Market Share Data Research Articles

EE280 Budget Impact (BI) of First-Line (1L) Cemiplimab Monotherapy for Advanced Non-Small Cell Lung Cancer (aNSCLC) with Programmed Cell Death-Ligand 1 (PD-L1) ≥50% in a Large US Health Plan: An Updated Analysis

Cemiplimab monotherapy significantly improved overall survival versus chemotherapy in 1L aNSCLC with PD-L1≥50%. Here, we estimate the BI of introducing cemiplimab monotherapy in the US from the healthcare payer’s perspective using updated market share data indicating higher usage of immunotherapy (IO)+chemotherapy and a lower share of IO monotherapy compared to prior analyses in the high PD-L1 population.

English

The production of dates has been increasing in Saudi Arabia during 1970-2019. However, this growth has not been accompanied by a proportionate increase in exports to global markets, with only 5.5% on average of the produced dates being destined for export in the same period (1970-2019). This study compares the competitiveness of Saudi date exports to several overseas markets and its effect on future exports. Our study hypothesizes that Saudi Arabia has the competitiveness of Saudi dates exports comparing others and this competitiveness could have a significant effect on Saudi’s dates exports. We test such a hypothesis by using the market share data and the RCA for countries that were the top exporters of dates in 2019.The Partial Adjustment Model is employed to explore the impact of the competitiveness of Saudi dates on future exports. The results showed that Saudi Arabia as well as other major date-exporting countries (Iran, Iraq, Israel, Pakistan, Tunisia, and the UAE) have high competitiveness in the global market. By division of markets by groups of countries, Saudi Arabia has a comparative advantage over at least four countries among the top six exporters in three markets (Africa, Asia, and the OIC), while Saudi dates are less competitive in the American and European markets, where it never held a dominant position. The general trend equation indicates that the decline in the competitiveness of Saudi dates will continue during 2021-2025

Budget Impact Analysis of a New-Generation Recombinant Factor VIII from a Human Cell Line (Nuwiq) for the Treatment of Patients with Hemophilia A in Canada

Introduction: Management of patients with hemophilia A is associated with significant economic burden, particularly in high-income developed countries such as Canada, where prophylaxis with replacement FVIII therapies is administered routinely. As standard prophylaxis regimens may lead to over/under treatment in certain individuals, personalized dosing regimens may be more effective for reducing costs.Aim: This analysis assesses the budgetary impact of a new-generation recombinant FVIII from a human cell line (Nuwiq, simoctocog alfa) for the treatment of patients with hemophilia A in Canada.Methods: To understand the potential financial impact of introducing simoctocog alfa into the drug reimbursement system of Canada, a budget impact analysis was performed in accordance with the guidelines of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR). A budget impact model was developed from the perspective of the Canadian Health Services considering a five-year time horizon (2017-2021). The model incorporates epidemiological, clinical, market share, cost and resource use data derived from Canadian-specific sources available at the time of model development. In addition to Nuwiq, the FVIII replacement treatments considered in the analysis are antihemophilic factors (recombinant) (Advate, Kovaltry and Eloctate) or antihemophilic factor (Xyntha). Scenario analyses (standard or personalized prophylaxis vs. on-demand) various severity and age groups) were conducted to explore the impact of changing the analysis assumptions. All costs were inflated to 2017 Canadian dollars (CAD).Results : Based on projected market shares over the 5-year time horizon, the introduction of simoctocog alfa to the Canadian market was associated with cost savings for the healthcare system over this time horizon. The cumulative budget impact of gradually replacing existing therapies by Nuwiq® in untreated and previously treated patients with severe hemophilia A over five years was estimated to be -$27,436,162 CAD (cost-saving) (Table 1). The majority of the cost savings (89%, $24,475,207 CAD) are attributed to the use of personalized prophylaxis in patients with severe hemophilia A. When patients with mild and moderate disease were added to the analysis, estimated total savings over 5 years increase further to $31,740,254 CAD. Cost reductions were mainly driven by decreases in the costs of treatment of inhibitor development and bleeding episodes.Conclusion: Nuwiq® for the treatment of patients with hemophilia A, could be associated with cost savings to the Canadian healthcare system over a time horizon of five years. [Display omitted] DisclosuresAdapa:Octapharma: Employment. Ovcinnikova:Octapharma: Consultancy, Research Funding; Mapi: Employment. Leighton:nspm ltd: Employment; Octapharma: Consultancy, Research Funding. de Silva:Mapi: Employment; Octapharma: Consultancy, Research Funding. Bending:Mapi: Employment; Octapharma: Consultancy, Research Funding. Belyanskaya:Octapharma AG: Employment. Lidia:Octapharma Canada Inc: Employment. Myerson:Octapharma Canada Inc: Employment.

