Mapping Health Technology Assessment Agency Approaches for Biosimilar Value Assessment: An ISPOR Special Interest Group Report.

OBJECTIVES: A systematic literature review undertaken by the ISPOR Biosimilar Special Interest Group highlighted that limited guidance exists on how to assess biosimilars value and on appropriate economic evaluation techniques. This study described current health technology assessment (HTA) agency approaches for biosimilar value assessment. METHODS: Semi-structured interviews (n = 16) were carried out with HTA experts in Africa, America, Asia, Australia, and Europe to investigate current HTA practices for biosimilars. Data categorization was based on a thematic analysis approach. Findings from the qualitative data analysis were interpreted in view of relevant published literature. RESULTS: Our research suggests that in systems in which frameworks for biosimilar regulatory approval are well established, HTA agencies can accept the regulators' comparability exercise, and reimbursement decisions can generally be based on price comparisons. This approach is accepted in practice and allows streamlining of biosimilars value assessment. Nevertheless, conducting HTAs for biosimilars can be relevant when (1) the originator is not reimbursed, (2) the biosimilar marketing authorization holder seeks reimbursement for indications/populations, pharmaceutical forms, methods and routes of administration that differ with respect to the originator, and (3) a price premium is sought for a biosimilar based on an added-value claim. Further, HTA agencies' role conducting class-review updates following biosimilar availability can support greater patients' access to biologics. CONCLUSIONS: Internationally, there are differences in how national competent authorities on pricing and reimbursement of pharmaceuticals perceive HTA's role for biosimilars. Therefore, HTA agencies are encouraged to issue clear guidance on when and how to conduct HTAs for biosimilars, and on which economic techniques to apply.

Project SATURN- a real-world evidence data collaboration with existing European datasets in Osteogenesis Imperfecta to support future therapies.

Regulatory marketing authorisation is not enough to ensure patient access to new medicinal products. Health Technology Assessment bodies may require data on effectiveness, relative effectiveness, and cost-effectiveness. Healthcare systems may require data on clinical utility, savings, and budget impact. Furthermore, the exact requirements of these bodies vary country by country and sometimes even region to region, resulting in a patchwork of different data requirements to achieve effective, reimbursed patient access to new therapies. In addition, clinicians require data to make informed clinical management decisions. This requirement is of key importance in rare diseases where there is often limited data and clinical experience at the time of regulatory approval.This paper describes an innovative initiative that is called Project SATURN: Systematic Accumulation of Treatment practices and Utilization, Real world evidence, and Natural history data for the rare disease Osteogenesis Imperfecta. The objective of this project is to generate a common core dataset by utilising existing data sources to meet the needs of the various stakeholders and avoiding fragmentation through multiple approaches (e.g., a series of individual national requests/approaches, and unconnected with the regulators' potential requirements). It is expected that such an approach will reduce the time for patient access to life-changing medications. Whilst Project SATURN applies to Osteogenesis Imperfecta, it is anticipated that the principles could also be applied to other rare diseases and reduce the time for patient access to new medications.

Health technology assessment and healthcare environmental sustainability: Prioritizing effort and maximizing impact.

The growing global focus on and sense of urgency toward improving healthcare environmental sustainability and moving to low-carbon and resilient healthcare systems is increasingly mirrored in discussions of the role of health technology assessment (HTA). This Perspective considers how HTA can most effectively contribute to these goals and where other policy tools may be more effective in driving sustainability, especially given the highly limited pool of resources available to conduct environmental assessments within HTA. It suggests that HTA might most productively focus on assessing those technologies that have intrinsic characteristics which may cause specific environmental harms or vulnerabilities, while the generic environmental impacts of most other products may be better addressed through other policy and regulatory mechanisms.

Deliberative process of health technology reassessment by health technology assessment agency in Korea.

In 2019, the National Evidence-based Healthcare Collaborating Agency (NECA) in Korea established a health technology reassessment (HTR) system to manage the life cycle of health technologies and develop operational measures promoting the efficient use of healthcare resources. The purpose of this study is to introduce the detailed implementation process and practical functional methods of the HTR implemented by NECA.The HTR is a structured multidisciplinary method for analyzing health technologies currently used in the healthcare system based on the latest information on parameters, such as clinical safety, effectiveness, and cost-effectiveness of optimizing the use of healthcare resources as well as social and ethical issues. All decision-making stages of the HTR are carefully reviewed and transparently managed. The HTR committee makes significant decisions, and the subcommittee decides the details related to the assessment process.Since the pilot began in 2018, 262 cases have been reassessed, of which, 126 cases (48.1 percent) were health services not covered by the National Health Insurance (NHI). Over the past 5 years, approximately 130 recommendations for the in-use technologies were determined by the HTR committee. In the near future, it will be necessary to officially develop and establish a Korean HTR system and a legal foundation to optimize the NHI system.

