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Introduction: Drug reimbursement decisions are often made based on a price set by the manufacturer. In some cases, this price leads to public and scientific debates about whether its level can be justified in relation to its costs, including those related to research and development (R&D) and manufacturing. Such considerations could enter the decision process in collectively financed health care systems. This paper investigates whether manufacturers' costs in relation to drug prices, or profit margins, are explicitly mentioned and considered by health technology assessment (HTA) organisations. Method: An analysis of reimbursement reports for cancer drugs was performed. All relevant Dutch HTA-reports, published between 2017 and 2019, were selected and matched with HTA-reports from three other jurisdictions (England, Canada, Australia). Information was extracted. Additionally, reimbursement reports for three cases of expensive non-oncolytic orphan drugs prominent in pricing debates in the Netherlands were investigated in depth to examine consideration of profit margins. Results: A total of 66 HTA-reports concerning 15 cancer drugs were included. None of these reports contained information on manufacturer's costs or profit margins. Some reports contained general considerations of the HTA organisation which related prices to manufacturers' costs: six contained a statement on the lack of price setting transparency, one mentioned recouping R&D costs as a potential argument to justify a high price. For the case studies, 21 HTA-reports were selected. One contained a cost-based price justification provided by the manufacturer. None of the other reports contained information on manufacturer's costs or profit margins. Six reports contained a discussion about lack of transparency. Reports from two jurisdictions contained invitations to justify high prices by demonstrating high costs. Conclusion: Despite the attention given to manufacturers' costs in relation to price in public debates and in the literature, this issue does not seem to get explicit systematic consideration in the reimbursement reports of expensive drugs. [ABSTRACT FROM AUTHOR]

Background: The availability of increasingly advanced and expensive new health technologies puts considerable pressure on publicly financed healthcare systems. Decisions to not—or no longer—reimburse a health technology from public funding may become inevitable. Nonetheless, policymakers are often pressured to amend or revoke negative reimbursement decisions due to the public disagreement that typically follows such decisions. Public disagreement may be reinforced by the publication of pictures of individual patients in the media. Our aim was to assess the effect of depicting a patient affected by a negative reimbursement decision on public disagreement with the decision. Methods: We conducted a discrete choice experiment in a representative sample of the public (n = 1008) in the Netherlands and assessed the likelihood of respondents' disagreement with policymakers' decision to not reimburse a new pharmaceutical for one of two patient groups. We presented a picture of one of the patients affected by the decision for one patient group and "no picture available" for the other group. The groups were described on the basis of patients' age, health-related quality of life (HRQOL) and life expectancy (LE) before treatment, and HRQOL and LE gains from treatment. We applied random-intercept logit regression models to analyze the data. Results: Our results indicate that respondents were more likely to disagree with the negative reimbursement decision when a picture of an affected patient was presented. Consistent with findings from other empirical studies, respondents were also more likely to disagree with the decision when patients were relatively young, had high levels of HRQOL and LE before treatment, and large LE gains from treatment. Conclusions: This study provides evidence for the effect of depicting individual, affected patients on public disagreement with negative reimbursement decisions in healthcare. Policymakers would do well to be aware of this effect so that they can anticipate it and implement policies to mitigate associated risks. [ABSTRACT FROM AUTHOR]

Rationale, aims, and objectives: In recent years, several expensive new health technologies have been introduced. The availability of those technologies intensifies the discussion regarding the affordability of these technologies at different decision‐making levels. On the meso level, both hospitals and clinicians are facing budget constraints resulting in a tension to balance between different patients' interests. As such, it is crucial to make optimal use of the available resources. Different strategies are in place to deal with this problem, but decisions on a macro level on what to fund or not can limit the role and freedom of clinicians in their decisions on a micro level. At the same time, without central guidance regarding such decisions, micro level decisions may lead to inequities and undesirable treatment variation between clinicians and hospitals. The challenge is to find instruments that can balance both levels of decision making. Discussion Clinicians are becoming increasingly aware that their decisions to spend more resources (like time and budget) on 1 particular patient group reduce the resources available to other patients. Involving clinicians in thinking about the optimal use of limited resources, also in an attempt to bridge the world of economic reasoning and clinical practice, is crucial therefore. We argue that clinical guidelines may prove a clear vehicle for this by including both clinical and economic evidence to support the recommendations made. The development of such guidelines requires cooperation of clinicians, and health economists are cooperating with each other. Conclusion: The development of clinical guidelines which combine economic and clinical evidence should be stimulated, to balance central guidance and uniformity while maintaining necessary decentralized freedom. This is an opportunity to combine the reality of budgets and opportunity costs with clinical practice. Missing this opportunity risks either variation and inequity or central and necessarily crude measures. [ABSTRACT FROM AUTHOR]

The authors reflect on the national guidelines for economic evaluations in healthcare issued by the Dutch National Health Care Institute in 2016. Topics include the societal costs and benefits outside the healthcare sector to be included in the analysis, the inclusion of unrelated indirect medical costs in life-years gained and the stronger and clearer guidance for evaluation of long-term care.