Linking Fortification Compliance Metrics With Decision Making Needs: From Brand Level Data to Market Share Weighted Information

Abstract Objectives A fortification program can only be effective if (1) each brand producer complies with fortification standards (i.e., adequately fortified), and (2) the adequately fortified products are consumed by a large proportion of the population. We quantified fortification quality (extent to which levels of fortification align with food standards) of oil, salt and wheat flour products; and ascertained the degree of food brand penetration and market share in Tanzanian markets. Methods Food inspectors collected multiple samples of food products at the production and/or market and laboratory analysts quantified the micronutrient content. We compared the average content for each individual brand product to the national fortification standards considering lab measurement uncertainty and classified into one of 4 fortification status categories (not fortified, fortified below, according to, or above the fortification standard). To establish penetration and market share, we visited 1500 retail outlets across regions in Tanzania to ascertain brand product availability and sales volumes. We applied weights using the market share estimates to extrapolate the fortification quality of the food market volume in the country. Results Of the different brand products of salt (26), wheat flour (25), and oil (68) found in the market, samples were collected and micronutrient content analyzed in the main oil (30%), salt (62%), and wheat flour brand products (85%). While 12% of salt, 35% of wheat flour, and 22% of oil brand products were fortified above the fortification standard minimum, when weighted by their market share, these represent 90% of the salt, 86% of wheat flour, and only 2% of the oil market volume respectively. Conclusions Fortification compliance of brand products provides important data for industry and regulatory authorities to identify where corrective action is necessary. Health and development staff are concerned about the extent to which additional nutrients are delivered to the population to anticipate public health impact, for which adjustment using reliable market share data is key. Weighted brand data can help resource constrained regulatory staff prioritize monitoring and enforcement activities to industries/producers with greatest influence. Funding Sources Bill and Melinda Gates Foundation (BMGF).

Compound Grey-Logistic Model and Its Application

Logistic regression model is widely used in ecology and in the analysis of social economic systems, because of its good adaptability. In order to improve the measurement accuracy of logistic model, this paper proposes a new method. A compound grey-logistic model is developed to carry out the grey transformation of the original data. Practice shows that the grey transformation data has better simulation accuracy; at the same time, grey transformation can reduce the observation noise of the original data. Mean absolute percentage error index has been used to evaluate the accuracy of prediction model, and information entropy can be used to evaluate the change of information entropy of forecasting data. In this paper, three cases are used to verify the applicability of grey-logistic model. From the perspective of the type of original data, the three cases represent three different data conditions: sufficient data, insufficient data, and fragmentary data. The cases represent different related fields: market share data, economic growth data, and R&D output data. The results show that the proposed grey-logistic method can effectively carry out the population growth analysis.

Multiway Cluster Robust Double/Debiased Machine Learning

This article investigates double/debiased machine learning (DML) under multiway clustered sampling environments. We propose a novel multiway cross-fitting algorithm and a multiway DML estimator based on this algorithm. We also develop a multiway cluster robust standard error formula. Simulations indicate that the proposed procedure has favorable finite sample performance. Applying the proposed method to market share data for demand analysis, we obtain larger two-way cluster robust standard errors for the price coefficient than nonrobust ones in the demand model.

Do Customer Satisfaction Scores Link to Business Revenue Over Time?

This study examines whether changes in customer satisfaction scores, derived from the American Customer Satisfaction Index (www.acsi.org), are associated with changes in business revenue. The study analyses firms or brands in nine industries. For most of those industries, the study uses data for the period 2005-2019; for cars the data covers 2002-2016. The analysis is simple and transparent: I create year-on-year differences in firm satisfaction, and year-on-year differences in firm revenue, and calculate the correlation between the two. In the case of cars, revenue by brand is not available, therefore I use US market share data sourced from Knoema.com.

