évaluation médico économique

In this report, we explore the potential impact of the National Institute of Health and Care Excellence (NICE) decision outcomes on healthcare decision-making in 12 countries across the globe (Australia, Brazil, Canada, France, Italy, Israel, Japan, South Korea, Poland, Saudi Arabia, Sweden, and the United Arab Emirates). We used quantitative and qualitative methods to estimate the level of impact and potential underlying mechanisms.

A high quality and widely-accepted UK EQ-5D-5L value set is urgently required to enable the latest version of EQ-5D scored using recent UK public pref…

United States Medicare will begin negotiating prices for top-selling drugs in 2023. This study describes and estimates potential savings from a therap…

A health economic model may include a set of related inputs whose true values are uncertain, but that can be assumed to follow a logical order. Various approaches are available for performing probabilistic sensitivity analysis while preserving the order constraint, one such approach is known as the difference method. The difference method approach appears to have many of the required properties, has been endorsed by good practice guidelines, and is likely to prove a popular approach. However, the proposed implementation of the difference method approach is cumbersome, requiring numerical estimation, which might present a barrier to its adoption. Furthermore, it is unclear whether the method can always be applied to three or more model inputs and whether it is unbiased across all possible input values. This study has investigated these three issues for ordered inputs bounded between 0 and 1. An analytic solution is given that allows for more straightforward and compact implementation. The difference method approach cannot always be applied to a set of three or more model inputs, and this depends on the relative size of the variances of the logit-transformed Beta distributions fitted to each variable. The approach can also produce samples with biased means and variances under certain combinations of input means and variances. It is recommended that the difference method approach be used where appropriate; however, an understanding of its limitations is necessary to identify such cases.

While welfarist economics (WE) methods rely wholly on individuals' valuations, extra-welfarist (EW) methods seek alternative measures of value. Major …

Positive health technology assessment (HTA) outcomes can have important implications for equity, efficiency and timely patient access to novel therapi…

The quality-adjusted life-year (QALY) is an international standard in cost-effectiveness analysis. A known concern arises from the relatively lower QALY gains attributed to treatments that extend the life of individuals with chronic disability. We analyze here the advantages and disadvantages of the equal value life-year (evLY) as an alternative or a complementary measure to the QALY, and share learned experiences from using this measure in health technology assessments. We present the conceptual rationale for the evLY, describe how it is estimated, and assess the differences in results between analyses based on the evLY and the QALY. We share a how-to guide in estimating the evLY using a downloadable tool and summarize our empirical experience using this measure. Incremental evLYs are feasible and address concerns regarding the risk for a cost-effectiveness analysis to undervalue treatments for people with chronic disabilities. Based on our set of analyses using the evLY, a threshold of $84,000 per evLY gained would be needed to maintain alignment with a threshold of $100,000 per added QALY. The evLY is a measure of health gain that can be used as an alternative or a complement to the QALY to address concerns related to undervaluing treatments that extend the life of individuals with serious illness or chronic disability. We recommend that it be reported within all cost-effectiveness analyses but may have special relevance in the current political environment in the USA, where use of the QALY is often challenged or prohibited.

Value sets for the EQ-5D-Y-3L published to date appear to have distinctive characteristics compared with value sets for corresponding adult instruments: in many cases, the value for the worst health state is higher and there are fewer values < 0. The aim of this paper is to consider how and why values for child and adult health differ; and what the implications of that are for the use of EQ-5D-Y-3L values in economic evaluations to inform healthcare resource allocation decisions. We posit four potential explanations for the differences in values: (a) The wording of severity labels may mean the worst problems on the EQ-5D-Y-3L are descriptively less severe than those on the EQ-5D-5L; (b) Adults may genuinely consider that children are less badly affected than adults by descriptively similar health issues. That is, for any given health problem, adult respondents in valuation studies consider children’s overall health-related quality of life (HRQoL) on average to be higher than that for adults; (c) Values are being sought by eliciting adults’ stated preferences for HRQoL in another person, rather than in themselves (regardless of whether the ‘other person’ concerned is a child); and (d) The need to elicit preferences for child HRQoL that are anchored at dead = 0 invokes special considerations regarding children’s survival. Existing evidence does not rule out the possibility that (c) and (d) exert an upward bias in values. We consider the implications of that for the interpretation and use of values for pediatric HRQoL. Alternative methods for valuing children’s HRQoL in a manner that is not ‘age specific’ are possible and may help to avoid issues of non-comparability. Use of these methods would place the onus on health technology assessment bodies to reflect any special considerations regarding child quality-adjusted life-year gains.

