Do the Washington Panel recommendations hold for europe inversigating the relation between quality of life versus work-status, absenteeism and presenteeism

__Abstract__ Background: The question of how to value lost productivity in economic evaluations has been subject of debate in the past twenty years. According to the Washington panel, lost productivity influences health-related quality of life and should thus be considered a health effect instead of a cost to avoid double counting. Current empirical evidence on the inclusion of income loss when valuing health states is not decisive. We examined the relationship between three aspects of lost productivity (work-status, absenteeism and presenteeism) and patient or social valuation of health-related quality of life (HRQoL). Methods: Cross-sectional survey data were collected from a total of 830 respondents with a rheumatic disorder from four West-European countries. Health-related quality of life was expressed in either the European societal utility using EQ-5D-3L or the patient valuation using EQ-VAS. The impact of work-status (four categories), absenteeism (absent from paid work during the past three months), and presenteeism (QQ method) on EQ-5D utilities and VAS scores was examined in linear regression analyses taking into account demographic characteristics and disease severity (duration, pain and restriction). Results: The relationship between work-status, absenteeism or presenteeism and HRQoL was stronger for patient valuation than societal valuation. Compared to work-status and presenteeism the relationship between absenteeism and HRQoL was even less explicit. However, results for all measures of lost productivity are only marginally significant and negligible compared to the influence of disease-related restrictions. Conclusions: This survey study in patients with a rheumatic disorder in four European countries, does not fully support the Washington panel’s claim that lost productivity is a significantly related with HRQoL, and this is even more apparent for absenteeism than for work-status and presenteeism. For West-European countries, there is no reason, to include absenteeism in the QALY. Findings need to be confirmed in other disease areas

From Good to Better: New Dutch Guidelines for Economic Evaluations in Healthcare

Many countries have national guidelines for performing economic evaluations in healthcare.1 These guidelines should ensure the comparability and quality of such evaluations, which should facilitate making well informed policy decisions regarding reimbursement of interventions. Given the developments in both the methodology and policy context of economic evaluation of healthcare interventions, these guidelines require periodical revision. Recently, the Dutch National Health Care Institute issued new guidance for economic evaluations in healthcare [1]. The new guidelines update and replace three separately published previous guidelines: those for pharmacoeconomic evaluation (latest version 2006), outcomes research (latest version 2008) as well as the Dutch costing manual (latest version 2010). In this editorial, we highlight the distinguishing features of the new Dutch guidelines. Moreover, we highlight which developments, in our opinion, are desirable in coming updates, but are still in development or controversial

REVIEWING TRANSFERABILITY in ECONOMIC EVALUATIONS ORIGINATING from EASTERN EUROPE

__Objectives:__ The aim of this study is to analyze the quality and transferability issues reported in published peer-reviewed English-language economic evaluations based in healthcare settings of the Central and Eastern European (CEE) and former Soviet countries. __Methods:__ A systematic search of economic evaluations of healthcare interventions was performed for Armenia, Azerbaijan, Belarus, Bulgaria, Estonia, Georgia, Turkmenistan, Kazakhstan, Lithuania, the former Yugoslav Republic of Macedonia, Republic of Moldova, Romania, the Russian Federation, Serbia, Slovenia, and Ukraine. The included studies were assessed according to their characteristics, quality (using Drummond’s checklist), use of local data, and the transferability of inputs and results, if addressed. __Results:__ Most of the thirty-four economic evaluations identified were conducted from a healthcare or payer perspective (74 percent), with 47 percent of studies focusing on infectious diseases. The least frequently and transparently addressed parameters were the items’ stated perspectives, relevant costs included, accurately measured costs in appropriate units, outcomes and costs credibly valued, and uncertainties addressed. Local data were often used to assess unit costs, baseline risk, and resource usage, while jurisdiction-specific utilities were included in only one study. Only 32 percent of relevant studies discussed the limitations of using foreign data, and 36 percent of studies discussed the transferability of their own study results to other jurisdictions. __Conclusions:__ Transferability of the results is not sufficiently discussed in published economic evaluations. To simplify the transferability of studies to other jurisdictions, the following should be comprehensively addressed: uncertainty, impact of influential parameters, and data transferability. The transparency of reporting should be improved

Cost-effectiveness of adding rituximab to fludarabine and cyclophosphamide for treatment of chronic lymphocytic leukemia in Ukraine

The aim of this study was to assess the cost-effectiveness, from a health care perspective, of adding rituximab to fludarabine and cyclophosphamide scheme (FCR versus FC) for treatment-naïve and refractory/relapsed Ukrainian patients with chronic lymphocytic leukemia. A decision-analytic Markov cohort model with three health states and 1-month cycle time was developed and run within a life time horizon. Data from two multinational, prospective, open-label Phase 3 studies were used to assess patients’ survival. While utilities were generalized from UK data, local resource utilization and disease-associated treatment, hospitalization, and side effect costs were applied. The alternative scenario was performed to assess the impact of lower life expectancy of the general population in Ukraine on the incremental cost-effectiveness ratio (ICER) for treatment-naïve patients. One-way, two-way, and probabilistic sensitivity analyses were conducted to assess the robustness of the results. The ICER (in US dollars) of treating chronic lymphocytic leukemia patients with FCR versus FC is US$8,704 per quality-adjusted life year gained for treatment-naïve patients and US$11,056 for refractory/relapsed patients. When survival data were modified to the lower life expectancy of the general population in Ukraine, the ICER for treatment-naïve patients was higher than US$13,000. This value is higher than three times the current gross domestic product per capita in Ukraine. Sensitivity analyses have shown a high impact of rituximab costs and a moderate impact of differences in utilities on the ICER. Furthermore, probabilistic sensitivity analyses have shown that for refractory/relapsed patients the probability of FCR being cost-effective is higher than for treatment-naïve patients and is close to one if the threshold is higher than US$15,000. State coverage of rituximab treatment may be considered a cost-effective treatment for the Ukrainian population u

