Health Technology Assessment Agencies Research Articles

A Systematic Review of Methods and Practice for Integrating Maternal, Fetal, and Child Health Outcomes, and Family Spillover Effects into Cost-Utility Analyses.

Maternal-perinatal interventions delivered during pregnancy or childbirth have unique characteristics that impact the health-related quality of life (HRQoL) of the mother, fetus, and newborn child. However, maternal-perinatal cost-utility analyses (CUAs) often only consider either maternal or child health outcomes. Challenges include, but are not limited to, measuring fetal, newborn, and infant health outcomes, and assessing their impact on maternal HRQoL. It is also important to recognize the impact of maternal-perinatal health on family members' HRQoL (i.e., family spillover effects) and to incorporate these effects in maternal-perinatal CUAs. The aim was to systematically review the methods used to include health outcomes of pregnant women, fetuses, and children and to incorporate family spillover effects in maternal-perinatal CUAs. A literature search was conducted in Medline, Embase, EconLit, Cochrane Collection, Cumulative Index to Nursing and Allied Health Literature (CINAHL), International Network of Agencies for Health Technology Assessment (INAHTA), and the Pediatric Economic Database Evaluation (PEDE) databases from inception to 2020 to identify maternal-perinatal CUAs that included health outcomes for pregnant women, fetuses, and/or children. The search was updated to December 2022 using PEDE. Data describing how the health outcomes of mothers, fetuses, and children were measured, incorporated, and reported along with the data on family spillover effects were extracted. Out of 174 maternal-perinatal CUAs identified, 62 considered the health outcomes of pregnant women, and children. Among the 54 quality-adjusted life year (QALY)-based CUAs, 12 included fetal health outcomes, the impact of fetal loss on mothers' HRQoL, and the impact of neonatal demise on mothers' HRQoL. Four studies considered fetal health outcomes and the effects of fetal loss on mothers' HRQoL. One study included fetal health outcomes and the impact of neonatal demise on maternal HRQoL. Furthermore, six studies considered the impact of neonatal demise on maternal HRQoL, while four included fetal health outcomes. One study included the impact of fetal loss on maternal HRQoL. The remaining 26 only included the health outcomes of pregnant women and children. Among the eight disability-adjusted life year (DALY)-based CUAs, two measured fetal health outcomes. Out of 174 studies, only one study included family spillover effects. The most common measurement approach was to measure the health outcomes of pregnant women and children separately. Various approaches were used to assess fetal losses in terms of QALYs or DALYs and their impact on HRQoL of mothers. The most common integration approach was to sum the QALYs or DALYs for pregnant women and children. Most studies reported combined QALYs and incremental QALYs, or DALYs and incremental DALYs, at the family level for pregnant women and children. Approximately one-third of maternal-perinatal CUAs included the health outcomes of pregnant women, fetuses, and/or children. Future CUAs of maternal-perinatal interventions, conducted from a societal perspective, should aim to incorporate health outcomes for mothers, fetuses, and children when appropriate. The various approaches used within these CUAs highlight the need for standardized measurement and integration methods, potentially leading to rigorous and standardized inclusion practices, providing higher-quality evidence to better inform decision-makers about the costs and benefits of maternal-perinatal interventions. Health Technology Assessment agencies may consider providing guidance for interventions affecting future lives in future updates.

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

Artificial intelligence (AI)-based medical devices have garnered attention due to their ability to revolutionize medicine. Their health technology assessment framework is lacking. This study aims to analyze the suitability of each health technology assessment (HTA) domain for the assessment of AI-based medical devices. 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. 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). 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.

Methods for Indirect Treatment Comparison: Results from a Systematic Literature Review.

Health technology assessment (HTA) agencies express a clear preference for randomized controlled trials when assessing the comparative efficacy of two or more treatments. However, an indirect treatment comparison (ITC) is often necessary where a direct comparison is unavailable or, in some cases, not possible. Numerous ITC techniques are described in the literature. A systematic literature review (SLR) was conducted to identify all the relevant literature on existing ITC techniques, provide a comprehensive description of each technique and evaluate their strengths and limitations from an HTA perspective in order to develop guidance on the most appropriate method to use in different scenarios. Electronic database searches of Embase and PubMed, as well as grey literature searches, were conducted on 15 November 2021. Eligible articles were peer-reviewed papers that specifically described the methods used for different ITC techniques and were written in English. The review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 73 articles were included in the SLR, reporting on seven different ITC techniques. All reported techniques were forms of adjusted ITC. Network meta-analysis (NMA) was the most frequently described technique (in 79.5% of the included articles), followed by matching-adjusted indirect comparison (MAIC) (30.1%), network meta-regression (24.7%), the Bucher method (23.3%), simulated treatment comparison (STC) (21.9%), propensity score matching (4.1%) and inverse probability of treatment weighting (4.1%). The appropriate choice of ITC technique is critical and should be based on the feasibility of a connected network, the evidence of heterogeneity between and within studies, the overall number of relevant studies and the availability of individual patient-level data (IPD). MAIC and STC were found to be common techniques in the case of single-arm studies, which are increasingly being conducted in oncology and rare diseases, whilst the Bucher method and NMA provide suitable options where no IPD is available. ITCs can provide alternative evidence where direct comparative evidence may be missing. ITCs are currently considered by HTA agencies on a case-by-case basis; however, their acceptability remains low. Clearer international consensus and guidance on the methods to use for different ITC techniques is needed to improve the quality of ITCs submitted to HTA agencies. ITC techniques continue to evolve quickly, and more efficient techniques may become available in the future.