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. [ABSTRACT FROM AUTHOR]

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-3 L 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. [ABSTRACT FROM AUTHOR]

Background: When national pharmacoeconomic guidelines are compared, different recommendations are identified on how to identify, measure and value lost productivity, leading to difficulties when comparing lost productivity estimates across countries. From a transferability point of view, the question arises of whether differences between countries regarding lost productivity are the result of using different calculation methods (methodological differences) or of other between-country differences. When lost productivity data differ significantly across countries, the transferability of lost productivity data across countries is hindered. Objective: The objective of this study was to investigate whether country of residence has a significant influence on the quantity of lost productivity among patients with rheumatic disorders. Confounding factors that might differ between countries were corrected for, while the methodology used to identify and measure lost productivity was kept the same. Methods: This question was investigated by means of an online questionnaire filled out by 200 respondents with a rheumatic disorder per country in four European countries, namely the Netherlands, the UK, Germany and France. In addition to those regarding lost productivity, the questionnaire contained questions about patient characteristics, disability insurance, disease characteristics, quality of life and job characteristics as these variables are expected to influence lost productivity in terms of absenteeism and presenteeism. The data were analysed by regression analyses, in which different components - being absent in last 3 months, number of days absent and presenteeism - of lost productivity were the main outcome measures and other variables, such as gender, impact of disease, shift work, job control, partial disability and overall general health, were corrected for. Results: The results showed that country sometimes has a significant influence on lost productivity and that other variables such as, for example, age, disease severity, number of contract hours, decision latitude, experienced health (as reported on the visual analogue scale) and partial disability, also influence lost productivity.A significant influence of country of residence was found on the variables 'being absent in the last three months', 'number of days absent' and 'quality of work on the last working day'. However, country did not influence 'quantity of work on the last working day' and 'overall presenteeism on the last working day'. Conclusion: It can be concluded that country has a significant influence on lost productivity among patients with rheumatic disorders, when corrected for other variables that have an influence on absenteeism and presenteeism. Transferring lost productivity data across countries without adaptation is hindered by the significant differences between countries in this patient group. As a result, transferring lost productivity data, being either monetary values or volumes of productivity losses, between countries can give wrong estimations of the cost effectiveness of treatments. [ABSTRACT FROM AUTHOR]

For at least two decades, there has been an intense debate on whether and how to include the value of lost productivity in economic evaluations. This debate is often reflected in pharmacoeconomic guidelines, which have been developed to indicate the methods and requirements for the design, execution, and reporting of economic evaluations in a particular country. Objective: To examine what various national pharmacoeconomic guidelines recommend regarding the identification, measurement, and valuation of lost productivity. Methods: First, the theoretical framework on how lost productivity can be identified, measured, and valued is described. Second, a summary sheet has been used to identify various pharmacoeconomic guidelines recommendations regarding the value of lost productivity. Results: Twenty-two of the 30 guidelines identified recommend performing economic evaluations using the societal perspective. Nevertheless, even if the societal perspective is recommended, it is not always clear how the value of lost productivity should be taken into account. Most guidelines recommend including the costs of absenteeism from paid and/or unpaid work. In addition, although no agreement exists on how lost productivity should be valued, none of the guidelines recommended using the US panel approach for the valuation of lost productivity. Discussion: The different recommendations hinder international transferability of the value of lost productivity. This difficulty is mainly caused by different recommendations regarding identification and valuation. These differences result from the debate and lack of consensus on including the value of lost productivity losses in economic evaluations. It will become easier to transfer data across jurisdictions if all data are reported transparently. [ABSTRACT FROM AUTHOR]

