Roberto Rodríguez-Ibeas

Transferability indices for health economic evaluations: methods and applications

In this paper, we have elaborated an index in two phases to measure the degree of transferability of the results of the economic evaluation of health technologies. In the first phase, we have considered the objective factors (critical and non-critical) to derive a general transferability index, which can be used to measure this internal property of the studies of economic evaluation applied to health technologies. In the second phase, with a more specific index, we have measured the degree of applicability of the results of a given study to a different setting. Both indices have been combined (arithmetic and geometric mean) to obtain a global transferability index. We have applied the global index to a sample of 27 Spanish studies on infectious diseases. We have obtained an average value for the index of 0.54, quite far from the maximum theoretical value of 1. We also found that 11 studies lacked some critical factor and were directly deemed as not transferable.

Should health authorities offer risk-sharing contracts to pharmaceutical firms? A theoretical approach

In this paper, we characterise the risk-sharing contracts that health authorities can design when they face a regulatory decision on drug pricing and reimbursement in a context of uncertainty. We focus on two types of contracts. On the one hand, the health authority can reimburse the firm for each treated patient regardless of health outcomes (non risk-sharing). Alternatively, the health authority can pay for the drug only when the patient is cured (risk-sharing contract). The optimal contract depends on the trade-off between the monitoring costs, the marginal production cost and the utility derived from treatment. A non-risk-sharing agreement will be preferred by the health authority, if patients who should not be treated impose a relatively low cost to the health system. When this cost is high, the health authority would prefer a risk-sharing agreement for relatively low monitoring costs.

Genetic testing in the European Union: does economic evaluation matter?

ObjectiveWe review the published economic evaluation studies applied to genetic technologies in the EU to know the main diseases addressed by these studies, the ways the studies were conducted and to assess the efficiency of these new technologies. The final aim of this review was to understand the possibilities of the economic evaluations performed up to date as a tool to contribute to decision making in this area.MethodsWe have reviewed a set of articles found in several databases until March 2010. Literature searches were made in the following databases: PubMed; Euronheed; Centre for Reviews and Dissemination of the University of York—Health Technology Assessment, Database of Abstracts of Reviews of Effects, NHS Economic Evaluation Database; and Scopus. The algorithm was “(screening or diagnosis) and genetic and (cost or economic) and (country EU27)”. We included studies if they met the following criteria: (1) a genetic technology was analysed; (2) human DNA must be tested for; (3) the analysis was a real economic evaluation or a cost study, and (4) the articles had to be related to any EU Member State.ResultsWe initially found 3,559 papers on genetic testing but only 92 articles of economic analysis referred to a wide range of genetic diseases matched the inclusion criteria. The most studied diseases were as follows: cystic fibrosis (12), breast and ovarian cancer (8), hereditary hemochromatosis (6), Down’s syndrome (7), colorectal cancer (5), familial hypercholesterolaemia (5), prostate cancer (4), and thrombophilia (4). Genetic tests were mostly used for screening purposes, and cost-effectiveness analysis is the most common type of economic study. The analysed gene technologies are deemed to be efficient for some specific population groups and screening algorithms according to the values of their cost-effectiveness ratios that were below the commonly accepted threshold of 30,000€.ConclusionsEconomic evaluation of genetic technologies matters but the number of published studies is still rather low as to be widely used for most of the decisions in different jurisdictions across the EU. Further, the decision bodies across EU27 are fragmented and the responsibilities are located at different levels of the decision process for what it is difficult to find out whether a given decision on genetic tests was somehow supported by the economic evaluation results.

Regulatory Enforcement with Discretionary Fining and Litigation

In this paper, we focus on the determination of the optimal fine set by a regulator when a firm can litigate to avoid paying the fine and the monitoring agency has discretionary power to negotiate with the firm the size of the fine. The regulator needs to balance the positive effect of the fines size on the degree of non-compliance and the possibility of litigation if the fine is too high. We find that the optimal fine is not necessarily set at its maximum level. Copyright 2002 by Blackwell Publishing Ltd and the Board of Trustees of the Bulletin of Economic Research

Some economics on personalized and predictive medicine.

