évaluation médico économique

Objective This paper reports on the valuation of the classification system for the Quality-of-Life Aged Care Consumers (QOL-ACC) instrument using a discrete choice experiment (DCE) with duration with a large sample of older people receiving aged care services. Methods A DCE with 160 choice sets of two quality-of-life state–survival duration combinations blocked into 20 survey versions, with eight choice sets in each version, was designed and administered through an on-line survey to older Australians receiving aged care services in home and via interviewer facilitation with older people in residential aged care settings. Model specifications investigating preferences with respect to survival duration and interactions between QOL-ACC dimension levels were estimated. Utility weights were developed, with estimated coefficients transformed to the 0 (being dead) to 1 (full health) scale to generate a value set suitable for application in quality assessment and for the calculation of quality-adjusted life-years for use in economic evaluation. Results In total, 953 older people completed the choice experiment with valid responses. The estimation results from econometric model specifications indicated that utility increased with survival duration and decreased according to quality-of-life impairment levels. An Australian value set (range − 0.56 to 1.00) was generated for the calculation of utilities for all QOL-ACC states. Conclusion The QOL-ACC is unique in its focus on measuring and valuing quality of life from the perspective of older people themselves, thereby ensuring that the preferences of aged care service users are the primary focus for quality assessment and economic evaluation.

Introduction Drugs for rare diseases (DRDs) offer important health benefits, but challenge traditional health technology assessment, reimbursement, and pricing processes due to limited effectiveness evidence. Recently, modified processes to address these challenges while improving patient access have been proposed in Canada. This review examined processes in 12 jurisdictions to develop recommendations for consideration during formal government-led multi-sectoral discussions currently taking place in Canada. Methods (i) A scoping review of DRD reimbursement processes, (ii) key informant interviews, (iii) a case study of evaluations for and the reimbursement status of a set of 7 DRDs, and (iv) a virtual, multi-stakeholder consultation retreat were conducted. Results Only NHS England has a process specifically for DRDs, while Italy, Scotland, and Australia have modified processes for eligible DRDs. Almost all consider economic evaluations, budget impact analyses, and patient-reported outcomes; but less than half accept surrogate measures. Disease severity, lack of alternatives, therapeutic value, quality of evidence, and value for money are factors used in all decision-making process; only NICE England uses a cost-effectiveness threshold. Budget impact is considered in all jurisdictions except Sweden. In Italy, France, Germany, Spain, and the United Kingdom, specific factors are considered for DRDs. However, in all jurisdictions opportunities for clinician/patient input are the same as those for other drugs. Of the 7 DRDs included in the case study, the number that received a positive reimbursement recommendation was highest in Germany and France, followed by Spain and Italy. No relationship between recommendation type and specific elements of the pricing and reimbursement process was found. Conclusions Based on the collective findings from all components of the project, seven recommendations for possible action in Canada are proposed. These focus on defining “appropriate access”, determining when a “full” HTA may not be needed, improving coordination among stakeholder groups, developing a Canadian framework for Managed Access Plans, creating a pan-Canadian DRD/rare disease data infrastructure, genuine and continued engagement of patient groups and clinicians, and further research on different decision and financing options, including MAPs.

Background and Objective Precision medicine highlights the importance of exploring heterogeneity in the effectiveness and costs of interventions. Our objective was to identify and compare frameworks for valuing heterogeneity-informed decisions, and consider their strengths and weaknesses for application to precision medicine. Methods We conducted a scoping review to identify papers that proposed an analytical framework to place a value, in terms of costs and health benefits, on using heterogeneity to inform treatment selection. The search included English-language papers indexed in MEDLINE, Embase or EconLit, and a manual review of references and citations. We compared the frameworks qualitatively considering: the purpose and setting of the analysis; the types of precision medicine interventions where the framework could be applied; and the framework’s ability to address the methodological challenges of evaluating precision medicine. Results Four analytical frameworks were identified: value of stratification, value of heterogeneity, expected value of individualised care and loss with respect to efficient diffusion. Each framework is suited to slightly different settings and research questions. All focus on maximising net benefit, and quantify the opportunity cost of ignoring heterogeneity by comparing individualised or stratified decisions to a means-based population-wide decision. Where the frameworks differ is in their approaches to uncertainty, and in the additional metrics they consider. Conclusions Identifying and utilising heterogeneity is at the core of precision medicine, and the ability to quantify the value of heterogeneity-informed decisions is critical. Using an analytical framework to value heterogeneity will help provide evidence to inform investment in precision medicine interventions, appropriately capturing the value of targeted health interventions.