This study aims to provide an overview of the gaps and challenges in the value assessment of biosimilars and to identify potential approaches to addre…

To estimate the incremental health benefits of pharmaceutical innovations approved between 2011-2021 and the share that would surpass the National Ins…

This paper illustrates analysis of opinions collected from selected European payers (HTA organisations, authorities/committees assessing, appraising a…

KCE Reports 369B (2023) S’ils souhaitent que leur produit soit remboursé, les producteurs d’implants ou de dispositifs médicaux invasifs doivent introduire un dossier auprès de l’assurance maladie (INAMI).

The German EQ-5D-5L value set is based on the average preferences of the general population. However, in Germany, there is an ongoing debate about the…

The effectiveness and cost of a public health intervention is dependent on complex human behaviors, yet health economic models typically make simplified assumptions about behavior, based on littl

Objectives Health regulators have progressively increased their attention and focus on patient-reported outcomes (PROs), driven by the diffusion of a patient-centred approach to the drug development process. This study investigates the consideration of PROs and their measures (PROMs) in the authorisation of medicines in Europe. Methods All medicines for human use authorised or refused by the European Medicines Agency (EMA) in the period 2017–2022 were identified, and corresponding European Public Assessment Reports (EPARs) were downloaded for review. Medicine and PROs/PROM characteristics were systematically recorded. A multivariate logistic regression was performed to identify variables associated with the use of patient-reported evidence in EPARs. Results Overall, 497 EPARs of authorised medicines and 19 EPARs of refused medicines were analysed; of these, 240 (48.3%) and 10 (52.6%), respectively, reported any use of PROs/PROMs (p = 0.710). For authorised medicines, the likelihood of using PROs/PROMs was negatively affected by generic (OR = 0.01, p < 0.001) and biosimilar status (OR = 0.46, p = 0.013) and positively affected by orphan status (OR = 1.41, p = 0.177). The use of PROMs (50.6% in 2017 vs 47.9% in 2022) did not show a clear pattern over the 6-year period considered (p = 0.758) and was particularly uncommon in some therapeutic areas (e.g., 15.2% in infectious diseases). A total of 816 dyads of PROs/PROMs were identified. On average each EPAR considered 1.6 (range: 0–14) instruments. Patient-reported outcomes were typically secondary (53.3%) and exploratory endpoints (18.8%); in one-third of cases (32.5%), they assessed generic quality of life. Among the PROMs, 227 (27.8%) targeted general population; EQ-5D (11.0%), SF-36/SF-12 (5.9%) and EORTC QLQ-C30 (5.6%) were the instruments most frequently used. Conclusions This study suggests PROs/PROMs are considered in less than half of total medicine assessments and even more rarely in some disease areas. The adoption of PROs is key in EMA strategy to 2025 and would be facilitated by consensus development on their measures and optimisation of data collection.

Background Compensation mechanisms and multiplier effects may affect productivity losses due to illness, disability, or premature death of individuals. Hence, they are important in estimating productivity losses and productivity costs in the context of economic evaluations of health interventions. This paper presents a systematic literature review of papers focusing on compensation mechanisms and multiplier effects, as well as whether and how they are included in health economic evaluations. Methods The systematic literature search was performed covering EconLit and PubMed. A data-extraction form was developed focusing on compensation mechanisms and multiplier effects. Results A total of 26 studies were included. Of these, 15 were empirical studies, three studies were methodological studies, two studies combined methodological research with empirical research, four were critical reviews, one study was a critical review combined with methodological research, and one study was a cost–benefit analysis. No uniform definition of compensation mechanisms and multiplier effects was identified. The terminology used to describe compensation mechanisms and multiplier effects varied as well. While the included studies suggest that both multipliers as well as compensation mechanisms substantially impact productivity cost estimates, the available evidence is scarce. Moreover, the generalizability as well as validity of assumptions underlying the calculations are unclear. Available measurement methods for compensation mechanisms and multiplier effects differ in approaches and are hardly validated. Conclusion While our review suggests that compensation mechanisms and multiplier effects may have a significant impact on productivity losses and costs, much remains unclear about their features, valid measurement, and correct valuation. This hampers their current inclusion in economic evaluation, and therefore, more research into both phenomena remains warranted.

