for NRPs, and 154.40€ for RPs. NRP packs were imported in 42.38%, while RP packs were imported only in 24.62%. Highest average pharmacy retail prices could be found in the therapeutic areas 'antineoplastic and immunomodulating agents' (1711.47€), 'systemic hormonal preparations' (1331.95€), and 'blood and blood forming organs' (1260.58€). We detected high fluctuations in pharmacy retail prices per indication, as well as for reference prices per indication. The indications with the highest number of reference price regulated medical packs are 'cardiovascular system', 'musculo-skeletal system', and 'nervous system'. Highest co-payments were found in the indications 'antineoplastic and immunomodulating agents', 'blood and blood forming organs', and 'antiinfectives for systemic use'.ConclusionPrice setting and price dynamics vary substantially between NRP and RP medication packs. Further, we saw major differences across all indication areas as well as when comparing medication packs launched by top 20 pharma companies vs. the rest.
| S-EPMC9422096 | biostudies-literature
Project description:This study analyzes the explanatory power of the latent factor conditional asset pricing model for the Korean stock market using an autoencoder. The autoencoder is a type of neural network in machine learning that can extract latent factors. Specifically, we apply the conditional autoencoder (CA) model that estimates factor exposure as a flexible nonlinear function of covariates. Our main findings are as follows. The CA model showed excellent explanatory power not only in the entire sample but also in several subsamples in the Korean market. Also, because of this explanatory power, it can better explain market anomalies compared to the traditional asset pricing models. As a result of examining investment strategies using pricing error, the CA model measures the expected return of stocks better than the traditional asset pricing model. In addition, the CA model indicates that the firm characteristic variables are important in asset pricing conditional on macro-financial states, such as the global financial crisis and the coronavirus disease 2019 pandemic. The result shows that the major variables considered in the explanation of stock returns through the CA model may vary depending on the time. This is expected to provide a broader perspective on asset pricing through the CA model in the future.
| S-EPMC10389732 | biostudies-literature