Static and Dynamic Efficiency of Irreversible Health Care Investments under Alternative Payment Rules

The paper studies the incentive for providers to invest in new health care technologies under alternative payment systems, when the patients' benefits are uncertain. If the reimbursement by the purchaser includes both a variable (per patient) and a lump-sum component, efficiency can be ensured both in the timing of adoption (dynamic) and the intensity of use of the technology (static). If the second instrument is unavailable, a trade-off may emerge between static and dynamic efficiency. In this context, we also discuss how the regulator could use the control of the level of uncertainty faced by the provider as an instrument to mitigate the trade-off between static and dynamic efficiency. Finally, the model is calibrated to study a specific technology.Health Care, Investments

Dynamic, economic approaches to HTA under uncertainty

A simple, two period framework is used to interpret existing contributions to the literature on decision rules for HTA under uncertainty and to contrast them with a dynamic, economic model solved using backward induction.economic evaluation, dynamic programming

R&D and market size: who benefits from orphan drug regulation?

Since the early 80s, orphan drug regulations have been introduced to stimulate R&D for rare diseases. We develop a theoretical model to study the heterogeneous impact on optimal R&D decisions of the incentives for diseases with different levels of prevalence. We show the mechanisms through which the type of incentives deployed by orphan drug regulations may stimulate R&D more for orphan diseases with comparatively high prevalence, thus increasing inequality within the class of orphan diseases. Using data from the Food and Drug Administration on the number of orphan designations, our empirical analysis shows that, while R&D has increased over time for all orphan diseases, the increase has been much greater for the less rare. According to our baseline specification, the difference between the predicted number of orphan designations for a disease belonging to the highest and the lowest class of prevalence is 5.6 times larger after 2008 than it was in 1983. Our findings support the idea that the type of incentives in place may be responsible for this increase in inequality within orphan diseases

R&D and market size: who benefits from orphan drug legislation?

Since the early 80s, incentives have been introduced to stimulate R&D for rare diseases. We develop a theoretical model to study the impact of push and pull incentives on the intensive and extensive margin of optimal R&D investments. The model describes the mechanisms by which the type of incentives provided may favor R&D for orphan diseases with comparatively high prevalence. In our empirical analysis, we merge data on orphan drug designations by the Food and Drug Administration with Orphanet data on disease characteristics. In line with the theoretical results, we find evidence supporting the idea that the incentives adopted may have contributed substantially to widening the gap between more and less rare diseases classified as orphan. Our theoretical and empirical findings together suggest that, if providing some therapeutic option to patients with very rare diseases is a priority, a revision of the current system of incentives should be considered

Spillovers of Pharmaceutical Price Regulations: evidence from the AMNOG Reform in Germany

In years of growing pharmaceutical spending, the adoption of new health technologies faces several regulatory hurdles. Such policies are typically studied at the country level, even though there are explicit and implicit channels that link decisions made in different countries. This can be relevant in the EU, where external reference pricing is widely adopted. This work exploits the IMS pricing database of cancer drugs approved by the European Medicine Agency between 2007 and 2017 to assess the impact of a pharmaceutical pricing regulation change that occurred in Germany in 2011 (the AMNOG bill) on foreign pharmaceutical prices. We show that the impact on foreign prices depends on whether the foreign country adopts external reference pricing policies and whether it includes Germany in its basket of reference countries and, symmetrically, if it enters Germany’s reference set. In particular, our diff-in-diff approach shows that AMNOG led to a price reduction for products launched in countries that refer to Germany (indirect spillover effect), whereas products launched in countries referenced by Germany experienced a 5.48% price increase (strategic spillover effect)

R&D and market size: who benefits from orphan drug legislation?

Since the early 80s, incentives have been introduced to stimulate R&D for rare diseases. We develop a theoretical model to study the impact of push and pull incentives on the intensive and extensive margin of optimal R&D investments. The model describes the mechanisms by which the type of incentives provided may favor R&D for orphan diseases with comparatively high prevalence. In our empirical analysis, we merge data on orphan drug designations by the Food and Drug Administration with Orphanet data on disease characteristics. In line with the theoretical results, we find evidence supporting the idea that the incentives adopted may have contributed substantially to widening the gap between more and less rare diseases classified as orphan. Our theoretical and empirical findings together suggest that, if providing some therapeutic option to patients with very rare diseases is a priority, a revision of the current system of incentives should be considered

Free-Riding in Pharmaceutical Price Regulation: Theory and Evidence

We present a model of the strategic interaction among authorities regulating pharmaceutical prices in different countries and the R&D investment decisions of pharmaceutical firms. Regulators’ decisions affect consumer surplus directly, via prices, and indirectly via firms’ profits and R&D investment policies, which in turn affect patient health. The positive externality of a price increase in one country provides an incentive for other countries to free-ride, and we show how country-level characteristics affect optimal pricing decisions and equilibria. Our theoretical predictions are tested using price data for a set of 70 cancer drugs in 25 OECD countries. We find evidence of behaviour that is consistent with the free-riding hypothesis and which, in line with the theoretical predictions, differs according to country-level characteristics. Countries with comparatively large market shares tend to react to increases in other countries’ prices by lowering their own prices; in countries with comparatively small market shares, regulators’ decisions are consistent with the objective of introducing the product at as low a price as possible. We discuss the policy implications of our results for incentivising global pharmaceutical R&D and the recent proposal to move towards a joint pharmaceutical procurement process at the European level

R&D and market size: who benefits from orphan drug regulation?