How health technology assessment can help to address challenges in drug repurposing: a conceptual framework.

Drug repurposing faces various challenges that can impede its success. We developed a framework outlining key challenges in drug repurposing to explore when and how health technology assessment (HTA) methods can address them. We identified 20 drug-repurposing challenges across the categories of data access, research and development, collaboration, business case, regulatory and legal challenges. Early incorporation of HTA methods, including literature review, empirical research, stakeholder consultation, health economic evaluation and uncertainty assessment, can help to address these challenges. HTA methods canassess the value proposition of repurposed drugs, inform further research and ultimately help to bring cost-effective repurposed drugs to patients.

A systematic review on the appropriate discounting rates for the economic evaluation of gene therapies: whether a specific approach is justified to tackle the challenges?

OBJECTIVES: Discounting the cost and effect for health intervention is a controversial topic over the last two decades. In particular, the cost-effectiveness of gene therapies is especially sensitive to the discount rate because of the substantial delay between the upfront cost incurred and long-lasing clinical benefits received. This study aims to investigate the influence of employing alternative discount rates on the incremental cost-effectiveness ratio (ICER) of gene therapies. METHODS: A systematic review was conducted to include health economic evaluations of gene therapies that were published until April 2023. RESULTS: Sensitivity or scenario analysis indicated that discount rate represented one of the most influential factors for the ICERs of gene therapies. Discount rate for cost and benefit was positively correlated with the cost-effectiveness of gene therapies, that is, a lower discount rate significantly improves the ICERs. The alternative discount rate employed in some cases could be powerful to alter the conclusion on whether gene therapies are cost-effective and acceptable for reimbursement. CONCLUSIONS: Although discount rate will have substantial influence on the ICERs of gene therapies, there lacks solid evidence to justify a different discounting rule for gene therapies. However, it is proposed that the discount rate in the reference case should be updated to reflect the real-time preference, which in turn will affect the ICERs and reimbursement of gene therapies more profoundly than conventional therapies.

Development of a disease-specific health utility score for chronic obstructive pulmonary disease from a discrete choice experiment patient preference study.

OBJECTIVES: While patient input to health technology assessment (HTA) has traditionally been of a qualitative nature, there is increasing interest to integrate quantitative evidence from patient preference studies into HTA decision making. Preference data can be used to generate disease-specific health utility data. We generated a health utility score for patients with chronic obstructive pulmonary disease (COPD) and consider its use within HTAs. METHODS: Based on qualitative research, six symptoms were identified as important to COPD patients: shortness of breath, exacerbations, chronic cough, mucus secretion, sleep disturbance, and urinary incontinence. We employed a discrete choice experiment (DCE) and the random parameter logistic regression technique to estimate utility scores for all COPD health states. The relationship between patients' COPD health utility scores, self-perceived COPD severity, and EQ-5D-3L utility scores was analyzed, with data stratified according to disease severity and comorbidity subgroups. RESULTS: The COPD health utility score had face validity, with utility scores negatively correlated with patients' self-perceived COPD severity. The correlation between the COPD health utility scores and EQ-5D-3L values was only moderate. While patient EQ-5D-3L scores were impacted by comorbidities, the COPD health utility score was less impacted by comorbid conditions. CONCLUSIONS: Our COPD utility measure, derived from a DCE, provides a patient-centered health utility score and is more sensitive to the COPD health of the individual and less sensitive to other comorbidities. This disease-specific instrument should be considered alongside generic health-related quality of life instruments when valuing new COPD therapies in submissions to licensing and reimbursement agencies.

Suitability of the Current Health Technology Assessment of Innovative Artificial Intelligence-Based Medical Devices: Scoping Literature Review.