Ill-posed estimation in high-dimensional models with instrumental variables

This paper is concerned with inference about low-dimensional components of a high-dimensional parameter vector β0 which is identified through instrumental variables. We allow for eigenvalues of the expected outer product of included and excluded covariates, denoted by M, to shrink to zero as the sample size increases. We propose a novel estimator based on desparsification of an instrumental variable Lasso estimator, which is a regularized version of 2SLS with an additional correction term. This estimator converges to β0 at a rate depending on the mapping properties of M. Linear combinations of our estimator of β0 are shown to be asymptotically normally distributed. Based on consistent covariance estimation, our method allows for constructing confidence intervals and statistical tests for single or low-dimensional components of β0. In Monte-Carlo simulations we analyze the finite sample behavior of our estimator. We apply our method to estimate a logit model of demand for automobiles using real market share data.

Characterizing Ingredients in Baked Products Sold in the U.S.

Abstract Objectives To develop a dataset of top ingredients used in baked products and to examine the scope of use of emulsifiers, leavening agents and sweeteners (nutritive and non-nutritive) in baked products. Methods We identified top-selling baked products using 2016 Information Resources Inc. market share data, and obtained ingredient lists for the top-selling products from the publicly available USDA Global Branded Food Products Database and manufacturer's websites. Individual ingredients were then parsed using a custom program in R, a statistical computing language. We performed several pre-processing steps before parsing, as ingredient lists were inconsistent and varied. For example, the additive Azodicarbonamide is listed in 9 different ways including spelling errors. We then reviewed the parsed ingredients reported more than once, to identify terms which were equivalent, such as synonyms, spelling and usage variants, common names, possible errors etc., and assigned a preferred descriptor and its technical use (eg. emulsifiers, leavening agents, sweeteners etc.). Results For the 4 baked product food categories, there are over 40,000 products available, of which ingredient lists were obtained for ∼79% of the total volume sold. These baked products use ∼6000 uniquely described ingredients (as listed on the labels). Preliminary results from grouping based on technical use shows, for example, ∼60 kinds of sweeteners were used; top nutritive sweeteners: sucrose, dextrose, high fructose corn syrup; top non-nutritive sweeteners: sucralose, stevia extract, Reb-A. Conclusions The ingredient dataset for baked products provides insight into ingredients used in commercially packaged baked products. This information can also be used to prioritize ingredients for which food composition data are needed and help in the development of computer programs and Artificial Intelligence tools. Funding Sources None.

Benchmarking the transparency, comprehensiveness and specificity of population nutrition commitments of major food companies in Malaysia

BackgroundThe aim of this study was to assess the commitments of food companies in Malaysia to improving population nutrition using the Business Impact Assessment on population nutrition and obesity (BIA-Obesity) tool and process, and proposing recommendations for industry action in line with government priorities and international norms.MethodsBIA-Obesity good practice indicators for food industry commitments across a range of domains (n = 6) were adapted to the Malaysian context. Euromonitor market share data was used to identify major food and non-alcoholic beverage manufacturers (n = 22), quick service restaurants (5), and retailers (6) for inclusion in the assessment. Evidence of commitments, including from national and international entities, were compiled from publicly available information for each company published between 2014 and 2017. Companies were invited to review their gathered evidence and provide further information wherever available. A qualified Expert Panel (≥5 members for each domain) assessed commitments and disclosures collected against the BIA-Obesity scoring criteria. Weighted scores across domains were added and the derived percentage was used to rank companies. A Review Panel, comprising of the Expert Panel and additional government officials (n = 13), then formulated recommendations.ResultsOf the 33 selected companies, 6 participating companies agreed to provide more information. The median overall BIA-Obesity score was 11% across food industry sectors with only 8/33 companies achieving a score of > 25%. Participating (p < 0.001) and global (p = 0.036) companies achieved significantly higher scores than non-participating, and national or regional companies, respectively. Corporate strategy related to population nutrition (median score of 28%) was the highest scoring domain, while product formulation, accessibility, and promotion domains scored the lowest (median scores < 10%). Recommendations included the establishment of clear targets for product formulation, and strong commitments to reduce the exposure of children to promotion of unhealthy foods.ConclusionsThis is the first BIA-Obesity study to benchmark the population nutrition commitments of major food companies in Asia. Commitments of companies were generally vague and non-specific. In the absence of strong government regulation, an accountability framework, such as provided by the BIA-Obesity, is essential to monitor and benchmark company action to improve population nutrition.