Including health outcomes for carers as well as patients in economic evaluations can change the results and conclusions of the analysis. Whilst in many disease areas there can be clear justification for including carers’ health-related quality of life (HRQL) in health technology assessments (HTAs), we believe that, in general, the perspective of carers is under-represented in HTA. We were interested in the extent, and methods by which, HTA bodies include carers’ HRQL in economic evaluation. We reviewed guidance from 13 HTA bodies across the world regarding carers’ HRQL. We examined five interventions, as case studies, assessed by different HTA bodies, and extracted information on whether carers’ HRQL was included by the manufacturers or assessors in their dossiers of evidence, the data and methods used, and the impact on the results. We developed recommendations to guide analysts on including carers’ HRQL in economic evaluations. When reviewing the methods guides: two bodies recommend including carers’ HRQL in the base case, two referred to outcomes for all individuals, two preferred to exclude carers, three said it depended on other conditions, and it was unclear for four. Across the five case studies: five source studies for carers’ HRQL and two different modelling approaches were used. Including carers’ HRQL increased incremental quality-adjusted life-years (QALYs) in 19/23 analyses (decreased it in two); there was substantial variation in the magnitude of change. We recommend: (1) the inclusion of carers is clearly justified, (2) the use of HRQL data from the population under comparison where possible, (3) the use of data from another disease area or country is clearly justified (and transferability/applicability issues are discussed), (4) the use of external data to derive comparisons for cross-sectional data is justified, (5) assumptions and implications of the modelling approach are explicit, and (6) disaggregated results for patients and carers are presented.

Publicly funded immunization programs have grown in both complexity and scope, resulting in increased costs and more complex programmatic decision making. Economic evaluations can provide crucial information to support informed decision making. While very few countries have National Immunization Technical Advisory Groups that analyze economic information, many have started to develop processes for this purpose. Since these guidelines are being developed at the national level, we propose that regional jurisdictions, especially those responsible for healthcare (e.g., provinces, territories, states), need clear processes for incorporating this information into their immunization decision making and program implementation. We interviewed Canadian vaccine experts involved in provincial vaccine policy decision making to identify current practices, perceptions, and recommendations around incorporating economic analysis into that process. Based on these interviews, we make five recommendations: (1) economic evidence should be routinely incorporated into the decision making process; (2) economic experts should sit on, or be available to, regional advisory committees; (3) efforts should be made to build on regional expertise by increasing educational opportunities on economic evaluation; (4) processes should include guidelines for when economic analysis is not required; and (5) clarification on the role of regional advisory groups in economic analysis is needed in relation to national expertise. The information presented here provides a starting point for regional health policy experts and decision makers to work collaboratively with national partners to create transparent and effective approaches to incorporating economic analysis into vaccine decision making.

The estimation of lifetime quality-adjusted life-years (QALYs) requires the extrapolation of both length and quality of life (QoL). The extrapolation …

Gene therapies represent a new era of medicine, offering the potential for truly transformational health gains, and further benefits for society and health systems. Gene therapy is particularly relevant to rare disease patients, as more than 80 per cent of rare diseases have a known monogenic (single gene) cause. In contrast to traditional small molecule medicines, gene therapies have the potential to correct underlying genetic defects, offering the potential for transformational health gains rather than simply managing symptoms.

Economic evaluations have increasingly sought to understand how funding decisions within care sectors impact health inequalities. However, there is a disconnect between the methods used by researchers (e.g., within universities) and analysts (e.g., within publicly funded commissioning agencies), compared to evidence needs of decision makers in regard to how health inequalities are accounted for and presented. Our objective is to explore how health inequality is defined and quantified in different contexts. We focus on how specific approaches have developed, what similarities and differences have emerged, and consider how disconnects can be bridged. We explore existing methodological research regarding the incorporation of inequality considerations into economic evaluation in order to understand current best practice. In parallel, we explore how localised decision makers incorporate inequality considerations into their commissioning processes. We use the English care setting as a case study, from which we make inference as how local commissioning has evolved internationally. We summarise the recent development of distributional cost-effectiveness analysis in the economic evaluation literature: a method that makes explicit the trade-off between efficiency and equity. In the parallel decision-making setting, while the alleviation of health inequality is regularly the focus of remits, few details have been formalised regarding its definition or quantification. While data development has facilitated the reporting and comparison of metrics of inequality to inform commissioning decisions, these tend to focus on measures of care utilisation and behaviour rather than measures of health. While both researchers and publicly funded commissioning agencies are increasingly putting the identification of health inequalities at the core of their actions, little consideration has been given to ensuring that they are approaching the problem in a consistent way. The extent to which researchers and commissioning agencies can collaborate on best practice has important implications for how successful policy is in addressing health inequalities.