BACKGROUND: Artificial intelligence (AI)-based medical devices have garnered attention due to their ability to revolutionize medicine. Their health technology assessment framework is lacking. OBJECTIVE: This study aims to analyze the suitability of each health technology assessment (HTA) domain for the assessment of AI-based medical devices. METHODS: We conducted a scoping literature review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology. We searched databases (PubMed, Embase, and Cochrane Library), gray literature, and HTA agency websites. RESULTS: A total of 10.1% (78/775) of the references were included. Data quality and integration are vital aspects to consider when describing and assessing the technical characteristics of AI-based medical devices during an HTA process. When it comes to implementing specialized HTA for AI-based medical devices, several practical challenges and potential barriers could be highlighted and should be taken into account (AI technological evolution timeline, data requirements, complexity and transparency, clinical validation and safety requirements, regulatory and ethical considerations, and economic evaluation). CONCLUSIONS: The adaptation of the HTA process through a methodological framework for AI-based medical devices enhances the comparability of results across different evaluations and jurisdictions. By defining the necessary expertise, the framework supports the development of a skilled workforce capable of conducting robust and reliable HTAs of AI-based medical devices. A comprehensive adapted HTA framework for AI-based medical devices can provide valuable insights into the effectiveness, cost-effectiveness, and societal impact of AI-based medical devices, guiding their responsible implementation and maximizing their benefits for patients and health care systems.

HTA criteria adopted in different models of public healthcare systems for orphan drugs: A scoping review.

Access to drugs for rare diseases constitutes a challenge to healthcare systems, especially those with public funding. This study aimed to map and summarize the criteria used by HTA agencies in different healthcare systems to evaluate reimbursement recommendations for orphan drugs. A comprehensive literature search was performed on the databases PubMed, LILACS, Scopus, and Embase and the gray literature (Google Scholar and websites of HTA agencies). Publications addressing the criteria used by HTA agencies in countries with public healthcare systems when evaluating reimbursement recommendations for orphan drugs were included. This scoping review included 23 studies published between 2014 and 2023, mostly consisting of reviews of HTA reports, guidance documents, and original articles. The criteria were mapped from 19 countries and ranked within three models of healthcare systems (National Health System, National Health Insurance, and Social Health Insurance). All models shared concerns about unmet needs and disease nature. In addition, NHS countries (e.g., United Kingdom, Sweden, and Italy) prioritized innovation and system-level impact, while SHI countries (e.g., Germany, France, the Netherlands) usually valued budget impact and employed expedited evaluation processes. This review provides a comprehensive understanding of the general tendencies of each healthcare system model in establishing differentiated criteria to address the challenges posed by the limited evidence and investment in the field of rare diseases.

Design of a multiple criteria decision analysis framework for prioritizing high-impact health technologies in a regional health service.

OBJECTIVES: This study aims to develop a framework for establishing priorities in the regional health service of Murcia, Spain, to facilitate the creation of a comprehensive multiple criteria decision analysis (MCDA) framework. This framework will aid in decision-making processes related to the assessment, reimbursement, and utilization of high-impact health technologies. METHOD: Based on the results of a review of existing frameworks for MCDA of health technologies, a set of criteria was proposed to be used in the context of evaluating high-impact health technologies. Key stakeholders within regional healthcare services, including clinical leaders and management personnel, participated in a focus group (n = 11) to discuss the proposed criteria and select the final fifteen. To elicit the weights of the criteria, two surveys were administered, one to a small sample of healthcare professionals (n = 35) and another to a larger representative sample of the general population (n = 494). RESULTS: The responses obtained from health professionals in the weighting procedure exhibited greater consistency compared to those provided by the general public. The criteria more highly weighted were "Need for intervention" and "Intervention outcomes." The weights finally assigned to each item in the multicriteria framework were derived as the equal-weighted sum of the mean weights from the two samples. CONCLUSIONS: A multi-attribute function capable of generating a composite measure (multicriteria) to assess the value of high-impact health interventions has been developed. Furthermore, it is recommended to pilot this procedure in a specific decision context to evaluate the efficacy, feasibility, usefulness, and reliability of the proposed tool.

The impact of willingness-to-pay threshold on price reduction recommendations for oncology drugs: a review of assessments conducted by the Canadian Agency for Drugs and Technologies in Health.

