A major shift appears to be underway in Europe in the relationship between national, regional, and local control over health sector decision-making. Since World War II, a central thrust of health policy has been to decentralize key dimensions of decision-making authority to increasingly lower levels of government, as well as (in Social Health Insurance systems and recently in some tax-based systems) to private sector organizations.1 This strategy, to adapt Kondratiev's business-cycle framework,2 has been one of two overlapping âlong wavesâ that helped frame structural decisions in most Western European health systems. The second waveâmarket-influenced-entrepreneurialismâhas run simultaneously with decentralization since the late 1980s. However, while this second, market-oriented wave has generated considerable controversy in some health policy circles, the concept of decentralization was readily accepted in many national policy contexts. As a result, over the second half of the 20th century, expanded decentralization of authority to regional, municipal and non-governmental control has become part of the âreceived wisdomâ about what good health policy should include. In the tax-funded health systems in Nordic countries, for example, most administrative and managerial responsibility as well as substantial political (policy) and fiscal decision-making control has been decentralized inside the public sector: from national to regional level (somatic hospitals in Norway in 1970; mental hospitals in Sweden in 1967), from regional to municipal level (elderly residential care in Sweden in 1992), and from national to municipal level (effective decision-making control over central hospitals in Finland in 1993). In the tax-funded health systems in Southern Europe, most administrative and managerial as well as many political (but not key fiscal) responsibilities were devolved from national to regional governments in Spain (to the 17 autonomous communities from 1981 to 2003), and in Italy (to 22 regional governments starting in the late 1980s). In social health insurance funded countries in continental Europe such as Germany and the Netherlands, most administrative and managerial as well as many fiscal (but not key political) decisions have long been delegated to private not-for-profit bodies (sickness funds and hospitals), under a form of âenforced self-regulationâ grounded in explicit national statutory responsibilities.3 In many cases, this particular form of decentralization has been in place since those systemsâ inception. In the more state-based social insurance systems that have emerged since 1990 in many Central European countries, various forms of decentralization have been utilized. Reacting strongly to the prior highly centralized Semashko model, countries decentralized ownership of hospitals from national to regional (Hungary) and local (Estonia, Poland) governments. The Czech Republic even termed its decentralization of hospital ownership to municipal governments as âprivatizationâ. In similar fashion, centralized funding structures of the Communist period were decentralized into regional social health insurance funds in countries such as Poland, the Czech Republic and Slovakia. The strategic role of decentralization was further strengthened by changes in overall governmental structures in Europe. During the 1980s and 1990s, national governments increasingly ceded areas of sovereign power upward to European Union bodies, while at the same time that they were losing responsibilities downward to increasingly assertive regionsâa process captured by the popular 1990s discussion about a âEurope of Regionsâ. This overall reduction in the role of national governments served to reinforce the health sector experience that the era of centralized power at the national level in Europe was fast receding. In the first years of the 21st century, however, this conventional wisdom has started to come undone. Far from continuing to recede, the role of the state in the health sector has begun to strengthen measurably. Instead of reinforcing the continued decentralization of authority away from national governments, state institutions have reversed course and are seizing responsibility for substantive political and fiscal decision-making in European health care systems. It now appears that in the near-term future only administrative and managerial authorityâe.g. day-to-day operating decisionsâwill remain decentralized to lower level and/or non-governmental organizations. These counter-indications can be observed in many of the health systems noted earlier. In the tax-funded system in Norway, the national government took over political and administrative/managerial responsibility for all hospitals in the entire country in January 2002, removing control from the 19 regional governments (counties) that had previously owned and operated the public hospitals and transferring the administrative role to five newly created regional bodies appointed from Oslo. The national government also set out new rules for how these regions were to manage their hospitalsâas âpublic enterprisesâ. Fiscal responsibility for health care remained, as before, a national responsibility. In Denmark, the national government initiated a major re-structuring of the health sector in January 2006. In the new configuration, the number of regional governments was reduced from 14 to 5, and their powers were greatly reduced. Fiscal and most political responsibilities were centralized back to the national government, with certain prevention and chronic care issues being re-allocated to the municipalities (also consolidated, from 271 to 98). At the end of these changes, the new regions retained little more than administrative and managerial responsibility for hospitals. A similar pattern of regional consolidation and a strengthening of the state role appears to be underway in Sweden and Finland. In Sweden, a royal commission is expected to recommend that the number of regional level governments (which have responsibilities for hospital and also primary care) be reduced from the current 21 to between 6 and 8. Similarly, in Finland, the national government is expected to propose that the number of central hospital districts, currently 22, be reduced to 18, and also that the number of municipalities (responsible for primary, nursing home and home care services) be reduced from 450 to about 250. In the United Kingdom, similar recentralization can be seen in the transformation of England's Regional Health Authorities from line to support functions, as well as in current plans to reduce the number of Primary Care Trusts from 300 to 150. In Ireland, key operating responsibilities were recently shifted from regional health care boards to a health executive at central level and the regional boards were abolished. A parallel, if less aggressive, thrust toward more state control over both political and fiscal decisions can also be observed in several social health insurance funded countries. In the Netherlands, the national government in 2006 changed the health system's funding structure from a sliding 50% employee/50% employee paid model to a 100% individually paid fixed premium, supplemented by social assistance funds (e.g. taxes) for low income citizens. The Dutch government also, since the late 1990s, has been ratcheting up the percentage of total expenditures for which the private not-for-profit sickness funds are at risk, forcing funds to manage their money more efficiently. In Germany, the federal government in 2009 is scheduled to take on responsibility for pooling all social health insurance contributions and then allocating them to the sickness funds on a prospective, risk adjusted, capitation basis. While this funding model has been in place in the neighboring