This study aimed to perform a systematic review of published evidence on the psychometric properties of 3-level version of EQ-5D-Y and 5-level version…

There is growing interest in cost-effectiveness thresholds as a tool to inform resource allocation decisions in health care. Studies from several countries have sought to estimate health system opportunity costs, which supply-side cost-effectiveness thresholds are intended to represent. In this paper, we consider the role of empirical estimates of supply-side thresholds in policy-making. Recent studies estimate the cost per unit of health based on average displacement or outcome elasticity. We distinguish the types of point estimates reported in empirical work, including marginal productivity, average displacement, and outcome elasticity. Using this classification, we summarise the limitations of current approaches to threshold estimation in terms of theory, methods, and data. We highlight the questions that arise from alternative interpretations of thresholds and provide recommendations to policymakers seeking to use a supply-side threshold where the evidence base is emerging or incomplete. We recommend that: (1) policymakers must clearly define the scope of the application of a threshold, and the theoretical basis for empirical estimates should be consistent with that scope; (2) a process for the assessment of new evidence and for determining changes in the threshold to be applied in policy-making should be created; (3) decision-making processes should retain flexibility in the application of a threshold; and (4) policymakers should provide support for decision-makers relating to the use of thresholds and the implementation of decisions stemming from their application.

Background Valuation is a critical part of the costing process in health economic evaluations. However, an overview of specific issues relevant to the European context on harmonizing methodological requirements for the valuation of costs to be used in health economic evaluation is lacking. We aimed to inform the development of an international, harmonized and multi-sectoral costing framework, as sought in the European PECUNIA (ProgrammE in Costing, resource use measurement and outcome valuation for Use in multi-sectoral National and International health economic evaluAtions) project. Conclusion This review provides a basic summary of existing costing practices for evaluative purposes across sectors and countries and highlights several common methodological factors influencing divergence in cost valuation methods that would need to be systematically incorporated and addressed in future costing practices to achieve more comparable, harmonized health economic evaluation evidence.

Purpose Oncology drugs are often approved for multiple indications, for which their clinical benefit varies. Aligning a single price to this differing value remains a challenge. This study examines the clinical and economic value, price, and reimbursement of multi-indication cancer drugs across seven countries, representing different approaches to value assessment, pricing, and coverage decisions: the USA, Germany, France, England, Canada, Australia, and Scotland. Methods Twenty-five multi-indication cancer drugs across 100 indications were identified with US Food and Drug Administration (FDA) approval between 2009 and 2019. For each indication data on Health Technology Assessment (HTA) recommendations, disease prevalence, and drug prices were obtained. Quality-adjusted life years (QALYs) gained, disease prevalence, list prices, and HTA outcomes were then compared across indications and regions. Results First approved indications provide a higher clinical benefit whilst targeting a smaller patient group than indication extensions. Quality-adjusted life year gains were higher for first (0.99, 95% CI 0.05–3.25) compared to second (0.51, 95% CI 0.02–1.63, p < 0.001) and third (0.58, 95% CI 0.05–2.07, p < 0.01) approved indications. Disease prevalence per 100,000 inhabitants was 20.7 (95% CI 0.2–63.3) for first compared to 27.1 (95% CI 1.5–109.6, p = 0.907) for second and 128.3 (95% CI 3.1–720.1, p < 0.001) for third approved indications. With each approved indication drug prices declined in Germany and France, remained constant in the UK, Canada, and Australia, whilst they increased in the USA. Negative HTA outcomes, clinical restrictions, and managed entry agreements (MEAs) were more frequently observed for indication extensions. Conclusions Results suggest that indication development is prioritised according to clinical value and disease prevalence. Countries employ different mechanisms to account for each indication’s differential benefit, e.g., weighted-average prices (Germany, France, Australia), differential discounts (England, Scotland), clinical restrictions, and MEAs (England, Scotland, Australia, Canada). Value-based indication-specific pricing can help to align the benefit and price for multi-indication cancer drugs.