Background: Within the framework of economic evaluations, the transferability of utility scores between jurisdictions remains unclear. The EQ-5D is a generic instrument for measuring health-related quality of life in economic evaluations, which can be used for comparing utility scores across countries. At present, the EQ-5D has several national value sets or tariffs. Nevertheless, utility estimates from foreign studies are often used directly for cost-effectiveness estimates, without adapting by applying the appropriate national value set. It is unclear if this practice is advisable, due to dissimilarities between the national value sets. Objective: To examine the effects of differences in national EQ-5D value sets on absolute and marginal utilities of health states, and determine to what degree these differences can be explained by methodological factors. Methods: First, the relative importance of the EQ-5D domains for the utility estimates was compared across the 15 value sets. Second, two hypothetical health states for a depressed patient and a pain patient (21232 and 33321) were selected for additional analysis, by comparing the utilities as scored by the value sets. The marginal influence of a one-level deterioration in a domain of these health states on the utility estimate was then determined. Third, the differences between the value sets were examined in more detail by using multilevel analysis to examine the role of methodological differences in the valuation studies. Results: Differences can be perceived between the national value sets of the EQ-5D in the preferences for the domains. The utilities of the two hypothetical health states show that the value sets differ substantially. Furthermore, the differences between the marginal values of the deteriorations are large, which can be explained partly by the type of valuation method. Other methodological differences also influence the value sets. Conclusion: All results indicate that the differences between the EQ-5D value sets are considerable and should not be ignored. The differences can largely be explained by methodological differences in the valuation studies. The remaining differences may reflect cultural dissimilarities between countries. Therefore, further research should focus on investigating the transferability of utilities across countries or agreeing on a standard to perform valuation studies. For the time being, transferring utilities from one country to another without any adjustment is not advisable. [ABSTRACT FROM AUTHOR]

Objective: One of the existing methods to assess the transferability of economic evaluations is the model of Welte, which is a decision-chart method that includes general and specific knockout criteria and a transferability checklist. This study aims to test Welte's model with the help of a case study. Methods: In this study, foreign studies were transferred to The Netherlands and then compared with a Dutch reference study. In the case study, the cost-effectiveness of physiotherapy was compared with a multidisciplinary treatment. With the help of a systematic search, several foreign studies could be identified. Based on these foreign studies, two different predictions were produced for The Netherlands. In the “all studies prediction,” all foreign studies were used. In the “Welte's model prediction,” only the foreign studies were used, which passed the general and specific knockout criteria. Both predictions were compared with the Dutch reference case. Results: A total of 14 non-Dutch studies were identified. Seven studies did not pass the general knockout criteria and one study did not pass the specific knockout criteria. As a result, 14 studies were included in the “all studies prediction” and 6 studies in the “Welte's model prediction.” The predictions yielded different results and the “Welte's model prediction” proved better on costs than the “all studies prediction.” Discussion: The application of Welte's model does influence cost and effects estimates when transferring economic data between countries. However, more cases should be subjected to the Welte transferability model before a final conclusion can be drawn. [ABSTRACT FROM AUTHOR]