Estimating Demand With Unobserved No-Purchases on Revenue-Managed Data

Discrete-choice models such as the multinomial-logit (MNL) model are increasingly being used to model customer purchase behaviour in hotels, airlines, fashion retail and e-commerce. Their estimation however has proved difficult in practice. One reason for this difficulty is well-known: most firms in retail do not, or unable to, record customers who were interested in purchasing but did not buy the product (``no-purchasers). Estimating demand even with the simplest discrete-choice model such as the MNL becomes challenging then as we do not know the fraction that have chosen an outside option (not purchased). Indeed, the parameters of the MNL model may not be identifiable with such data. Some previous approaches have proposed using ``market-share to pin down the parameter associated with the outside option. However, in many industries, market-share data is difficult to obtain, and for some, such as fashion products, has little meaning. In this paper we point out an additional difficulty that arises in practice: Many firms constantly monitor sales and optimize their prices and assortments based on partially observed demand. This leads to an optimization-induced endogeneity as the input used for estimation has been processed by optimization that takes both past data as well as future demand trends in setting controls. As we demonstrate, methods that work well on randomly generated assortments may do badly on optimized assortment data. In this paper we propose a robust method when the firm cannot observe no-purchases, has no market-share information, and the optimization-induced endogeneity exists in the data. The method is a two-step GMM (Generalized Method of Moments) procedure for which we show the estimates are consistent, and we give intuition for its robustness. In Monte-Carlo simulations the performance of our method matches existing methods on randomly generated controls, and is superior in accuracy and robustness when optimization-induced endogeneity is present. On a large real-world data set from the fashion industry --- subject to markdowns as well as stock-outs and unknown management controls --- our method provides very reasonable and robust estimates compared to existing methods.

PUK10 BUDGET IMPACT ANALYSIS OF DEGARELIX FOR THE TREATMENT OF PROSTATE CANCER IN CHINA

Prostate cancer (PCa) is one of the most common cancer and one of the leading causes of mortality among males worldwide. This study was to estimate the budget impact of degarelix for the treatment of prostate cancer from Chinese healthcare payer’s perspective. A budget impact model was established to estimate the potential economic impact of adding degarelix to Chinese national reimbursement drug list (NRDL) over a 5-year time horizon (2019-2023). Two scenarios were developed: scenario 1 when degarelix not getting reimbursed by NRDL; scenario 2 when degarelix getting reimbursed by NRDL. The eligible patient population was estimated from China epidemiology statistics. Market share projections were based on market research data. Cost data, including cost of drug, administration and adverse events, were obtained from online sources and KOL survey. The intention-to-treat (ITT) population and a PSA level >20 ng/mL sub-group were analyzed in the model. The incremental aggregate budget impact per year was calculated. Assuming degarelix would be included by NRDL in 2020, the drug cost was estimated to increase by approximately 130 to 650 million RMB from 2020 to 2023 for ITT population. Given that using degarelix would decrease the likelihood of adverse events based on clinical trials, the cost of adverse events would be reduced accordingly; the overall impact would be decreased to 90 ∼ 560 million. For PSA level >20 ng/mL sub-group, the drug cost was estimated to increase by nearly 59 million, 100 million, 190 million, and 300 million RMB in 2020-2023. The overall economic impact would be 42 million, 86 million, 170 million, and 260 million RMB after saving the cost of adverse events. Based on projected market share data, degarelix is likely to have a minimal economic impact on Chinese healthcare system after getting reimbursed by NRDL.

Blood glucose meters and test strips: Global market and challenges to access in low-resource settings

Summary Blood glucose meters and test strips for self-monitoring of blood glucose (SMBG) are often inaccessible to, and infrequently used by, people with diabetes in countries with limited resources for health care. Supplies for measuring blood glucose can also be scarce in health facilities, despite being needed in a myriad of clinical settings at all levels of the health system. Numerous studies and international guidelines emphasise the value of SMBG in diabetes care, particularly in people with type 1 diabetes. In this Review, we assess global access to blood glucose meters and test strips, collating published information on cost, availability, system accuracy, competitive bidding, technological trends, and non-financial barriers. We also provide new information on global market share data and prices, taxes and tariffs, and product availability. Blood glucose meters and test strips should be viewed similarly to essential medicines, with issues of access prioritised by relevant international agencies. Efforts are needed to reduce tariffs and taxes and to create unified global system accuracy requirements and accountable post-marketing evaluations. Preferential pricing arrangements, pooled procurement, and best-purchasing practices could help to lower direct costs. SMBG supplies should also be included in national health insurance schemes. Enhanced diabetes education of health professionals and patients is crucial to ensure effective use of SMBG. Finally, as technology advances for people who can afford new interstitial fluid glucose monitoring systems, blood glucose meters and test strips must remain available and become more affordable in low-resource settings.