Netherlands for many years, in Germany it would represent a major move toward centralizing fiscal responsibilities away from the private not-for-profit sickness funds and into the hands of a national government body. In Central Europe, Poland, in 2003, pulled operating control over its social health insurance system away from 17 regional funds and back into the Ministry of Health. From the perspective of national health policymakers, this process of re-centralization appears to reflect a complex set of concerns. Structurally, there is substantial worry about the aging of their populations (e.g. more elderly), the rapid growth of expensive new clinical technologies, and the economic constraints on health sector funding generated by European regionalization as well as the globalization of markets. Administratively, there is evidence in countries like Finland and Norway (also concerns in Denmark) that local control over health sector decision-making has led to increased disparities in services provided and in outcomes to vulnerable populationsâin short, that decentralization has heightened equity problems. Economically, there are worries that local finance bases are insufficient to fund expensive future care needs, and that local administrative arrangements are inefficient and duplicative. Politicallyâan important factor in Northern European tax-funded countriesâthere is a sense among national politicians that they are being blamed when the health system fails to meet the expectations of the citizenry, and that national policymakers need to have the necessary organizational levers to correct these problems. Technically, the introduction of electronic medical records and other computerized reporting systems has reduced the transaction costs of information and made it feasible to more closely monitor health system performance from a central level. While many of these dilemmas with decentralization were predicted earlier in theoretical assessments,4 one can see strong elements of their concrete manifestation in the current movement toward re-centralization. Moreover, since these causal factors are long-term in nature, their recent importance lends strength to the argument that re-centralization may indeed represent a long-term structural shift in national health strategies. Several important questions arise from these examples of re-centralizaton in both tax funded as well as social health insurance funded health systems. One is whether the observed changes represent more than just the normal ebb-and-flow of policy development in European health systems, and instead signal a fundamental shift in the overall pattern of these decisions. A related question is whether political and fiscal authority will continue to migrate from regional and municipal to national government, leaving mostly administrative and managerial forms of control at the lower levels. The underlying issue here concerns the mix of national and local authority that typically exists within most European health care systems, and whether the main bias in structuring that mix might be changing from one favouring decentralizing to local governments into one that favors centralizing authority back to national governments. Posed more provocatively, one might ask whether a new âlong waveâ of re-centralization has now begun, pointing toward a health policy future of stronger national governments and weaker regional, local, and delegated private (SHI) institutions. There areâas Kuhn's theory about the complexities of paradigm shift would predict5âseveral confounding factors in arriving at satisfactory answers to these questions. One issue concerns whether a new âlong waveâ of re-centralization can co-exist comfortablyâas decentralization didâwith the parallel long-wave pattern of market-influenced entrepreneurial measures, particularly in tax-funded health systems. Will re-centralization and entrepreneurialism reinforce each other, as happened previously with decentralized local units? Second, there are several exceptions to this broad pattern of increasing re-centralization across European health systems. One clear exception is in countries with serious ethnic conflicts, for example Bosnia-Herzegovina and Macedonia in the Balkans, and also in Belgium. Recent history suggests that decentralization may be essential in these highly charged political environments, in that various forms of local control are typically linked to the survival of the state itself. Another conceptually messy question concerns the pattern of continued regional decentralization of health sector decisions in Southern European countries like Italy and Spain. Regional governments in these two countries have fiercely defended their recently gained authority in the health sector, and have forced their less convinced central governments (Spain in 2003, for example) to tread carefully in designing new national programs to monitor performance or set standards for quality and outcomes. Of course, Spain and Italy both have histories of earlier regional sovereignty. Moreover, both are geographically larger and have bigger populations than Nordic countriesâalthough they are roughly equal in size to the United Kingdom and also Poland. There is, further, within both Italian and Spanish regions a tendency toward greater internal centralization inside the regions themselves. Despite these caveats, however, it appears that Italy and Spain are pursuing greater decentralization at the same point in time that Northern European countries are shifting away from decentralization in their health systems. This brief review of recent health sector patterns raises a series of questions that do not allow for easy answers. A further complicating factor is the apparent lack of fit between continued local control over services to the elderly (home care, social assistance, also nursing home care) and increasing central control over fiscal and policy decisions in the overall health sector, which implies that re-centralization may soon confront key structural limitations. The current distribution of health sector evidence does suggest, however, that many European health systems will continue to see a tightening of state controls, especially over fiscal and quality-related matters. In this clash between national and local governments, it would appear that, on balance, democratic control at the national level will strengthen, taking increased authority over political and fiscal decisions, while democratic control at the regional and municipal level will weaken, and be increasingly focused only on administrative and managerial decisions. Moreover, given the rapid melting of publicâprivate boundaries within many European health systems, this greater state role will likely be combined with growing public as well as private sector entrepreneurialism, despite the appearance that greater reliance on market-oriented decisions contradicts tighter state control over health system behaviour. While the particular balance between increased state controls and increased entrepreneurial initiatives will vary from country to country, this new blend of two âlong wavesâ, with increasing levels of state authority over key health sector decisions, will likely define the future policymaking framework for many European health systems in the near-term future. Earlier versions of this argument were presented at the Third International Health Policy Conference in Jerusalem (December 2006) and the Annual Meeting of the European Public Health Association in Helsinki (October 2007). This version has benefited from comments made by a number of colleagues at both meetings, and especially from Josep Figueras, David Chinitz and Charles Phelps. An earlier version of this article is included in the conference proceedings of the Jerusalem meeting.