Background: The current use of health economic decision models in HTA is mostly confined to single use cases, which may be inefficient and result in little consistency over different treatment comparisons, and consequently inconsistent health policy decisions, for the same disorder. Multi-use disease models (MUDMs) (other terms: generic models, whole disease models, disease models) may offer a solution. However, much is uncertain about their definition and application. The current research aimed to develop a blueprint for the application of MUDMs. Methods: We elicited expert opinion using a two-round modified Delphi process. The panel consisted of experts and stakeholders in health economic modelling from various professional backgrounds. The first questionnaire concerned definition, terminology, potential applications, issues and recommendations for MUDMs and was based on an exploratory scoping review. In the second round, the panel members were asked to reconsider their input, based on feedback regarding first-round results, and to score issues and recommendations for priority. Finally, adding input from external advisors and policy makers in a structured way, an overview of issues and challenges was developed during two team consensus meetings. Results: In total, 54 respondents contributed to the panel results. The term 'multi-use disease models' was proposed and agreed upon, and a definition was provided. The panel prioritized 10 potential applications (with comparing alternative policies and supporting resource allocation decisions as the top 2), while 20 issues (with model transparency and stakeholders' roles as the top 2) were identified as challenges. Opinions on potential features concerning operationalization of multi-use models were given, with 11 of these subsequently receiving high priority scores (regular updates and revalidation after updates were the top 2). Conclusions: MUDMs would improve on current decision support regarding cost-effectiveness information. Given feasibility challenges, this would be most relevant for diseases with multiple treatments, large burden of disease and requiring more complex models. The current overview offers policy makers a starting point to organize the development, use, and maintenance of MUDMs and to support choices concerning which diseases and policy decisions they will be helpful for. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to investigate whether the profit margins of pharmaceuticals would influence the outcome of reimbursement decisions within the Dutch policy context.Methods: We conducted a discrete choice experiment among 58 Dutch decision makers. In 20 choice sets, we asked respondents to indicate which of 2 pharmaceutical treatment options they would select for reimbursement. Options were described using 5 attributes (disease severity, incremental costs per quality-adjusted life-year, health gain, budget impact, and profit margin) with 3 levels each. Additionally, cognitive debriefing questions were presented, and for validation debriefing, interviews were conducted. Choice data were analyzed using mixed logit models, also to calculate marginal effects and choice probabilities.Results: Results indicated that the specified levels of profit margins significantly influenced choices made. Decision makers were less likely to reimburse a product with a higher profit margin. The relative importance of profit margins was lower than that of the included traditional health technology assessment criteria, but not negligible. When asked directly, 61% of respondents indicated that profit margin should play a role in reimbursement decision making, although concerns about feasibility and the connection to price negotiations were voiced.Conclusions: Our results suggest that if available to decision makers the profit margin of pharmaceutical products would influence reimbursement decisions within the Dutch policy context. Higher profit margins would reduce the likelihood of reimbursement. Whether adding profit margin as an additional, explicit criterion to the health technology assessment decision framework would be feasible and desirable is open to further exploration. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Healthcare resource allocation decisions made under conditions of uncertainty may turn out to be suboptimal. In a resource constrained system in which there is a fixed budget, these suboptimal decisions will result in health loss. Consequently, there may be value in reducing uncertainty, through the collection of new evidence, to make better resource allocation decisions. This value can be quantified using a value of information (VOI) analysis. This report, from the ISPOR VOI Task Force, introduces VOI analysis, defines key concepts and terminology, and outlines the role of VOI for supporting decision making, including the steps involved in undertaking and interpreting VOI analyses. The report is specifically aimed at those tasked with making decisions about the adoption of healthcare or the funding of healthcare research. The report provides a number of recommendations for good practice when planning, undertaking, or reviewing the results of VOI analyses. [ABSTRACT FROM AUTHOR]

Objective: Sodium–glucose cotransporter 2 inhibitors (SGLT2i) have been shown to reduce the risk of cardiovascular complications, which largely drive diabetes' health and economic burdens. Trial results indicated that SGLT2i are cost effective. However, these findings may not be generalizable to the real-world target population. This study aims to evaluate the cost effectiveness of SGLT2i in a routine care type 2 diabetes population that meets Dutch reimbursement criteria using the MICADO model. Methods: Individuals from the Hoorn Diabetes Care System cohort (N = 15,392) were filtered to satisfy trial inclusion criteria (including EMPA-REG, CANVAS, and DECLARE-TIMI58) or satisfy the current Dutch reimbursement criteria for SGLT2i. We validated a health economic model (MICADO) by comparing simulated and observed outcomes regarding the relative risks of events in the intervention and comparator arm from three trials, and used the validated model to evaluate the long-term health outcomes using the filtered cohorts' baseline characteristics and treatment effects from trials and a review of observational studies. The incremental cost-effectiveness ratio (ICER) of SGLT2i, compared with care-as-usual, was assessed from a third-party payer perspective, measured in euros (2021 price level), using a discount rate of 4% for costs and 1.5% for effects. Results: From Dutch individuals with diabetes in routine care, 15.8% qualify for the current Dutch reimbursement criteria for SGLT2i. Their characteristics were significantly different (lower HbA1c, higher age, and generally more preexisting complications) than trial populations. After validating the MICADO model, we found that lifetime ICERs of SGLT2i, when compared with usual care, were favorable (< €20,000/QALY) for all filtered cohorts, resulting in an ICER of €5440/QALY using trial-based treatment effect estimates in reimbursed population. Several pragmatic scenarios were tested, the ICERs remained favorable. Conclusions: Although the Dutch reimbursement indications led to a target group that deviates from trial populations, SGLT2i are likely to be cost effective when compared with usual care. [ABSTRACT FROM AUTHOR]