Real-World Data Approaches for Early Detection of Potential Safety and Effectiveness Signals for Generic Substitution: A Metoprolol Extended-Release Case Study.

Real-world spontaneous adverse event reports and administrative health care data were utilized as one part of a multipronged approach to verify surveillance signals related to generic drug formulations. This study used metoprolol succinate extended release as a historic case example from which to develop an analytic framework. The US Food and Drug Administration Adverse Event Reporting System was utilized for disproportionality analyses and to identify outcomes of interest. Claims data were analyzed for generic uptake, proportion of prescriptions with "dispense as written" orders, time to discontinuation or switching, and relative rates of clinical events. Adverse Event Reporting System data showed that the Medical Dictionary for Regulatory Activities terms for product quality were higher for generic metoprolol cases and that a number of clinical events were increased that could be side effects of high or low variability in drug levels. Compared to amlodipine-benazepril, which also had a first-approved generic at the same time, market share data showed that metoprolol succinate had lower utilization and more prescriptions written as dispense as written. Switching and discontinuation were generally higher for metoprolol users compared to amlodipine-benazepril users. Finally, clinical event rates were generally higher for generic versus brand metoprolol but lower for the same comparison for amlodipine-benazepril users. In the claims-based analyses, the 90-day period immediately after generic entry provided stronger signal capture than using the entire study period. This analytic framework can be implemented to actively monitor new generic formulations for potential bioequivalence failures. Signals from these analyses require confirmation (eg, via pharmacometric analyses) to be informative for regulatory action.

Estimating Demand for Differentiated Products with Zeroes in Market Share Data

In this paper we introduce a new approach to estimating differentiated product demand systems that allows for products with zero sales in the data. Zeroes in demand are a common problem in product differentiated markets, but fall outside the scope of existing demand estimation techniques. Our solution to the zeroes problem is based on constructing bounds for the conditional expectation of the inverse demand. These bounds can be translated into moment inequalities that are shown to yield consistent and asymptotically normal point estimator for demand parameters under natural conditions for differentiated product markets. In Monte Carlo simulations, we demonstrate that the new approach works well even when the fraction of zeroes is as high as 95%. We apply our estimator to supermarket scanner data and find that correcting the bias caused by zeroes has important empirical implications, e.g., price elasticities become on the order of twice as large when zeroes are properly controlled.

The Impact of Chronic Myeloid Leukemia Therapy Management on the Oncology Care Model