Since late 2020, the Canadian Agency of Drugs and Technologies in Health (CADTH) has been using a threshold of $50,000 (CAD) per quality-adjusted life-year (QALY) for both oncology and non-oncology drugs. When used for oncology products, this threshold is hypothesized to have a higher impact on the time to access these drugs in Canada. We studied the impact of price reductions on time to engagement and negotiation with the pan-Canadian Pharmaceutical Alliance for oncology drugs reviewed by CADTH between January 2020 and December 2022. Overall, 103 assessments reported data on price reductions recommended by CADTH to meet the cost-effectiveness threshold for reimbursement. Of these assessments, 57% (59/103) recommendations included a price reduction of greater than 70% off the list price. Eight percent (8/103) were not cost-effective even at a 100% price reduction. Of the 47 assessments that had a clear benefit, in 21 (45%) CADTH recommended a price reduction of at least 70%. The median time to price negotiation (not including time to engagement) for assessments that received at least 70% vs >70% price reduction was 2.6 vs 4.8 months. This study showed that there is a divergence between drug sponsor's incremental cost-effectiveness ratio (ICER) and CADTH revised ICER leading to a price reduction to meet the $50,000/QALY threshold. For the submissions with clear clinical benefit the median length of engagement (2.5 vs 3.3 months) and median length of negotiation (3.1 vs 3.6 months) were slightly shorter compared with the submissions where uncertainties were noted in the clinical benefit according to CADTH. This study shows that using a $50,000 per QALY threshold for oncology products potentially impacts timely access to life saving medications.

Value-based payment for high-cost treatments in Singapore: a qualitative study of stakeholders' perspectives.

OBJECTIVES: The rising costs of drugs have necessitated the exploration of innovative payment methods in healthcare systems. Risk-sharing agreements (RSAs) have been implemented in many countries as a value-based payment mechanism to manage the uncertainty associated with expensive technologies. This study aimed to investigate stakeholder perspectives on value-based payment in the Singaporean context, providing insights for future directions in health technology assessment and financing. METHODS: This descriptive qualitative inquiry involved participant interviews conducted between October 2021 and April 2022. Thematic analysis was conducted in two phases to analyze the interview transcripts. RESULTS: Seventeen respondents participated in the study, and five key themes emerged from the analysis. Stakeholders viewed RSAs as moderately positive, despite limited experience with them. They emphasized the importance of clearly defining objectives and establishing transparent criteria for implementing these schemes. The current data infrastructure was identified as both a barrier and facilitator, as RSAs impose administrative burdens. To successfully implement these payment mechanisms, capacity building, and effective stakeholder engagement that fosters mutual trust and cocreation are crucial. CONCLUSION: This study confirms previously identified barriers and facilitators to successful RSA implementation while contextualizing them within the Singaporean setting. The findings suggest that value-based payment has the potential to address uncertainty and improve access to healthcare technologies, but these barriers must be addressed for the schemes to be effective.

Give Due Consideration .

The new EU Regulation on health technology assessment (HTAR) provides for joint clinical assessments (JCA) of health technologies at EU level. When Member States carry out health technology assessments (HTA) at the national level, they shall give due consideration to the results of a JCA and comply with other obligations of the Regulation. This article aims to clarify what these obligations mean for the Member States and whether JCA results have to be considered outside a national health technology assessment as well. In this context, the question of which processes qualify as 'national HTA' and which requirements need to be fulfilled to trigger the obligations under Article 13 HTAR are discussed in more detail in this paper.

Application of natural language processing to predict final recommendation of Brazilian health technology assessment reports.

INTRODUCTION: Health technology assessment (HTA) plays a vital role in healthcare decision-making globally, necessitating the identification of key factors impacting evaluation outcomes due to the significant workload faced by HTA agencies. OBJECTIVES: The aim of this study was to predict the approval status of evaluations conducted by the Brazilian Committee for Health Technology Incorporation (CONITEC) using natural language processing (NLP). METHODS: Data encompassing CONITEC's official report summaries from 2012 to 2022. Textual data was tokenized for NLP analysis. Least Absolute Shrinkage and Selection Operator, logistic regression, support vector machine, random forest, neural network, and extreme gradient boosting (XGBoost), were evaluated for accuracy, area under the receiver operating characteristic curve (ROC AUC) score, precision, and recall. Cluster analysis using the k-modes algorithm categorized entries into two clusters (approved, rejected). RESULTS: The neural network model exhibited the highest accuracy metrics (precision at 0.815, accuracy at 0.769, ROC AUC at 0.871, and recall at 0.746), followed by XGBoost model. The lexical analysis uncovered linguistic markers, like references to international HTA agencies' experiences and government as demandant, potentially influencing CONITEC's decisions. Cluster and XGBoost analyses emphasized that approved evaluations mainly concerned drug assessments, often government-initiated, while non-approved ones frequently evaluated drugs, with the industry as the requester. CONCLUSIONS: NLP model can predict health technology incorporation outcomes, opening avenues for future research using HTA reports from other agencies. This model has the potential to enhance HTA system efficiency by offering initial insights and decision-making criteria, thereby benefiting healthcare experts.