Open access
Health Systems, Economic Evaluations, Quality of Life
In many countries health services and/or health insurance are delivered but also partly financed by subnational entities that vary in their fiscal or financial capacity, e.g. local governments and social health insurance schemes. The central government typically mandates a specific (or at least minimum) level of benefit or expenditure per intended beneficiary, and sets rules about enrollment and coverage. It also typically contributes to the cost of the program, partly because the resources of subnational entities may be insufficient, on average, to meet the expenditure requirements, but partly for equity reasons. These two problems are typically addressed through tax-transfer schemes. In practice, there is considerable institutional heterogeneity across countries in the mix of vertical and horizontal schemes, and the way each works. In this Note, we show how the progressivity of health outlays by subnational entities can be decomposed into contributions from vertical and horizontal schemes, and how each of these can be further decomposed into contributions from taxes and transfers. We suggest that, in addition to providing a foundation for future empirical work, the decomposition provides some insights into the reasons for different institutional choices, and into the way vertical and horizontal tax-transfer schemes operate in practice.
Global Health Care Issues
Healthcare Policy and Management
Health Systems, Economic Evaluations, Quality of Life
District health systems, comprising primary health care and first referral hospitals, are key to the delivery of basic health services in developing countries. They should be prioritized in resource allocation and in the building of management and service capacity. The relegation in the World Health Report 2000 of primary health care to a 'second generation' reform--to be superseded by third generation reforms with a market orientation--flows from an analysis that is historically flawed and ideologically biased. Primary health care has struggled against economic crisis and adjustment and a neoliberal ideology often averse to its principles. To ascribe failures of primary health care to a weakness in policy design, when the political economy has starved it of resources, is to blame the victim. Improvement in the working and living conditions of health workers is a precondition for the effective delivery of public health services. A multidimensional programme of health worker rehabilitation should be developed as the foundation for health service recovery. District health systems can and should be financed (at least mainly) from public funds. Although in certain situations user fees have improved the quality and increased the utilization of primary care services, direct charges deter health care use by the poor and can result in further impoverishment. Direct user fees should be replaced progressively by increased public finance and, where possible, by prepayment schemes based on principles of social health insurance with public subsidization. Priority setting should be driven mainly by the objective to achieve equity in health and wellbeing outcomes. Cost effectiveness should enter into the selection of treatments for people (productive efficiency), but not into the selection of people for treatment (allocative efficiency). Decentralization is likely to be advantageous in most health systems, although the exact form(s) should be selected with care and implementation should be phased in after adequate preparation. The public health service should usually play the lead provider role in district health systems, but non-government providers can be contracted if needed. There is little or no evidence to support proactive privatization, marketization or provider competition. Democratization of political and popular involvement in health enhances the benefits of decentralization and community participation. Integrated district health systems are the means by which specific health programmes can best be delivered in the context of overall health care needs. International assistance should address communicable disease control priorities in ways that strengthen local health systems and do not undermine them. The Global Fund to Fight AIDS, Tuberculosis and Malaria should not repeat the mistakes of the mass campaigns of past decades. In particular, it should not set programme targets that are driven by an international agenda and which are achievable only at the cost of an adverse impact on sustainable health systems. Above all the targets must not retard the development of the district health systems so badly needed by the rural poor.
Open access
Healthcare Policy and Management
Health Systems, Economic Evaluations, Quality of Life
Carlos Centeno, S. Hernansanz, Luis Alberto Flores, Ălvaro Sanz Rubiales · 5 authors
Abstract This chapter offers an in-depth look at health politics and the tax-financed, universal health system in Spain. It traces the development of the Spanish healthcare system, focusing in particular on its double transition in the 1980s and 1990s from a centralized social insurance system, mostly funded through workersâ and employersâ contributions, to a decentralized universal model financed by general taxation. The new national health system aimed at covering all residents and transferred healthcare competences to the regions, i.e. the seventeen Autonomous Communities, a process completed in 2001. Key issues include rationalization, harmonization, and territorial equity-building of the decentralized healthcare system; efficiency improvement through the introduction of private management elements; and cost containment to bolster the systemâs financial sustainability in the context of growing demand and scarce resources. As the chapter argues, these challenges along with the remarkable changes in the political party system have increased the political salience of healthcare in public debate in the 2010s, but the prospects for developing consensual healthcare policies have worsened, such that structural problems are likely to persist.