Introduction: In an Oncology Care Model (OCM) setting, practices may earn a Performance-Based Payment (PBP) for a reduction in the costs of treating participating Medicare patients during a 6-month episode of care. An Excel-based decision analytics model was developed to evaluate the cost-savings associated with implementing changes in the usage of tyrosine kinase inhibitors (TKIs) among patients with chronic myeloid leukemia (CML) within a typical OCM practice and the impact it could have on a practice potentially receiving a PBP.Methods: The default scenario is based on an OCM practice that treats 1,000 cancer patients during a 6-month episode of care. The types of cancers treated and the proportions of patients treated in the OCM practice were estimated from an OCM baseline report; all-cause healthcare costs for each cancer type were obtained from published literature. CML patients were stratified into newly-diagnosed and established TKI-treated patients. The percentages of CML patients on each of the TKIs (branded and generic imatinib [1st-gen TKIs], as well as dasatinib and nilotinib [2nd-gen TKIs]) within each stratum were estimated using market share data from April 2018. The 2018 Wholesales Acquisition Costs for the TKIs were obtained from RedBook. It was assumed that, if a practice implements the policy of restricting utilization of branded TKIs as a cost-cutting measure, 80% of the current market share of branded imatinib would shift to the generic and 50% of the current market shares of 2nd-gen TKIs would shift to generic imatinib. Among established TKI-treated patients, it was assumed that 80% of the current market share of branded imatinib would shift to the generic, whereas no patients treated with 2nd-gen TKIs would be switched to generic imatinib due to the lack of supporting evidence, physician and patient apprehension, some patients already having used imatinib, among other reasons. The relationship between the savings achieved from restricting utilization of 2nd-gen TKIs and the savings required for the OCM practice to receive a PBP using either a one-sided or two-sided risk model was evaluated.Results: The total healthcare costs of an OCM practice that treats 1,000 cancer patients for 6 months were estimated at $51,345,812. It was estimated that there would only be 4 CML patients in a 1,000-patient OCM practice, 1 newly-diagnosed and 3 established TKI-treated patients. Implementing the policy of restricting utilization of 2nd-gen TKIs for patients with CML would save a practice $12,970 during the 6-month episode of care, while $25,250 would be saved through a branded to generic imatinib shift (Table). For a 1,000-patient OCM practice participating in a one-sided risk model, a total cost-savings of $3,013,832 is required for it to be eligible for a PBP. In this scenario, the cost reduction associated with a shift from 2nd-gen TKIs to generic imatinib amounts to only 0.4% of the required total cost-savings threshold before the practice is eligible for a PBP. For a 1,000-patient OCM practice participating in a two-sided risk model, a total cost-savings of $2,372,010 is required for it to be eligible for a PBP. In this case, the cost reduction associated with a shift from 2nd-gen TKIs to generic imatinib amounts to only 0.5% of the required total cost-savings threshold before the practice is eligible for a PBP.Conclusions: This economic model indicates that the cost-savings associated with restricting branded TKI utilization among CML patients in an OCM setting will represent only a very small portion of the cost-savings required before an OCM practice is eligible for a PBP. Of the reduction in TKI costs, approximately two-thirds was attributed to the shift from branded to generic imatinib. Restricting utilization of the 2nd-gen TKIs contributed a negligible amount of savings required for a PBP. The cost-savings opportunities in CML in the OCM setting are limited by how few CML patients would be affected by restrictions. [Display omitted] DisclosuresJabbour:Pfizer: Consultancy, Research Funding; Novartis: Research Funding; Takeda: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Abbvie: Research Funding. Mendiola:Bristol-Myers Squibb: Employment. Lingohr-Smith:Novosys Health: Employment. Menges:Novosys Health: Employment. Lin:Bristol-Myers Squibb: Consultancy; Novosys Health: Employment. Makenbaeva:Bristol-Myers Squibb: Employment.

Realized and Projected Cost Savings from the Introduction of Generic Imatinib, with Minimal Additional Savings to Payers through Formulary Management

INTRODUCTIONThe availability of imatinib, the first generation tyrosine kinase inhibitor (TKI), has dramatically improved survival of patients with Chronic Myelogenous Leukemia (CML). Second generation TKIs have further advanced patient care. Since loss of exclusivity (LOE) and the entry of a generic imatinib in the US in February 2016, US payers have started realizing savings. However, generic prices have taken two years to decline substantially. Previous work had estimated the anticipated impact of the generic imatinib entry for its first two years, and now the actual prices and savings can be calculated. The objective of this research was to quantify the savings from generic substitution of branded imatinib relative to the potential impact of requiring step therapy through generic imatinib before a 2nd generation TKI. METHODSAn Excel-based model representing the TKI pharmacy budget of a hypothetical 1-million member commercial plan and 1-million member Medicare plan was developed from a pharmacy only perspective. Historical market share and wholesale acquisition cost pricing over the period of January 2016 to February 2018 were combined with CML age-adjusted US epidemiology data to calculate the monthly spend on TKIs over the same period. Logarithmic regression models were fitted to historical market share data in order to project future utilization of branded TKIs and generic imatinib up to 5 years after LOE. Future drug pricing was assumed to remain constant over the forecasted period. It was assumed that a health plan would not mandate changes in choice of TKI among patients with ongoing TKI treatment. Savings were calculated by comparing the costs of TKIs with generic imatinib to a scenario where generic imatinib was not available. The potential impact of implementing formulary restriction in the TKI class in the next 3 years was explored by applying a step edit to require a trial of generic imatinib before 2nd generation TKIs for incident patients with CML who are new to TKI therapy. Analyses were repeated for the entire commercially and Medicare-covered population in the US based on National Census data RESULTSIt was estimated that a 1-million member commercial plan saved $0.5M (3%) in the first year and $3.8M (19%) in the second year after LOE. Projected savings significantly increase to $7.8M (37%), $8.2M (39%), and $8.6M (40%) in the 3rd, 4th, and 5th year after LOE, respectively. Initiating a step edit for newly treated CML patients in the commercial plan setting was associated with a very small incremental savings of 1.5% annually over the next 3 years.It was estimated that a 1-million member Medicare plan saved $1.7M (3%) and $14M (19%) in the first and second year, respectively. Projected savings in a Medicare plan were $27.8M (37%), $29.4M (39%), and $30.7M (40%), and a step edit for newly treated CML patients gained an additional 1.2% per year in savings over the next 3 years in a Medicare health plan population.In the first two years, the introduction of generic imatinib saved US payers $1.5B, 7% of the total spend on this drug class. In the next 3 years, the estimated savings are expected to grow to 22% and result in cumulative savings of $8.3B with no management of the class at all. Nearly all of potential savings from the class, 93%, are estimated to come from the generic imatinib conversion from brand with no management required. CONCLUSIONSLow generic imatinib price is estimated to result in substantial cost savings to US payers over the next 3 years independent of any formulary management strategies. Formulary management restricting access to 2nd generation TKIs may result in minimal additional savings that are unlikely to reach a threshold of value worthy of action by the health plan. [Display omitted] DisclosuresBloudek:Xcenda: Employment. Brokars:Bristol-Myers Squibb: Employment. David:Xcenda: Employment. Makenbaeva:Bristol-Myers Squibb: Employment.