Background: When proven effective, decision making regarding reimbursement of new health technology typically involves ethical, social, legal, and health economic aspects and constraints. Nevertheless, when applying standard value of information (VOI) analysis, the value of collecting additional evidence is typically estimated assuming that only cost-effectiveness outcomes guide such decisions.Objectives: To illustrate how decision makers' constraints can be incorporated into VOI analyses and how these may influence VOI outcomes.Methods: A simulation study was performed to estimate the cost-effectiveness of a new hypothetical technology compared with usual care. Constraints were defined for the new technology on 1) the maximum acceptable rate of complications and 2) the maximum acceptable additional budget. The expected value of perfect information (EVPI) for the new technology was estimated in various scenarios, both with and without incorporating these constraints.Results: For a willingness-to-pay threshold of €20,000 per quality-adjusted life-year, the probability that the new technology was cost-effective equaled 57%, with an EVPI of €1868 per patient. Applying the complication rate constraint reduced the EVPI to €1137. Similarly, the EVPI reduced to €770 when applying the budget constraint. Applying both constraints simultaneously further reduced the EVPI to €318.Conclusions: When decision makers explicitly apply additional constraints, beyond a willingness-to-pay threshold, to reimbursement decisions, these constraints can and should be incorporated into VOI analysis as well, because they may influence VOI outcomes. This requires continuous interaction between VOI analysts and decision makers and is expected to improve both the relevance and the acceptance of VOI outcomes. [ABSTRACT FROM AUTHOR]

Introduction: To make efficient use of available resources, decision-makers in healthcare may assess the costs and (health) benefits of health interventions. For interventions aimed at improving mental health capturing the full health benefits is an important challenge. The Mental Health Quality of Life (MHQoL) instrument was recently developed to meet this challenge. Evaluating the pyschometric properties of this instrument in different contexts remains important.Methods: A psychometric evaluation of the MHQoL was performed using existing international, cross-sectional data with 7155 respondents from seven European countries (Denmark, France, Germany, Italy, Portugal, The Netherlands, Portugal and the United Kingdom). Reliability was examined by calculating Cronbach's alpha, a measure of internal consistency of the seven MHQoL dimensions, and by examining the association of the MHQoL sum scores with the MHQoL-VAS scores. Construct validity was examined by calculating Spearman's rank correlation coefficients between the MHQoL sum scores and EQ-5D index scores, EQ-VAS scores, EQ-5D anxiety/depression dimension scores, ICECAP-A index scores and PHQ-4 sum scores.Results: The MHQoL was found to have good internal consistency for all seven countries. The MHQoL sum score and the MHQoL-VAS had a high correlation. Spearman's rank correlation coefficients were moderate to very high for all outcomes.Conclusion: Our results, based on data gathered in seven European countries, suggest that the MHQoL shows favourable psychometrical characteristics. While further validation remains important, the MHQoL may be a useful instrument in measuring mental health-related quality of life in the Western European context. [ABSTRACT FROM AUTHOR]

This is exactly what we advocate in our paper: a broad range of possible estimates is provided through the use of intermediate steps between the set minimum and maximum values [[3]].This is especially relevant in those cases where probability distributions are not known, given that in those cases, the extreme values are most likely not known either (or they are at least very uncertain). Note that this is also in line with the lifecycle dynamics that the author speaks of; a stepwise DSA shows alternative scenarios for minimum and maximum values that decision-makers may need to consider. If minimum and maximum values are arbitrary and/or uncertain, it is very helpful for decision-makers to know the outcomes of their decision models under alternative minimum and maximum scenarios. [Extracted from the article]

The aim of this letter to the editor is to provide a comprehensive summary of uncertainty assessment in Health Technology Assessment, with a focus on transferability to the setting of rare diseases. The authors of "TRUST4RD: tool for reducing uncertainties in the evidence generation for specialised treatments for rare diseases" presented recommendations for reducing uncertainty in rare diseases. Their article is of great importance but unfortunately suffers from a lack of references to the wider uncertainty in Health Technology Assessment and research prioritisation literature and consequently fails to provide a trusted framework for decision-making in rare diseases. In this letter to the editor we critique the authors' tool and provide pointers as to how their proposal can be strengthened. We present references to the literature, including our own tool for uncertainty assessment (TRUST; unrelated to the authors' research), and provide a broader perspective on uncertainty and risk management in rare diseases, including a detailed research agenda. [ABSTRACT FROM AUTHOR]