Committee for Proprietary Medicinal Products (CPMP)
A number of recent applications have led to CPMP discussions concerning the interpretation of superiority, noninferiority and equivalence trials. These issues are covered in ICH E9 (Statistical Principles for Clinical Trials). There is further relevant material in the Step 2 draft of ICH E10 (Choice of Control Group) and in the CPMP Note for Guidance on the Investigation of Bioavailability and Bioequivalence. However, the guidelines do not address some specific difficulties that have arisen in practice. In broad terms, these difficulties relate to switching from one design objective to another at the time of analysis. The types of trials in question are those designed to compare a new product with an active comparator. The objective may be to demonstrate: the superiority of the new product the noninferiority of the new product or the equivalence of the two products. When the results of the trial become available, they may suggest an alternative interpretation. Thus the results of a superiority trial may only appear to be sufficient to support noninferiority, while the results of a noninferiority trial may appear to support superiority. Alternatively, the results of an equivalence trial may appear to support a tighter range of equivalence. A satisfactory approach to this subject requires an understanding of confidence intervals and the manner in which they capture the results of the trial and indicate the conclusions that can be drawn from them. Such an understanding also leads to an appreciation of why power calculations are of relatively little interest when a trial is complete. For simplicity, this paper addresses the issues of superiority, noninferiority and equivalence from the perspective of an efficacy trial with a single primary variable. Some comments on other situations are made in Section VI. It is assumed throughout this document that switching the objective of a trial does not lead to any change in the selection or definition of the primary variable. A superiority trial is designed to detect a difference between treatments. The first step of the analysis is usually a test of statistical significance to evaluate whether the results of the trial are consistent with the assumption of there being no difference in the clinical effect of the two treatments. In a trial of good quality, the degree of statistical significance (P value) indicates the probability that the observed difference, or a larger one, could have arisen by chance assuming that no difference really existed. The smaller this probability is, the more implausible is the assumption that there really is no difference between the treatments. Once it is accepted that the assumption of âno differenceâ is untenable, it then becomes important to estimate the size of the difference in order to assess whether the effect is clinically relevant. This has two aspects. First there is the best estimate of the size of the difference between treatments (point estimate). For normally distributed data this is usually taken as the observed difference between the mean values on each. Next, there is the range of values of the true difference that are plausible in the light of the results of the trial (confidence interval). It is clear that this range should not include zero since the possibility of a zero difference has already been rejected as unreasonable. The method of constructing confidence intervals generally ensures that this is so, provided it corresponds to the choice of significance test. Thus the following two statements are usually equivalent: The two-sided 95% confidence interval for the difference between the means excludes zero. The two means are statistically significantly different at the 5% level (P < 0.05) two-sided. The above text addresses the situation where the difference between two mean values is the statistic of interest and a zero difference represents no effect. In practice a number of other summary statistics are used for the evaluation of differences between treatments, for example the odds ratio for proportions or the ratio of geometric means in bio-equivalence studies. (The latter arises from the logarithmic transformation used for bioavailability data.) In such cases the same principles apply but âno differenceâ may be represented by a value other than zero â a value of 1 in both the examples quoted here. In these cases it is the position of the confidence interval for the test statistic relative to this âno differenceâ value that is of interest. When significance tests are carried out in practice, precise numerical values of probabilities are usually quoted, for example P = 0.032, because this is more informative than P < 0.05. This allows judgement to be based more precisely on the extent of the disagreement between the null hypothesis and the observed data rather than on the approximations implied by using cut-off points of 0.05, 0.01 and 0.001. However, confidence intervals have to be associated with a specific probability value (coverage probability) and this is nearly always taken as 95% (0.95). When a difference is statistically significant at a more extreme level, e.g. P = 0.002, the two-sided 95% confidence interval will exclude zero by a wider margin. Figure 1 illustrates these points. Relationship between significance tests and confidence intervals. Whether the observed difference is indeed clinically relevant is a matter of judgement. In contrast to an equivalence or noninferiority trial where clinical relevance is addressed through the prestudy choice of Î (see II.2 and II.3), in a superiority trial clinical relevance requires separate consideration: a statistically significant difference may not be clinically relevant. The difference taken as the basis of the power calculation in a superiority trial cannot be assumed to provide a suitable value. Note that in Figure 1, and throughout the rest of the document, it is assumed that values to the right of zero correspond to a better response on the new treatment so that values to the left are worse, i.e. better on the control treatment. An equivalence trial is designed to confirm the absence of a meaningful difference between treatments. In this case it is more informative to conduct the analysis by means of the calculation and examination of the confidence interval although there are closely related methods using significance test procedures. (See also II.3.) A margin of clinical equivalence (Î) is chosen by defining the largest difference that is clinically acceptable, so that a difference bigger than this would matter in practice. There are well-recognized difficulties associated with this task which will not be discussed in any detail here. If the two treatments are to be declared equivalent, then the