Since the early 80s, orphan drug regulations have been introduced to stimulate R&D for rare diseases. We develop a theoretical model to study the heterogeneous impact on optimal R&D decisions of the incentives for diseases with different levels of prevalence. We show the mechanisms through which the type of incentives deployed by orphan drug regulations may stimulate R&D more for orphan diseases with comparatively high prevalence, thus increasing inequality within the class of orphan diseases. Using data from the Food and Drug Administration on the number of orphan designations, our empirical analysis shows that, while R&D has increased over time for all orphan diseases, the increase has been much greater for the less rare. According to our baseline specification, the difference between the predicted number of orphan designations for a disease belonging to the highest and the lowest class of prevalence is 5.6 times larger after 2008 than it was in 1983. Our findings support the idea that the type of incentives in place may be responsible for this increase in inequality within orphan diseases

Optimal sequential sampling rules for the economic evaluation of health technologies

Referring to the literature on optimal stopping under sequential sampling developed by Chernoff and collaborators, we solve a dynamic model of the economic evaluation of a new health technology, deriving optimal rules for technology adoption, research abandonment and continuation as functions of sample size. The model extends the existing literature to the case where an adoption decision can be deferred and involves a degree of irreversibility. We explore the model's applicability in a case study of the economic evaluation of Drug Eluting Stents (DES), deriving dynamic adoption and abandonment thresholds which are a function of the model's economic parameters. A key result is that referring to a single cost-effectiveness threshold may be sub-optimal.Cost-effectiveness analysis, Sequential sampling, Dynamic programming

Counting co-occurrences in citations to identify plagiarised text fragments

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-40802-1_19Research in external plagiarism detection is mainly concerned with the comparison of the textual contents of a suspicious document against the contents of a collection of original documents. More recently, methods that try to detect plagiarism based on citation patterns have been proposed. These methods are particularly useful for detecting plagiarism in scientific publications. In this work, we assess the value of identifying co-occurrences in citations by checking whether this method can identify cases of plagiarism in a dataset of scientific papers. Our results show that most the cases in which co-occurrences were found indeed correspond to plagiarised passagesThis work was partially funded by CNPq (478979/2012-6). Solange Pertile’s 5-month internship at NLE Lab of Universitat Polit`ecnica de Val`encia was funded by CAPES. P.Rosso’s work was carried out in the framework of the the VLC/CAMPUS Microcluster on Multimodal Interaction in Intelligent Systems and the European Commission WIQ-EI IRSES (no. 269180) and DIANA-APPLICATIONSFinding Hidden Knowledge in Texts: Applications (TIN2012-38603-C02-01) research projects. We thank the authors of [5] for sharing their dataset with us and Enrique Flores for the preliminary brainstorming on how to identify co-occurrences in citationsPertile, SDL.; Rosso, P.; Moreira, VP. (2013). Counting co-occurrences in citations to identify plagiarised text fragments. En Information Access Evaluation. Multilinguality, Multimodality, and Visualization. Springer Verlag (Germany). 150-154. https://doi.org/10.1007/978-3-642-40802-1_19S150154CrossCheck, http://www.crossref.org/crosscheck/Journal of Zhejiang University-Science, http://www.zju.edu.cn/jzus/PAN, http://www.pan.webis.dePlagiarism corpus, http://www.c2learn.com/plagiarism/corpus/v1/Alzahrani, S., Palade, V., Salim, N., Abraham, A.: Using structural information and citation evidence to detect significant plagiarism cases in scientific publications. JASIST 63(2), 286–312 (2012)Barrón-Cedeño, A., Vila, M., Marti, A., Rosso, P.: Plagiarism meets paraphrasing: Insights for the next generation in automatic plagiarism detection. Computational Linguistics 39(4) (2013)Cortez, E., da Silva, A.S., Gonçalves, M.A., de Moura, E.S.: Ondux: on-demand unsupervised learning for information extraction. In: SIGMOD, pp. 807–818 (2010)Gipp, B., Meuschke, N.: Citation pattern matching algorithms for citation-based plagiarism detection: greedy citation tiling, citation chunking and longest common citation sequence. In: DocEng, pp. 249–258 (2011)Gupta, P., Rosso, P.: Text reuse with ACL (upward) trends. In: ACL 2012 Special Workshop on Rediscovering 50 Years of Discoveries, pp. 76–82 (2012)Mccabe, D.L.: Cheating among college and university students: A north american perspective. International Journal for Educational Integrity 1 (2005)Potthast, M., Barrón-Cedeño, A., Stein, B., Rosso, P.: Cross-language plagiarism detection. Language Resources and Evaluation 45(1), 45–62 (2011)Potthast, M., Gollub, T., Hagen, M., Tippmann, M., Kiesel, J., Stamatatos, E., Rosso, P., Stein, B.: Overview of the 5th International Competition on Plagiarism Detection. In: CLEF 2013 - Working Notes (September 2013)Ritt, M., Costa, A.M., Mergen, S., Orengo, V.M.: An integer linear programming approach for approximate string comparison. European Journal of Operational Research 198(3), 706–714 (2009)Zhang, Y.: Crosscheck: an effective tool for detecting plagiarism. Learned Publishing 23, 9–14 (2010