The aim of this letter to the editor is to provide a comprehensive summary of uncertainty assessment in Health Technology Assessment, with a focus on transferability to the setting of rare diseases. The authors of "TRUST4RD: tool for reducing uncertainties in the evidence generation for specialised treatments for rare diseases" presented recommendations for reducing uncertainty in rare diseases. Their article is of great importance but unfortunately suffers from a lack of references to the wider uncertainty in Health Technology Assessment and research prioritisation literature and consequently fails to provide a trusted framework for decision-making in rare diseases. In this letter to the editor we critique the authors' tool and provide pointers as to how their proposal can be strengthened. We present references to the literature, including our own tool for uncertainty assessment (TRUST; unrelated to the authors' research), apply TRUST to two assessments of orphan drugs in rare diseases and provide a broader perspective on uncertainty and risk management in rare diseases, including a detailed research agenda. [ABSTRACT FROM AUTHOR]

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 identified, 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 effectiveness 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 identification 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 effectiveness 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 identification, assessment, and reporting of uncertainties in health economic models and may contribute to more informed and transparent decision making in the face of uncertainty. [ABSTRACT FROM AUTHOR]

Background: Value of information (VOI) is a tool that can be used to inform decisions concerning additional research in healthcare. VOI estimates the value of obtaining additional information and indicates the optimal design for additional research. Although it is recognized as good practice in handling uncertainty, it is still hardly used in decision making in the Netherlands.Objective: This paper aims to examine the potential value of VOI, barriers and facilitators and the way forward with the use of VOI in the decision-making process for reimbursement of pharmaceuticals in the Netherlands.Methods: Three focus group interviews were conducted with researchers, policy makers, and representatives of pharmaceutical companies.Results: The results revealed that although all stakeholders recognize the relevance of VOI, it is hardly used and many barriers to the performance and use of VOI were identified. One of these barriers is that not all uncertainties are easily incorporated in VOI, and the results may be biased if structural uncertainties are ignored. Furthermore, not all research designs indicated by VOI may be feasible in practice.Conclusions: To fully embed VOI into current decision-making processes, a threshold incremental cost-effectiveness ratio and guidelines that clarify when and how VOI should be performed are needed. In addition, it should be clear to all stakeholders how the results of VOI are used in decision making. [ABSTRACT FROM AUTHOR]

Background: When national pharmacoeconomic guidelines are compared, different recommendations are identified on how to identify, measure and value lost productivity, leading to difficulties when comparing lost productivity estimates across countries. From a transferability point of view, the question arises of whether differences between countries regarding lost productivity are the result of using different calculation methods (methodological differences) or of other between-country differences. When lost productivity data differ significantly across countries, the transferability of lost productivity data across countries is hindered.Objective: The objective of this study was to investigate whether country of residence has a significant influence on the quantity of lost productivity among patients with rheumatic disorders. Confounding factors that might differ between countries were corrected for, while the methodology used to identify and measure lost productivity was kept the same.Methods: This question was investigated by means of an online questionnaire filled out by 200 respondents with a rheumatic disorder per country in four European countries, namely the Netherlands, the UK, Germany and France. In addition to those regarding lost productivity, the questionnaire contained questions about patient characteristics, disability insurance, disease characteristics, quality of life and job characteristics as these variables are expected to influence lost productivity in terms of absenteeism and presenteeism. The data were analysed by regression analyses, in which different components - being absent in last 3 months, number of days absent and presenteeism - of lost productivity were the main outcome measures and other variables, such as gender, impact of disease, shift work, job control, partial disability and overall general health, were corrected for.Results: The results showed that country sometimes has a significant influence on lost productivity and that other variables such as, for example, age, disease severity, number of contract hours, decision latitude, experienced health (as reported on the visual analogue scale) and partial disability, also influence lost productivity. A significant influence of country of residence was found on the variables 'being absent in the last three months', 'number of days absent' and 'quality of work on the last working day'. However, country did not influence 'quantity of work on the last working day' and 'overall presenteeism on the last working day'.Conclusion: It can be concluded that country has a significant influence on lost productivity among patients with rheumatic disorders, when corrected for other variables that have an influence on absenteeism and presenteeism. Transferring lost productivity data across countries without adaptation is hindered by the significant differences between countries in this patient group. As a result, transferring lost productivity data, being either monetary values or volumes of productivity losses, between countries can give wrong estimations of the cost effectiveness of treatments. [ABSTRACT FROM AUTHOR]

The original article can be found online at https://doi.org/10.1186/s13023-020-01666-4. Building a trusted framework for uncertainty assessment in rare diseases: suggestions for improvement (Response to "TRUST4RD: tool for reducing uncertainties in the evidence generation for specialised treatments for rare diseases"). [Extracted from the article]