ObjectiveTo contribute to the theoretical literature on personalized medicine, analyzing and integrating in an economic model, the decision a health authority faces when it must decide on the implementation of personalized medicine in a context of uncertainty.MethodsWe carry out a stylized model to analyze the decision health authorities face when they do not have perfect information about the best treatment for a population of patients with a given disease. The health authorities decide whether to use a test to match patients with treatments (personalized medicine) to maximize health outcomes. Our model characterizes the situations under which personalized medicine dominates the alternative option of business-as-usual (treatment without previous test). We apply the model to the KRAS test for colorectal cancer, the PCA3 test for prostate cancer and the PCR test for the X-fragile syndrome, to illustrate how the parameters and variables of the model interact.ResultsImplementation of personalized medicine requires, as a necessary condition, having some tests with high discriminatory power. This is not a sufficient condition and expected health outcomes must be taken into account to make a decision. When the specificity and the sensitivity of the test are low, the health authority prefers to apply a treatment to all patients without using the test. When both characteristic of the test are high, the health authorities prefer to personalize the treatments when expected health outcomes are better than those under the standard treatment. When we applied the model to the three aforementioned tests, the results illustrate how decisions are adopted in real world.ConclusionsAlthough promising, the use of personalized medicine is still under scrutiny as there are important issues demanding a response. Personalized medicine may have an impact in the drug development processes, and contribute to the efficiency and effectiveness of health care delivery. Nevertheless, more accurate statistical and economic information related to tests results and treatment costs as well as additional medical information on the efficacy of the treatments are needed to adopt decisions that incorporate economic rationality.

Is personalized medicine a panacea for health management? Some thoughts on its desirability

During the last decade we have witnessed a change in health care management. Predictive, personalized [1], individualized [2] or stratified [3] medicine are some of the terms that have been coined to describe a new approach to dealing with disease. In essence, the new paradigm is based on matching patients with the best treatments available according to each patient’s characteristics. Patients are classified through new tests, mainly genetic in nature, the growing proliferation of which is behind the extensive application of this new approach to managing disease. In parallel, new therapies, many based on new mechanisms of action and biological agents, allow ever narrower targets within the cell to be addressed. This combination of new diagnostic techniques and targeted therapies has improved the perspectives of managing some difficult conditions, such as some types of cancer, by controlling the progression of a disease and maintaining it rather as a chronic condition, even achieving a cure in some cases. This new paradigm is raising expectations for both patients and physicians. Health care systems are transforming the management of some diseases and re-writing treatment guidelines to incorporate the advantages of newly available therapies and approaches. However, notwithstanding the rapid development of these changes, there are some issues that should also be taken into account. Here, we highlight some elements that are frequently overlooked or taken for granted. Personalized medicine is frequently based on drug treatments that are more expensive than other, more traditional, therapies. These types of new drug generally target conditions that are more prevalent in developed countries, where a wide market in terms of potential patients and purchase capacity exists. To our knowledge, there is no experience of this kind of approach being used to address conditions whose prevalence is higher in less developed countries. It would be interesting to make personalized medicine accessible to lower income countries so that they could also benefit from the new advantages. A clear contribution of personalized medicine is that it aims to address the imperfect information related to diagnoses and effectiveness that generates uncertainties in healthcare. Personalized medicine reduces uncertainty by identifying more clearly those patients that will response better to treatment and by establishing new and more specific therapeutic targets. However, personalized medicine could also have the ‘‘side effect’’ of introducing undesirable effects into the system, in the sense that new diseases are seemingly created based on an identified gene mutation. Manufacturers intend to classify mutations of the general condition as potential new orphan diseases (prevalence lower than 50 cases per 100,000 persons), which, as a consequence, would attract a greater reward from health authorities in terms of higher prices for the new therapy, and probably better reimbursement policies. Of course, this process would imply higher costs for public health care systems. This is nothing new at this point, however, as this trade-off between improved health outcomes and higher health costs is already common practice. Within the last decade, new tests, mostly genetic, have gained access to the market. Currently, there are over 1,800 genetic tests that help define and classify new diseases and patients [4]. Some tests belong to the field of so-called companion tests, i.e., they must be applied to patients prior to the administration of a given drug to make sure that they are the right candidate to receive that medication. Other tests do not belong to this category and their link to drug F. Antonanzas (&) C. A. Juarez-Castello R. Rodriguez-Ibeas University of La Rioja, Logrono, Spain e-mail: fernando.antonanzas@unirioja.es

Impacto del Real Decreto-Ley 16/2012 sobre el copago farmacéutico en el número de recetas y en el gasto farmacéutico