Cost comparison of treating chronic hepatitis C genotype one with pegylated interferons in Ukraine

Based on the pivotal trial showing no clinicallyrelevant differences between pegylated interferon α-2b (Peg-α-2b) and α-2a (Peg-α-2a) combined with ribavirin for treatment of chronic hepatitis C virus (HCV) genotype 1 infection in Ukraine, a cost-minimization analysis was performed using a 1 year time horizon and both a health care and patients' perspective. A decision tree reflects treatment pathways. Drug costs were based on drug labeling and adjusted to the average body mass in Ukraine. Subgroup analysis was applied to deal with heterogeneity of patient's weight causing dose changes. A break-even price of Peg-α-2a and Peg-α-2b (based on the average dose) was calculated. Univariate sensitivity analyses and probabilistic sensitivity analysis were carried out to reflect decision uncertainty. For an average body weight, total medical costs per patient differ from US$9220 for Peg-α-2b to US$9513 for Peg-α-2a from a health care perspective, and from US$15,212 to US$15,696 from a patients' perspective. Sensitivity analyses show these results are robust. With average body weight, the break-even price of Peg-α-2b may be 7.3% higher than Peg-α-2a to have similar total costs

Do economic evaluations of TAVI deal with learning effects, innovation, and context dependency? A review

Introduction: Most collectively funded healthcare systems set limits to their benefit package. Doing so require

Development and Validation of the TRansparent Uncertainty ASsessmenT (TRUST) Tool for Assessing Uncertainties in Health Economic Decision Models.

Background An increasing number of technologies are obtaining marketing authorisation based on sparse evidence, which causes growing uncertainty and risk within health technology reimbursement decision making. To ensure that uncertainty is considered and addressed within health technology assessment (HTA) recommendations, uncertainties need to be identifed, included in health economic models, and reported. Objective Our objective was to develop the TRansparent Uncertainty ASsessmenT (TRUST) tool for systematically identifying, assessing, and reporting uncertainties in decision models, with the aim of making uncertainties and their impact on cost efectiveness more explicit and transparent. Methods TRUST was developed by drawing on the uncertainty and risk assessment literature. To develop and validate this tool, we conducted HTA stakeholder discussion meetings and interviews and applied it in six real-world HTA case studies in the Netherlands and the UK. Results The TRUST tool enables the identifcation and categorisation of uncertainty according to its source (transparency issues, methodology issues, and issues with evidence: imprecision, bias and indirectness, and unavailability) in each model aspect. The source of uncertainty determines the appropriate analysis. The impact of uncertainties on cost efectiveness is also assessed. Stakeholders found using the tool to be feasible and of value for transparent uncertainty assessment. TRUST can be used during model development and/or model review. Conclusion The TRUST tool enables systematic identifcation, assessment, and reporting of uncertainties in health economic models and may contribute to more informed and transparent decision making in the face of uncertainty

The Application and Implications of Novel Deterministic Sensitivity Analysis Methods

Deterministic sensitivity analyses (DSA) remain important to interpret the effect of uncertainties in individual parameters on results of cost-effectiveness analyses. Classic DSA methodologies may lead to wrong conclusions due to a lack of or misleading information regarding marginal effects, non-linearity, likelihood and correlations. In addition, tornado diagrams are misleading in some situations. Recent advances in DSA methods have the potential to provide decision makers with more reliable information regarding the effects of uncertainties in individual parameters. This practical application discusses advances to classic DSA methods and their implications. Three methods are discussed: stepwise DSA, distributional DSA and probabilistic DSA. For each method, the technical specifications, options for presenting results, and its implications for decision making are discussed. Options for visualizing DSA results in incremental cost-effectiveness ratios and in incremental net benefits are presented. The use of stepwise DSA increases interpretability of marginal effects and non-linearities in the model, which is especially relevant when arbitrary ranges are implemented. Using the probability distribution of each parameter in distributional DSA provides insight on the likelihood of model outcomes while probabilistic DSA also includes the effects of correlations between parameters. Probabilistic DSA, preferably expressed in incremental net benefit, is the most appropriate method for providing insight on the effect of uncertainty in individual parameters on the estimate of cost effectiveness. However, the opportunities provided by probabilistic DSA may not always be needed for decision making. Other DSA methods, in particular distributional DSA, can sometimes be sufficient depending on model features. Decision makers must determine to which extent they will accept and implement these new and improved DSA methodologies and adjust guidelines accordingly