Estimating switching costs with market share data: an application to Medicare Part D

Choice inertia and switching frictions are well-documented features of the demand for health insurance. In this paper, we estimate switching costs in the Medicare Part D market with aggregate market share data using standard discrete choice models for differentiated products. We consider various modelling assumptions: myopic and forward-looking consumers, and with and without random coefficients. Both myopic and forward-looking consumer models with no random coefficients yield switching cost estimates that closely match the actual average switching frequency, with implied dollar-valued switching costs of $1600 to $2000. We find the inclusion of random coefficients to the myopic consumer model results in smaller estimates of switching costs, but only at the expense of the model’s fit to the switching frequency. The estimated welfare losses from switching frictions are large, but they are smaller under the forward-looking consumer model, amounting to around $500 per enrollee annually, compared to over $1000 under the myopic model.

Limiting trans Fats in Foods: Use of Partially Hydrogenated Vegetable Oils in Prepacked Foods in Slovenia

Consumption of industrially produced trans-fatty acids (TFAs) is a well-established health risk factor that correlates with the increased risk of developing cardiovascular disease. The recommended TFA intake is as low as possible, within the context of a nutritionally adequate diet. Different countries have introduced different measures to minimize the exposure of their population to TFAs. Previous data have shown that TFA content has significantly decreased in Western European countries, while this was not the case in many Central-Eastern European countries, including Slovenia. In the absence of regulatory requirements, a number of awareness campaigns were launched in Slovenia since 2015, with the common goal of lowering the use of partially hydrogenated oils (PHO), which are considered a major source of TFAs. To determine if this goal had been reached, we performed an assessment of the exposure of the population to prepacked foods containing PHOs in years 2015 and 2017. Altogether, data on the composition of 22,629 prepacked foods was collected from food labels, using a specifically developed smartphone application. Furthermore, the food categories with the most frequent use of PHOs were identified. The proportion of PHO-containing products was determined for each specific food category, and adjusted with the market share data. The results showed that in 2015, vegetable cream substitutes, soups, and biscuits were the categories with the highest penetration of declared PHO content. In 2017, the proportion of products with PHO decreased considerably. In vegetable cream substitutes the percentage of PHO containing items dropped from 30 down to 4%, in soups it decreased from 21 to 5%, in biscuits from 17 to 8%, and in crisps and snacks from 10 to 4%. However, PHO content remained notable among cakes, muffins, pastries, and biscuits. We can conclude that the voluntary guidelines and regular public communication of the risks related to the TFA consumption has had a considerable effect on the food supply, but did not result in sufficient removal of PHOs from foods.

Multi-scale Economic Dynamics: The Micro–Macro Wealth Dynamics and the Two-Level Imbalances of the Euro Crisis

We introduce a system of ordinary differential equations to model the micro–macro wealth dynamics of interactions between international enterprise competitiveness and the macroeconomic growth as an open system. The novelty of the approach is to postulate dynamic interaction between domestic and foreign companies and link this interaction to the GDP growth. The objective is to construct a micro–macro wealth dynamic model. By analyzing the market share data of the retail industry of 13 largest Eurozone countries as a system, our model suggests that the predator–prey relation exists. Under certain regimes, it is shown that foreign companies have a negative contribution to the GDP growth. Such dynamics reveals two levels of imbalances: company competitiveness and national economic growth.