Fundamentos: el objetivo del trabajo es es conocer si el impacto del Real Decreto-Ley 16/2012 en el numero de recetas y el gasto farmaceutico, evaluadas por el Ministerio de Sanidad, Servicios Sociales e Igualdad (MSSSI), se corresponden con las obtenidas por otros metodos estadisticos habitualmente empleados. Asimismo, se han elaborado unos modelos para predecir la evolucion de ambas variables entre septiembre de 2013 y diciembre de 2014. Metodos: se aplico la metodologia Box-Jenkins conjuntamente con el analisis de intervencion de Box-Tiao a datos del periodo 2003-13 para predecir mensualmente los valores de las series de recetas y gasto farmaceutico. Las predicciones se emplearon en un analisis contrafactico para compararlas con las series de recetas y gasto real. Tambien se efectuaron predicciones para el periodo de septiembre de 2013 a diciembre de 2014 para observar el impacto de la medida en un horizonte superior al real. Resultados: el analisis contrafactico estimo el descenso en el numero de recetas en un 12,18% y el del gasto farmaceutico en un 12,83%, mientras que al calcularse mediante el analisis de intervencion fueron 12,75% y 14,03%, respectivamente. Conclusiones: la reduccion estimada del numero de recetas para el periodo de junio de 2012 hasta agosto de 2013 es similar a la ofrecida por el MSSSI, mientras que para la serie del gasto farmaceutico fue inferior a la ofrecida por el MSSSI. La metodologia de Box-Jenkins genera errores de prediccion menores al 3% por lo que se considera util para anticipar fiablemente los consumos futuros.BACKGROUND this research aims to understand if the consequences on drug expenditures and number of prescriptions of Royal Decree-Law 16/2012 as estimated by the Ministry of Health, Social Services and Equality (MHSSE) are similar to those found by using common statistical approaches. In addition, several models have been built to forecast the evolution of both variables for the period September 2013-December 2014. METHODS the Box-Jenkins methodology and the Box-Tiao intervention analysis were applied to data of the period 2003-13 to forecast the monthly values of the number of prescriptions and pharmaceutical expenditures. Forecasts were used in a counter-factual analysis to be compared to the actual values of prescriptions and drug expenditures. Moreover, forecasts for the period September 2013 to December 2014 were obtained to observe the impact of the policy in the future. RESULTS the counterfactual analysis estimated a decrease in the number of prescriptions of 12.18% and 12.83% in the pharmaceutical expenditure; these figures were 12,75% and 14,03% respectively, when the intervention analysis was used. CONCLUSION the estimated reduction in the number of prescriptions for the period June 2012-August 2013 was similar to the figure offered by the MHSSE, while the reduction in the drug expenditure series was smaller. The Box-Jenkins methodology generated low forecast errors (less than 3%) what makes this procedure useful to reliably anticipate future consumptions.

Channeling health economics research initiatives to improve decision-making processes in the EU

Health economics as a specialization area has rapidly grown during the last 4 decades. Researchers have selected the topics according to a variety of issues, such as general scientific interest, background knowledge, and perceived gaps in the field as well as the relevance of the topics to their jurisdictions, among others. On the part of the health authorities (managers and politicians), they have to cope with a variety of real-life types of problems that need to be addressed. In their daily practice, they have at their disposal instruments and information from the health economics literature to better manage their health systems. Nevertheless, some mismatches exist in the activities developed by these two groups. On the one hand, it is believed that health authorities disregard or do not use all the available information generated by researchers in their decision-making processes. This could be due to either the irrelevance of a given research for a specific health decision or because health authorities simply ignore it. On the other hand, researchers, for whatever the reason, do not address some topics that really matter to health managers and that would potentially improve the general efficiency of healthcare systems and increase social welfare. The interest in assessing the value of research activities in support of health systems policies was highlighted by Buxton and Hanney 2 decades ago [1]. The need to cope with the gap between research and health policy has also been previously acknowledged by some authors and institutions such as the WHO [2–4]. However, the number of studies and their scope have been quite limited (addressing particular health areas such as pain [5], focusing on single Member States’ research needs [6], being descriptive of some situations [7], and dealing with specific research venues—such as the economic evaluation of health technologies [8] and the value of information as a technique to establish research topics in economic evaluation [9]). More recently, Hunter and Brown [10] have reviewed research topics within the field of health management, and Debrand and Dourgnon [11] described the relationships between health economics research and health policies debated in a meeting of experts from several countries; they also emphasized the need for ‘‘using research evidence to produce pertinent and efficient tools for health policymaking.’’ In spite of these efforts, there is a lack of systematic analysis (follow-up or periodic reviews) on this topic so that health research can be channeled to the more useful areas of health policy making. Other authors have recently noted the necessity to fill the gap between health research and policy [12]. Interestingly, health economics scientific policy in most of the EU countries usually relies on public calls as the instruments to channel funds to research programs. However, these programs have vaguely defined goals and are commonly framed in rather general terms, either guided by some leading research teams or by politicians and bureaucrats in charge of the general scientific policy. Health authorities are not usually empowered to decide on or select the guiding principles of the general scientific policy (i.e., the goals of the calls for each program). In this environment, it is a common practice for each research group to participate in the calls by proposing its preferred topics, which usually find a niche that makes their proposal eligible to receive financial aid. One frequent evaluation criterion to evaluate the results of a research project ex-post is to look at the quality of the peer-reviewed F. Antonanzas (&) R. Rodriguez-Ibeas Department of Economics, University of La Rioja, 26004 Logrono, Spain e-mail: fernando.antonanzas@unirioja.es