two-sided 95% confidence interval â which defines the range of plausible differences between the two treatments â should lie entirely within the interval âÎ to + Î, see Figure 2. There are situations in which the equivalence margins may be chosen asymmetrically with respect to zero. Confidence interval approach to analysis of equivalence trial. In the case of bioequivalence studies a coverage probability of 90% for the confidence interval has become the accepted standard when evaluating whether the average values of the pharmacokinetic parameters of two formulations are sufficiently close. Clinical equivalence trials, with two-sided 95% confidence intervals, may be carried out when conventional bio-equivalence trials are impossible, for example in the case of a generic inhaled or topically applied product. In Phase III drug development, noninferiority trials are more common than equivalence trials. In these we wish to show that a new treatment is no less effective than an existing treatment â it may be more effective or it may have a similar effect. Again a confidence interval approach is the most straightforward way of performing the analysis but now we are only interested in a possible difference in one direction. Hence the two-sided 95% confidence interval should lie entirely to the right of the value âÎ, see Figure 3. Non-inferiority trials are sometimes mistakenly referred to, and designed as, equivalence trials. This distinction is important and can be a source of confusion. Confidence interval approach to analysis of non-inferiority trial. Note also that by using the closely related significance testing procedures referred to in II.2, it is possible to calculate a P value associated with the null hypothesis of inferiority. This is a valuable further aid to assessing the strength of the evidence in favour of noninferiority. It will be assumed throughout this document that two-sided 95% confidence intervals are to be used for all clinical trials whatever their objective. Among other benefits, this preserves consistency between significance testing and subsequent estimation. It is also consistent with the guidance provided in the ICH E9 Note for Guidance. If one-sided intervals are used, then they should be used with a coverage probability of 97.5%. In the special case of bioequivalence studies, two-sided 90% confidence intervals have been established as the norm as recommended, for example, in the CPMP Note for Guidance on the Investigation of Bioavailability and Bioequivalence. A conclusion of equivalence or noninferiority clearly depends upon the value of Î chosen as the maximum acceptable difference. It is always possible to choose a value of Î which leads to a conclusion of equivalence or noninferiority if it is chosen after the data have been inspected. Since the choice of Î is generally a difficult one, there is ample room for bias here, however, well intentioned the researcher may be. Plausible arguments may often be advanced for a retrospective choice. In the design of equivalence and noninferiority trials, this reason (amongst others) makes it necessary for the choice of Î, and the reasoning behind the choice, to be set down in advance by the researcher in the study protocol. The corresponding coverage probability for the confidence interval (usually 95%) should also be chosen at this time. (See Section IV.2 for how these requirements apply when objectives are changed.) The question of how to choose an appropriate Î will be addressed in a subsequent CPMP Points to Consider. Pre-definition of a trial as a superiority trial, an equivalence trial or a noninferiority trial is necessary for numerous reasons including the following: to ensure that comparator treatments, doses, patient populations and endpoints are appropriate (see ICH E10) to allow sample size estimates to be based on the correct power calculations to ensure that equivalence and noninferiority criteria are predefined to permit appropriate analysis plans to be described in the protocol to ensure that the trial has sufficient sensitivity to achieve its objectives (see ICH E10) If the objective of a trial is switched from superiority to noninferiority, or vice versa, these aspects may lead to greater difficulty than the interpretation of significance tests and confidence intervals. The only switching which is likely to have any practical relevance is switching between superiority and noninferiority. The place of equivalence trials is so specific that they stand alone. If the 95% confidence interval for the treatment effect not only lies entirely above âÎ but also above zero then there is evidence of superiority in terms of statistical significance at the 5% level (P < 0.05). See Figure 4. In this case it is acceptable to calculate the P value associated with a test of superiority and to evaluate whether this is sufficiently small to reject convincingly the hypothesis of no difference. There is no multiplicity argument that affects this interpretation because, in statistical terms, it corresponds to a simple closed test procedure. Usually this demonstration of a benefit is sufficient on its own, provided the safety profiles of the new agent and the comparator are similar. When there is an increase in adverse events, however, it is important to estimate the size of the effect to evaluate whether it is sufficient in clinical terms to outweigh the adverse effects. Non-inferiority to superiority. There are a number of other factors that might be affected by this changed objective. If the comparator was suitable for a demonstration of noninferiority, then there should be well-controlled data to show that it is an effective treatment. Hence, for proof of efficacy, a clear demonstration of superiority to the comparator in terms of statistical significance should be acceptable. Non-inferiority trials are generally large because of their need to exclude the possibility of a small degree of inferiority of a new agent relative to an active control. However if the new agent is actually superior to control by a small amount, then the power to show its noninferiority is increased. Demonstrating the small amount of superiority to control might in principle require the planning of an even larger trial. When the trial is completed, however, the results provided by the confidence interval supply a concrete assessment of the precision actually achieved, superseding any calculations of power carried out before the trial was undertaken. Since the comparator in a noninferiority trial must be an effective agent, any superiority to that agent should carry the implication of acceptable superiority to no treatment (placebo). For this reason the size of the additional clinical benefit demonstrated is not likely to be relevant to a claim of efficacy except in