Background The international protocol for valuing EQ-5D-5L focuses upon prescribed preference elicitation methods and design. However, there are no recommendations around sampling, recruitment, data analysis or modelling to generate the EQ-5D-5L value set. This review examines methods used to generate international EQ-5D-5L values sets, across sampling, recruitment, data analysis, modelling, assessing model performance and selection of the recommended value set. Methods All published EQ-5D-5L value sets were identified by a systematic search and confirmed by the EuroQol Group. Data were extracted to assess sampling, recruitment, preference elicitation techniques and design, data analysis, modelling, assessing model performance, and vale set selection. These are summarised in tables. Results The review included 29 studies with 27 value sets generated using time-trade-off (TTO) data (n = 10) only or using a hybrid model that combines TTO and discrete choice experiment data (n = 17). TTO data were most commonly estimated using a heteroscedastic Tobit model with censoring at − 1, and the hybrid model using a specially created program. Model performance was generally assessed using goodness of fit, logical consistency and significance of coefficients, suitability of the model for the data characteristics and parsimony, though not all selected models account for the specific characteristics of the data. Discussion Different assessments of model performance and reasoning are provided for the selection of the recommended value set for a country. This raises the question of valid criteria for selecting a recommended value set and whether this should rely upon researchers’ recommendations when value sets are often used to inform public policy.

Economic evaluation of genomic/genetic tests: a review and future directions - Volume 38 Issue 1

Background Health economic evaluation of digital nursing technologies (DNT) is important to provide information that helps avoid undesirable developments and implementations as well as increase the chances of success of developed applications. At the same time, studies and evidence on cost-effectiveness are still very rare in this field. Review studies in related technology areas such as telemedicine frequently criticise the quality and comparability of health economic evaluations conducted in this field. Based on a content analysis of methodological literature on the economic evaluation of innovative (digital) technologies in health and nursing, this article aims to identify specific challenges in this research area and offers recommendations on how to address these challenges to promote more sound health economic evaluations in the future. Methods A rapid review was conducted, consisting of a systematic search in the Pubmed database as well as Google Scholar. In addition, the literature lists of the analysed texts were scoured for additional texts to be included. Methodological literature, single studies, and reviews were included. A total of 536 studies were screened, of which 29 were included in the full text analysis. Results Based on the systematic content analysis of the studies under consideration, 10 specific methodological challenges are identified, and the methodological recommendations were examined for consideration. A particular focus was given to whether specific methodological approaches might be needed in the context of evaluating the efficiency of DNT. Conclusion Many of the challenges identified for the health economic evaluations of digital nursing technologies are comparable to those of other complex health care interventions. The recommendations discussed can help to alleviate those challenges. Future research should focus on alternative approaches to assessing causality in different phases of technology development while maintaining high evidence standards. High-evidence economic assessment of technologies in nursing care should be carried out in routine use, especially if they are intended to be reimbursed by the social insurance.

This research aimed to review the theoretical and methodological aspects of the quality-adjusted life year (QALY) which give rise to potential for bias against certain patient populations

Advances in machine learning (ML) and artificial intelligence offer tremendous potential benefits to patients. Predictive analytics using ML are alrea…

Background Using a standardized approach to describe the sources of uncertainty in cost-effectiveness analyses might bring added value to the local critical assessment procedure of reimbursement submissions in Hungary. The aim of this research is to present a procedural framework to identify, quantify and interpret sources of uncertainty, using the reimbursement dossier of darolutamide as an illustrative example. Methods In the procedural framework designed for the critical assessment of cost-effectiveness analyses, the quantifiability of an identified source of uncertainty is assessed through the input parameters of the originally submitted model, which is followed by the interpretation of its impact on estimates of costs and outcomes compared to the base case cost-effectiveness conclusion. Results Based on our experiences with the recent reimbursement dossier of darolutamide, the significant and quantifiable sources of uncertainty were the time horizon of the economic analysis; the restriction of the efficacy analysis population; long-term relative effectiveness of darolutamide; price discount on subsequent therapies. We identified resource use patterns for comparator and subsequent therapies as a quantifiable, yet non-significant source of uncertainty. The EQ-5D value set used to estimate utility values was identified as a non-quantifiable and potentially not significant source of uncertainty. Conclusions The procedural framework, demonstrated with an example, was sufficiently flexible and coherent to document and structure the sources of uncertainty in cost-effectiveness analyses. The full-scale use of this framework is desirable during the decision-making process for reimbursement in Hungary. The further formalization of identifying sources of uncertainty is a possible subject of methodological development.

This study aimed to provide recommendations for identifying and implementing real option value (ROV) calculations in value assessment.We identified th…