Pharmaceutical patents, R&D incentives and access to new drugs: new ways of progress at the crossroad

Patents are defined as a right granted to innovators by governments for the exclusive production and marketing of an innovation for a limited period of time. Patent owners enjoy a legal monopoly. Patents rights have traditionally been considered a good mechanism to provide incentives to innovate as it allows innovators to obtain monopolistic benefits that compensate the R&D expenditures. In the case of the pharmaceutical industry, as imitation of new drugs is relatively easy and it is difficult to keep the ‘first mover’ advantage in the market, it seems that the patent system is the only mechanism to incentive the innovative activity.

Improving health care systems by building ‘more Europe’

Health results from a combination of different factors, but society tends to believe that health care systems have the highest responsibility to provide the inputs needed to increase quality of life and survival, the two major variables that allow us to quantify such an abstract and multifactorial concept as health. Health care systems require human resources, scientific knowledge and technologies to yield the expected output. A system is, by definition, a set of organized elements that interact among themselves to achieve a given target. But, so far, the context within which the interaction of the elements of health care systems has taken place has been national (or in some cases regional), rather than supranational. And that is the crucial issue we would like to address in this text. The organization of a national health system, in order to efficiently achieve its goals, should consider the organization of other neighboring systems, especially when the country belongs to an international structure such as the European Union (EU). So far, the Member States (MS) are competent to organize their own care systems, and the European Commission has mainly limited its directives to facilitate a common framework regarding a few aspects of the inputs related to health such as the supplementary protection certificates for extending the patent protection of technologies (mostly drugs and medical devices), the design of the clinical trials for drug research, the creation of the European Medicaments Agency to assess the value of new drugs, and patient data protection issues. The mobility of human resources across countries is not yet straightforward in all countries, and we still lack an EU common title of medicine, for instance. Furthermore, the differences in access requirements that each health system has make difficult the provision of health care to those who are not citizens of a specific country, despite the fact that the majority of the European systems are mostly public. To cope with all these issues several general policies are needed (educative, migratory as well as those related to the EU citizenship right to health care). These policies exceed the competence of the health departments of the MS and require a higher political consensus to be implemented. However, there are other policies that more directly belong to the area of influence of the health departments and could eventually be applied more easily. We will refer to them in the following paragraphs. The target of efficiency, i.e., higher quality care for less cost, is aimed at by every system. New health technologies are continuously launched to markets and the systems incorporate them to improve the quality of their services. In the WHO document of Health for all in the year 2000 for the European region it was already clear that health systems had to perform assessments of new technologies to guarantee a good level of quality and efficiency. Accordingly, EU national systems implemented assessment mechanisms and created many agencies to analyze the value and characteristics of health technologies (national, regional, specific for drugs, general for all technologies, etc.). Contingent to the results of the assessments, health technologies are priced and reimbursed in some countries, are positioned in the treatments algorithm in others and, finally, are prescribed or restricted in health care centers depending on each jurisdiction too. However, the assessment processes and methods, and the influence of their results in the health care systems deeply differ across regions and countries. As an example, the recent paper by & F. Antoñanzas fernando.antonanzas@unirioja.es