Issues for countries considering introducing the "fourth hurdle": The case of Hungary

Objectives: This study outlines the needs and current development of the "fourth hurdle" (i.e., requirement of effectiveness and cost-effectiveness data for drug coverage policy decisions) in Hungary, describes the legal background and seeks to address some of the most important questions in this field. Methods: The study draws on international experiences and discusses five issues that a given jurisdiction needs to consider before introducing the "fourth hurdle" for pharmaceuticals. Results: The "fourth hurdle" is very relevant in Hungary because many existing drugs are unevaluated and many new, expensive drugs are becoming available. On the other hand, the existing resources for health technology assessment, including economic evaluation, are quite limited. All the five issues are relevant in the Hungarian setting and were helpful in determining exactly how the "fourth hurdle" should be applied. Conclusions: The most important issue seems to be that the implementation of the "fourth hurdle" needs to be achieved in a way consistent with the limited resources for HTA in Hungary. Specifically this means that, in setting priorities for drugs to evaluate, additional criteria need to be applied. In particular, priority should be given to assessing drugs that have been evaluated in other countries, because this affords the opportunity to adapt existing studies or models to the Hungarian situation

Flattening an object algebra to provide performance

Algebraic transformation and optimization techniques have been the method of choice in relational query execution, but applying them in object-oriented (OO) DBMSs is difficult due to the complexity of OO query languages. This paper demonstrates that the problem can be simplified by mapping an OO data model to the binary relational model implemented by Monet, a state-of-the-art database kernel. We present a generic mapping scheme to flatten data models and study the case of straightforward OO model. We show how flattening enabled us to implement a query algebra, using only a very limited set of simple operations. The required primitives and query execution strategies are discussed, and their performance is evaluated on the 1-GByte TPC-D (Transaction-processing Performance Council's Benchmark D), showing that our divide-and-conquer approach yields excellent result

Vectorwise: Beyond Column Stores

textabstractThis paper tells the story of Vectorwise, a high-performance analytical database system, from multiple perspectives: its history from academic project to commercial product, the evolution of its technical architecture, customer reactions to the product and its future research and development roadmap. One take-away from this story is that the novelty in Vectorwise is much more than just column-storage: it boasts many query processing innovations in its vectorized execution model, and an adaptive mixed row/column data storage model with indexing support tailored to analytical workloads. Another one is that there is a long road from research prototype to commercial product, though database research continues to achieve a strong innovative influence on product development

Comparing cost-sharing practices for pharmaceuticals and health care services among four central European countries

The paper reviews the existing cost-sharing practices in four Central European countries namely the Czech Republic, Hungary, Poland and Slovakia focusing on patient co-payments for pharmaceuticals and services covered by the social health insurance. The aim is to examine the role of cost-sharing arrangements and to evaluate them in terms of efficiency, equity and public acceptance to support policy making on patient payments in Central Europe. Our results suggest that the share of out-of-pocket payments in total health care expenditure is relatively high (24–27%) in the countries examined. The main driver of these payments is the expenditure on pharmaceuticals and medical devices, which share exceeds 70% of the household expenditure on health care. The four countries use similar cost-sharing techniques for pharmaceuticals, however there are differences concerning the measure of exemption mechanisms for vulnerable social groups. Patient payment policies for health care services covered by the social health insurance are also converging. All the four countries apply co-payments for dental care, some hotel services or in the case of free choice of physician. Also the countries (except for Poland) tried to extend co-payments for physician services and hospital care. However, their introduction met strong political opposition and unpopularity among public

MonetDB/XQuery: a fast XQuery processor powered by a relational engine

Relational XQuery systems try to re-use mature relational data management infrastructures to create fast and scalable XML database technology. This paper describes the main features, key contributions, and lessons learned while implementing such a system. Its architecture consists of (i) a range-based encoding of XML documents into relational tables, (ii) a compilation technique that translates XQuery into a basic relational algebra, (iii) a restricted (order) property-aware peephole relational query optimization strategy, and (iv) a mapping from XML update statements into relational updates. Thus, this system implements all essential XML database functionalities (rather than a single feature) such that we can learn from the full consequences of our architectural decisions. While implementing this system, we had to extend the state-of-the-art with a number of new technical contributions, such as loop-lifted staircase join and efficient relational query evaluation strategies for XQuery theta-joins with existential semantics. These contributions as well as the architectural lessons learned are also deemed valuable for other relational back-end engines. The performance and scalability of the resulting system is evaluated on the XMark benchmark up to data sizes of 11GB. The performance section also provides an extensive benchmark comparison of all major XMark results published previously, which confirm that the goal of purely relational XQuery processing, namely speed and scalability, was met

Pathfinder: XQuery - The Relational Way

Relational query processors are probably the best understood (as well as the best engineered) query engines available today. Although carefully tuned to process instances of the relational model (tables of tuples), these processors can also provide a foundation for the evaluation of "alien" (non-relational) query languages: if a relational encoding of the alien data model and its associated query language is given, the RDBMS may act like a special-purpose processor for the new language

P2P XQuery and the StreetTiVo application

MonetDB/XQuery* is a fully functional publicly available XML DBMS that has been extended with distributed and P2P data management functionality. Our (minimal) XQuery language extension XRPC adds the concept of RPC to XQuery, and we outlined our approach to include the services offered by diverse P2P network structures (such as DHTs), in a way that avoids any further intrusion in the XQuery language and semantics. We also discussed the StreetTiVo application were mxq is being used for data management in a large P2P environment. new construct called XRPC

From X100 to Vectorwise: opportunities, challenges and things most researchers do not think about

textabstractIn 2008 a group of researchers behind the X100 database kernel created Vectorwise: a spin-o which together with the Actian corporation (previously Ingres) worked on bringing this technology to the market. Today, Vectorwise is a popular product and one of the examples of conversion of a research prototype into successful commercial software. We describe here some of the interesting aspects of the work performed by the Vectorwise development team in the process, and discuss the op- portunities and challenges resulting from the decision of integrating a prototype-quality kernel with Ingres, an established commercial product. We also discuss how requirements coming from real-life scenarios sometimes clashed with design choices and simplications often found in research projects, and how Vectorwise team addressed some of of them