This is the 23rd in a series of articles describing the GRADE approach to grading the certainty of evidence and strength of recommendations for system…

ObjectivesThis study aimed to compare reimbursement recommendations by the British National Institute for Health and Care Excellence (NICE) and the French National Authority for Health (Haut

Background Missing data in costs and/or health outcomes and in confounding variables can create bias in the inference of health economics and outcomes research studies, which in turn can lead to inappropriate policies. Most of the literature focuses on handling missing data in randomized controlled trials, which are not necessarily always the data used in health economics and outcomes research. Objectives We aimed to provide an overview on missing data issues and how to address incomplete data and report the findings of a systematic literature review of methods used to deal with missing data in health economics and outcomes research studies that focused on cost, utility, and patient-reported outcomes. Methods A systematic search of papers published in English language until the end of the year 2020 was carried out in PubMed. Studies using statistical methods to handle missing data for analyses of cost, utility, or patient-reported outcome data were included, as were reviews and guidance papers on handling missing data for those outcomes. The data extraction was conducted with a focus on the context of the study, the type of missing data, and the methods used to tackle missing data. Results From 1433 identified records, 40 papers were included. Thirteen studies were economic evaluations. Thirty studies used multiple imputation with 17 studies using multiple imputation by chained equation, while 15 studies used a complete-case analysis. Seventeen studies addressed missing cost data and 23 studies dealt with missing outcome data. Eleven studies reported a single method while 20 studies used multiple methods to address missing data. Conclusions Several health economics and outcomes research studies did not offer a justification of their approach of handling missing data and some used only a single method without a sensitivity analysis. This systematic literature review highlights the importance of considering the missingness mechanism and including sensitivity analyses when planning, analyzing, and reporting health economics and outcomes research studies.

Trial-based economic evaluations are increasingly being conducted to support healthcare decision-making. When analysing trial-based economic evaluation data, different methodological challenges may be encountered, including (i) missing data, (ii) correlated costs and effects, (iii) baseline imbalances and (iv) skewness of costs and/or effects. Despite the broad range of methods available to account for these methodological challenges in effectiveness studies, they may not always be directly applicable in trial-based economic evaluations where costs and effects are analysed jointly, and more than one methodological challenge typically needs to be addressed simultaneously. The use of inappropriate methods can bias results and conclusions regarding the cost-effectiveness of healthcare interventions. Eventually, such low-quality evidence can hamper healthcare decision-making, which may in turn result in a waste of already scarce healthcare resources. Therefore, this tutorial aims to provide step-by-step guidance on how to combine appropriate statistical methods for handling the abovementioned methodological challenges using a ready-to-use R script. The theoretical background of the described methods is provided, and their application is illustrated using a simulated trial-based economic evaluation.

Cancer therapies targeting tumour-agnostic biomarkers are challenging traditional health technology assessment (HTA) frameworks. The high prevalence o…

In evaluating the clinical benefit of new therapeutic interventions, it is critical that the treatment outcomes assessed reflect aspects of health tha…

Background Implementation and uptake of health technology assessment for evaluating medical devices require including aspects that different stakeholders consider relevant, beyond cost and effectiveness. However, the involvement of stakeholders in sharing their views still needs to be improved. Objective This article explores the relevance of distinct value aspects for evaluating different types of medical devices according to stakeholders' views. Methods Thirty-four value aspects collected through literature review and expert validation were the input for a 2-round Web-Delphi process. In the Web-Delphi, a panel of participants from five stakeholders’ groups (healthcare professionals, buyers and policymakers, academics, industry, and patients and citizens) judged the relevance of each aspect, by assigning a relevance-level (‘Critical’, ‘Fundamental’, ‘Complementary’, or ‘Irrelevant’), for two types of medical devices separately: ‘Implantable’ and ‘In vitro tests based on biomarkers’. Opinions were analysed at the panel and group level, and similarities across devices were identified. Results One hundred thirty-four participants completed the process. No aspects were considered ‘Irrelevant’, neither for the panel nor for stakeholder groups, in both types of devices. The panel considered effectiveness and safety-related aspects ‘Critical’ (e.g., ‘Adverse events for the patient’), and costs-related aspects ‘Fundamental’ (e.g., ‘Cost of the medical device’). Several additional aspects not included in existing frameworks’ literature, e.g., related to environmental impact and devices’ usage by the healthcare professional, were deemed as relevant by the panel. A moderate to substantial agreement across and within groups was observed. Conclusion Different stakeholders agree on the relevance of including multiple aspects in medical devices’ evaluation. This study produces key information to inform the development of frameworks for valuing medical devices, and to guide evidence collection.