relation to any increase in adverse effects and hence relative risk/benefit. However, when the proposed licence includes a claim of superiority to the comparator, the size of the additional benefit should be discussed in clinical terms. In a superiority trial the full analysis set, based on the ITT (intention-to-treat) principle, is the analysis set of choice, with appropriate support provided by the PP (per protocol) analysis set. In a noninferiority trial, the full analysis set and the PP analysis set have equal importance and their use should lead to similar conclusions for a robust interpretation. A switch of objective would require this difference of emphasis to be recognized. More details of the relative importance of these two analysis sets in superiority and noninferiority trials can be found in the ICH E9 Note for guidance. A trial to show equivalence or noninferiority must show a high degree of consistency with protocolled plans if it is to be reliable. Deviations from the inclusion criteria, from the intended treatment regimen, from the schedule, manner and precision of taking measurements, and so on, all tend to reduce the sensitivity of a trial and to make a conclusion of âno differenceâ more likely, even when the deviations are of an unsystematic or random nature. The size of the bias associated with these and other departures from the protocol is generally unknown and may render such a trial uninterpretable. Failure to show a difference between two treatments can also arise when both treatments are inefficacious, perhaps as a result of being inappropriately administered. This problem does not affect superiority trials to the same extent because the demonstration of a difference is itself validation of the sensitivity of the trial. The estimate of the size of the effect may however, be similarly affected. For these reasons, switching from noninferiority to superiority is likely to carry with it a greater degree of confidence in the conclusion. Switching the objective of a trial from noninferiority to superiority is feasible provided: The trial has been properly designed and carried out in accordance with the strict requirements of a noninferiority trial. Actual P values for superiority are presented to allow independent assessment of the strength of the evidence. Analysis according to the intention-to-treat principle is given greatest emphasis. If a superiority trial fails to detect a significant difference between treatments, there may be interest in the lesser objective of establishing noninferiority. If the results of the superiority trial are summarized by means of a 95% confidence interval for the treatment difference, the lower end of that confidence interval provides a quantitative estimate of the minimum estimated effect of the new treatment relative to the comparator. When the study protocol an acceptable, margin âÎ for noninferiority, the objective less a noninferiority margin would appear only to make in trials with noninferiority as an However, in any superiority trial where noninferiority may be an acceptable for it is to a noninferiority margin in the protocol in order to the difficulties that can arise from such it is also to design to the possible need to that the study sufficient sensitivity to detect the drug effects of interest (see It is important to that there are of where noninferiority to an active control is to be acceptable as the or evidence of efficacy, and trials are to In trials where there is no noninferiority such a has to be after the and in situations this will not be It is likely that the will have to be after the results have been and there may be little basis for an objective choice of margin. there does not appear to be a statistical multiplicity related to this switch of that does not the difficulties associated with the definition of A number of other issues require A comparator chosen for a demonstration of superiority may not be acceptable for a conclusion of noninferiority. In order for it to be acceptable, it will be necessary to that there are data from good superiority trials consistent evidence that the comparator is an effective treatment with and establishing the size of its effect relative to no treatment. There should also be a basis for that the same degree of efficacy would be in the trial. For example, the patient and the endpoints should be similar. These issues are covered in ICH in the results provided by the confidence interval supply a concrete assessment of the precision actually by a clinical trial, superseding any calculations of power carried out before the trial was undertaken. The position of the lower end of the confidence interval relative to the of noninferiority provides the for noninferiority. In a superiority trial the full analysis set, based on the ITT (intention-to-treat) principle, is the analysis set of choice, with appropriate support provided by the PP (per protocol) analysis set. In a noninferiority trial the full analysis set and the PP analysis set have equal importance and their use should lead to similar conclusions for a robust interpretation. A switch of objective would require this difference of emphasis to be recognized. More details of the relative importance of these two analysis sets in superiority and noninferiority trials can be found in the ICH E9 Note for Guidance. A trial to show equivalence or noninferiority must show a high degree of consistency with protocolled plans if it is to be reliable. Deviations from the inclusion criteria, from the intended treatment regimen, from the schedule, manner and precision of taking measurements, and so on, all tend to reduce the sensitivity of a trial and to make a conclusion of âno differenceâ more likely, even when the deviations are of an unsystematic or random nature. The size of the bias associated with these and other departures from the protocol is generally unknown and may render such a trial uninterpretable. Failure to show a difference between two treatments can also arise when both treatments are inefficacious, perhaps as a result of being inappropriately administered. This problem does not affect superiority trials to the same extent because the demonstration of a difference is itself validation of the sensitivity of the trial. For these reasons, switching from superiority to noninferiority is likely to carry with it a lesser degree of confidence in the It will be necessary to to the sensitivity of the trial by or that the control treatment is its efficacy the trial with trials which demonstrated the efficacy of the control agent in of and of of and data that are at to those in the trials similar results from the full analysis set and PP analysis set. Switching the objective of a trial from superiority to noninferiority may be feasible provided: The noninferiority margin with respect to the control treatment was predefined or can be (The latter is likely to difficult and to be to cases where there is a accepted value for Analysis according to the intention-to-treat principle and PP confidence intervals and P values for the null hypothesis of similar The trial was properly designed and carried out in accordance with the strict requirements of a noninferiority trial (see ICH E9 and The sensitivity of the trial is high to ensure that it is of relevant differences if they There is or evidence that the control treatment is its level of A further related that has arisen in with equivalence and noninferiority trials to the equivalence margins when the trial is complete. that a bioequivalence trial a 90% confidence interval for the relative bioavailability of a new that from to we only that the relative bioavailability lies between the conventional of and because these the predefined equivalence can we that it lies between and The interval based on the data is the appropriate one to Hence, if the changed to this study would have satisfactory There is no question of a selection However, if the trial in a confidence interval from to then a change of equivalence margins to would not be acceptable because of the conclusion that the equivalence margin was chosen to the These apply to the 95% confidence intervals used for clinical equivalence and for noninferiority. The confidence interval based on the results of the trial is always the best summary of the It is the choice of equivalence margin that is subject to This should be chosen on the basis of and not chosen to the This Points to has been from the perspective of an efficacy trial active with a single primary variable. In practice some studies have more than one primary and most studies have respect to switching of these requires separate in the of the specific drug development, separate conclusions superiority or noninferiority for in judgement whether the trial as a has established the superiority or noninferiority of the new treatment will upon the requirements for that clinical and the of results all relevant The covered in these Points to can also be applied to specific safety when these have been as endpoints of a trial to compare active In practice the of switching objectives is not relevant to trials, even where noninferiority to is a valuable i.e. for safety The problem of switching objectives can be by a trial in the that both noninferiority and superiority are of value. In this case all the issues in this document should be addressed In the statistical analysis should be using an appropriate from noninferiority to superiority. The interpretation of superiority trials as noninferiority trials and vice is best by the results as a confidence interval for the difference between the test treatment and control. There is no problem associated with the use of this confidence interval as a basis for of interpretation. For a and trial, there are difficulties with the change from noninferiority to superiority that cannot be addressed by appropriate analysis. However, there are more difficulties associated with the switch from superiority to noninferiority because of the possible need to a basis and on, a margin of equivalence after the and because of the difficulties of noninferiority trials. There are for the design of a superiority trial in which noninferiority might be an acceptable When the results with respect to alternative of the equivalence margins the problem from to switch to wider acceptable that equivalence margins may be in this
Open access
Statistical Methods in Clinical Trials
Health Systems, Economic Evaluations, Quality of Life
In the early 1970s physicians engaged in fierce debates over the most appropriate method of evaluating the efficacy of coronary artery bypass grafting (CABG). With millions of patients and billions of dollars at stake, CABG sparked fierce controversy. Skeptics demanded that randomized controlled trials (RCTs) be performed, while enthusiasts argued that they already had visual proof of CABG's efficacy. When RCTs appeared, they did not settle the controversy. Participants simply reasserted their preconceptions, defending a trial's strengths or exploiting its flaws. The debate centered on standards of knowledge for the evaluation of therapeutic efficacy. Specifically, cardiologists and cardiac surgeons struggled to assess the relevance of different measures of therapeutic success: physiological or clinical, visual or statistical. Many factors contributed to participants' decisions, including disciplinary affiliation, traditions of research, personal experience with angiography, and assessments of the history of cardiac therapeutics. Physicians had to decide whether angiography provided a meaningful representation of the disease and its treatment or whether demonstrations of therapeutic success could come only from long-term statistical evaluation of mortality data.
Open access
Health and Medical Research Impacts
Health Systems, Economic Evaluations, Quality of Life
Kalevi Lauslahti, Risto P. Roine, Virpi Semberg, Martti KekomÀki · 6 authors
Finland has a long tradition of supporting social programs that promote equality and the welfare state. The healthcare system is financed mainly by taxation. Everyone is insured against illness. Each of Finland's five provinces is run by a provincial government that monitors the provision of social welfare and health care. However, the municipalities actually provide the services and regulate medical equipment and regionalization of services. During the early 1990s, gross domestic product (GDP) fell dramatically, and healthcare expenditure rose to 9.4% of GDP. Due to the economy's rapid recovery, the share of healthcare expenditure has again decreased and now matches the average level of OECD countries of approximately 7.7%. The former Finnish method of central planning and norm setting has guaranteed a fairly uniform development of necessary services throughout the country and free or low-cost access. Tight central planning did not, however, create incentives to contain costs. Therefore, in the beginning of the 1990s, decision-making power was largely decentralized to the municipalities, and the principles of state subsidies were reformed. In 1995, the Finnish Office for Health Care Technology Assessment (FinOHTA) was set up as a new unit of the National Research and Development Centre for Welfare and Health (STAKES). FinOHTA is intended to function as a national central body for advancing HTA-related work in Finland, with the ultimate goal of promoting the effectiveness and efficiency of Finnish health care. At present, the importance of HTA is widely recognized in Finland, especially in the face of rising healthcare costs.