Problems with NICE's severity weights.

This essay examines the implications, plausibility, and justification of the severity weighting that NICE (The National Institute for Health and Care Excellence) has endorsed for technology assessments in the U.K. It argues that the assignment by NICE of additional weights to health conditions which involve a large absolute or proportional shortfall of future expected QALYs (Quality-Adjusted Life Years) as compared to those who do not have these health conditions is not well supported and has troubling implications. The literature concerned with attitudes toward prioritizing severity has found a variety of notions of severity, and it is questionable to what extent those studies bear on whether to assign greater weights to health states involving large absolute or proportional shortfalls. In addition, the severity weighting is not well supported by either egalitarian or prioritarian political philosophy, because it is concerned only with the future and focuses only on health rather than well-being in general.

Issues, Challenges and Opportunities for Economic Evaluations of Orphan Drugs in Rare Diseases: An Umbrella Review.

BACKGROUND AND OBJECTIVES: There are significant challenges when obtaining clinical and economic evidence for health technology assessments of rare diseases. Many of them have been highlighted in previous systematic reviews but they have not been summarised in a comprehensive manner. For all stakeholders working with rare diseases, it is important to be aware and understand these issues. The objective of this review is to identify the main challenges for the economic evaluation of orphan drugs in rare diseases. METHODS: An umbrella review of systematic reviews of economic studies concerned with orphan and ultra-orphan drugs was conducted. Studies that were not systematic reviews, or on advanced therapeutic medicinal products, personalised medicines or other interventions that were not considered orphan drugs were excluded. The database searches included publications from 2010 to 2023, and were conducted in MEDLINE, EMBASE and the Cochrane library using filters for systematic reviews, and economic evaluations and models. These filters were combined with search terms for rare diseases and orphan drugs. A hand search supplemented the literature searches. The findings were reported by a compliant Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram. RESULTS: Two hundred and eighty-two records were identified from the literature searches, of which 64 were duplicates, whereas five reviews were identified from the hand search. A total of 36 reviews were included after screening against inclusion/exclusion criteria, 35 from literature searches and one from hand searching. Of those studies 1, 27 and 8 were low, moderate and high quality, respectively. The reviews highlight the scarcity of evidence for health economic parameters, for example, clinical effectiveness, costs, quality of life and the natural history of disease. Health economic evaluations such as cost-effectiveness and budget-impact analyses were scarce, and generally low-to-moderate quality. The causes were limited health economic parameters, together with publications bias, especially for cost-effectiveness analyses. CONCLUSIONS: The results highlighted issues around a considerable paucity of evidence for economic evaluations and few cost-effectiveness analyses, supporting the notion that a paucity of evidence makes economic evaluations of rare diseases more challenging compared with more prevalent diseases. Furthermore, we provide recommendations for more sustainable approaches in economic evaluations of rare diseases.

Application of Multi-Criteria Decision Analysis (MCDA) to Prioritize Real-World Evidence Studies for Health Technology Management: Outcomes and Lessons Learned by the Canadian Real-World Evidence for Value of Cancer Drugs (CanREValue) Collaboration.

Multi-criteria decision analysis (MCDA) is a value assessment tool designed to help support complex decision-making by incorporating multiple factors and perspectives in a transparent, structured approach. We developed an MCDA rating tool, consisting of seven criteria evaluating the importance and feasibility of conducting potential real-world evidence (RWE) studies aimed at addressing uncertainties stemming from initial cancer drug funding recommendations. In collaboration with the Canadian Agency for Drugs and Technologies in Health's Provincial Advisory Group, a validation exercise was conducted to further evaluate the application of the rating tool using RWE proposals varying in complexity. Through this exercise, we aimed to gain insight into consensus building and deliberation processes and to identify efficiencies in the application of the rating tool. An experienced facilitator led a multidisciplinary committee, consisting of 11 Canadian experts, through consensus building, deliberation, and prioritization. A total of nine RWE proposals were evaluated and prioritized as low (n = 4), medium (n = 3), or high (n = 2) priority. Through an iterative process, efficiencies and recommendations to improve the rating tool and associated procedures were identified. The refined MCDA rating tool can help decision-makers prioritize important and feasible RWE studies for research and can enable the use of RWE for the life-cycle evaluation of cancer drugs.