Health Systems, Economic Evaluations, Quality of Life
The Austrian healthcare system relies mainly on physicians in private practice and on various services provided by hospitals. The social health insurance scheme is compulsory, covering 99% of the population. The system is very decentralized. While the federal state provides the framework, the nine autonomous provinces are responsible for administering health and social services. There is ongoing public discussion about centralizing the healthcare system to make it more efficient and to enforce structural reforms. Because of concerns about healthcare expenditures, in 1997 the Performance-Related Hospital Financing System (LKF), a system similar to the diagnosis-related group system, was introduced for hospitals, including a plan for large medical devices. It is too early to evaluate the success of this new system, although some effects of the LKF system that could have been anticipated, such as shortened lengths of stay and more hospitalizations, have been seen. Previously, health technologies have been almost uncontrolled in Austria. The evaluation of health technologies as an instrument to support or to control their dissemination and use or to help define policies is not institutionalized or systematically used. It seems clear that structural reforms of the Austrian healthcare system are needed. Health technology assessment should be part of such reforms.
Health Systems, Economic Evaluations, Quality of Life
Italy has a national health service (SSN) dating to 1978. Italy's system of government is characterized by a rather high degree of decentralization of power, and the health system is likewise decentralized. Most of the responsibilities for health care have been ceded to the regions. The state retains only limited coordinating and supervisory powers. The state has a financial responsibility for the national health service, but state contributions are limited and expenditures in excess of this made by the region must be financed from other sources. Health reforms of 1992-93 aimed at making the regions more sensitive to the need to control aggregate expenditure and to monitor measures to promote efficiency, quality, and citizen-patient satisfaction. The diffusion of individual health technologies has been relatively uncontrolled in many regions in Italy, although tight central constraints on capital spending have contained diffusion of new technology. Regulation of placement of services is a planning function and is the responsibility of both the Ministry of Health and the regions. Health technology assessment (HTA) activities have been expanding since the early 1990s, but these activities tend to be untargeted, uncoordinated, and without priorities. Nonetheless, the principal actors in the SSN at national, regional, and local levels are becoming more sensitive to the need to apply criteria of clinical and cost-effectiveness and to be more rigorous in deciding what services to guarantee. There are reasons to be guardedly optimistic about the future of HTA in Italy.
Health Systems, Economic Evaluations, Quality of Life
While Washington has been unable to lead the way in significant health care reform, the health care system has begun to transform itself in terms of curbing skyrocketing health care costs, dealing with the more than forty million Americans who lack health care coverage, and the problems plaguing the Medicare and Medicaid systems. The search has begun for a health care model that ensures quality care to a wide population in a cost-efficient manner. This article explores how the U.S. Health care system currently functions, examines several innovative models, and suggests ways in which a decentralized, community-based approach to health care reform can address our nationâs health care crisis. Specifically, Part I examines the current system of health care financing. Part II discusses current efforts to provide community based care. Part III offers suggestions for a community-based approach to health care reform, including ways to stimulate provider volunteerism, financing mechanisms, and methods to overcome potential legal barriers to local reform efforts.
Open access
Health Systems, Economic Evaluations, Quality of Life
Various ways of financing health care expenditures by communities are studied in this chapter. The first method is direct payments by patients for drugs. Application of this method presupposes that other health care expenditures are financed by other agents such as international donors and central, district or local government. A fee-for-service arrangement constitutes the second method. This is more general in that fees may cover other recurrent expenditures as well as drug expenditures. Salaries of health personnel and depreciation allowances may also be included in a fee-for service system. The third method consists of prepayments for health care or decentralized forms of health insurance. Finally, we consider community labour as a means of financing health expenditures. In the last section, evaluation criteria for projects in community financing are examined.
Healthcare Policy and Management
Pharmaceutical Economics and Policy
Health Systems, Economic Evaluations, Quality of Life
This article contends that the German social and economic situation is conductive to the rapid diffusion of innovative medical technology. While there is public control over hospital facilities, the pluralistic health care system and decentralized government responsibilities contribute to an essentially laissez faire regulatory environment. There is perfunctory planning and regulation for major medical expenditures, but the essential constraints are financial. This is no comprehensive program for the assessment of diagnostic technologies and the effective imposition of guidelines depends on the cooperative effort of various financing organizations, professional interests, and public pressure groups.
Health Systems, Economic Evaluations, Quality of Life
Stephen T. Miller, Roger Vander Zwagg, Melanie Joyner, John W. Runyan
Observations of a publicly-financed system for the medical care of a large number of persons with chronic diseases have been made over seven years. The system combines decentralized, nurse-staffed neighborhood clinics, operated by a public health department, with a central referral clinic for consultations and the management of complicated problems. After seven years in the chronic disease program 55% of 1,004 patients with diagnoses of diabetes mellitus, hypertension, and cardiac diseases were still receiving care, 19% had died, and 26% had been lost to the program. In the seventh year, the mean diastolic blood pressure in hypertensives was 84 mm Hg and the mean serum glucose in diabetics was 203 mg/dl. For the group under care, hospital days/1000/year were 74% of the rate during the year before referral to the program and out-patient visits/1000/year were approximately the same as before referral. However, two-thirds of the visits, formerly made to a public hospital, were now being made to neighborhood clinics. The system appears to be an effective method of providing medical services for persons who formerly used the public hospital as their source of outpatient care.
Open access
Primary Care and Health Outcomes
Chronic Disease Management Strategies
Health Systems, Economic Evaluations, Quality of Life