Barriers and Facilitators of Using R for Decision Analytic Modeling in Health Technology Assessment: Focus Group Results.

Decision models for health technology assessment (HTA) are largely submitted to HTA agencies using commercial software, which has known limitations. The use of the open-source programming language R has been suggested because of its efficiency, transparency, reproducibility, and ability to consider complex analyses. However, its use in HTA remains limited. This qualitative study aimed to explore the main reasons for this slow uptake of R in HTA and identify tangible facilitators. We undertook two semi-structured focus group discussions with 24 key stakeholders from government agencies, consultancy, pharmaceutical companies, and academia. Two 1.5-hour discussions reflected on barriers identified in a previous study and highlighted additional barriers. Discussions were recorded and semi-transcribed, and data were organized and summarized into key themes. Human resources constraints were identified as a key barrier, including a lack of training, prioritization and collaboration, and resistance to change. Another key barrier was the lack of acceptance, or clear guidance, around submissions in R by HTA agencies. Participants also highlighted a lack of communication around accepted packages and decision model structures, and between HTA agencies on standard decision modeling structures. There is a need for standardization, which can facilitate decision model sharing, coding homogeneity, and improved country adaptations. The creation of training materials and tailored workshops was identified as a key short-term facilitator. Increased communication and engagement of stakeholders could also facilitate the use of R by identifying needs and opportunities, encouraging HTA agencies to address structural barriers, and increasing incentives to use R.

Economic evaluation of non-invasive liver tests for the diagnosis of liver fibrosis in chronic liver diseases: a systematic review protocol.

The objective of this review is to determine the costs and benefits of non-invasive liver tests vs liver biopsy in patients with chronic liver diseases. Hepatic diseases can lead to liver fibrosis, cirrhosis, and hepatocellular carcinoma. In the past, liver biopsy was the only option for diagnosing fibrosis degree. Liver biopsy is an invasive procedure that depends on the sample size to be able to deliver an accurate diagnosis. In recent years, non-invasive liver tests have been increasingly used to estimate liver fibrosis degree; however, there is a lack of economic assessments of technology implementation outcomes. This review will include partial (cost studies) and complete economic evaluation studies on hepatitis B, hepatitis C, alcoholic liver disease, and non-alcoholic fatty liver disease that compare non-invasive liver tests with liver biopsies. Studies published in English, French, Spanish, German, Italian, or Portuguese will be included. No date limits will be applied to the search. This review will identify published and unpublished studies. Published studies will be identified using MEDLINE (PubMed), Cochrane Library (CENTRAL), Embase, Web of Science, Scopus, and LILACS. Sources of unpublished studies and gray literature will include sources from health technology assessment agencies, clinical practice guidelines, regulatory approvals, advisories and warnings, and clinical trial registries, as well as Google Scholar. Two independent reviewers will screen and assess studies, and extract and critically appraise the data. Data extracted from the included studies will be analyzed and summarized to address the review objective using narrative text, and the JBI dominance ranking matrix. PROSPERO CRD42023404278.

Methods for Including Adverse Events in Economic Evaluations: Suggestions for Improvement

ObjectiveInclusion of relevant effectiveness and safety outcomes in economic evaluation of health technologies is required to aid efficient healthcare decisions. Our objective was to identify the key issues related to the inclusion of adverse events (AEs) in economic evaluation and explore perspectives for good practice recommendations to handle these issues. MethodsWe focused on the frequently encountered methodological issues related to the integration of AEs in economic evaluations of health technologies. We distinguished the following elements: the incorporation of AEs in decision models, the terminology of AEs, the estimation of AEs consequences in terms of quality of life (QoL) and costs, and the exploration of the uncertainty related to the impact of AEs on the economic results. ResultsWe illustrated and discussed each of the identified issues by giving health technology assessment examples. We focused on the extent to which the integration of AEs in decision models can be improved by dealing with the lack of relevant real-world safety data, estimating the consequences of AEs (eg, for costs and QoL loss), exploring the impacts of AEs that are not adequately captured in current measurement of health-related QoL, and identifying the need for development of a good terminology of relevant types of AEs to be incorporated in economic evaluation. ConclusionBased on a reflection the key methodological issues related to the incorporation of adverse drug events in economic evaluations, we suggested several recommendations to serve a starting point for health technology assessment agencies and researchers to develop good research practices in this field.

Understanding Canadian stakeholders’ views on measuring and valuing health for children and adolescents: a qualitative study

ObjectiveValuing child health is critical to assessing the value of healthcare interventions for children. However, there remain important methodological and normative issues. This qualitative study aimed to understand the views of Canadian stakeholders on these issues.MethodsStakeholders from health technology assessment (HTA) agencies, pharmaceutical industry representatives, healthcare providers, and academic researchers/scholars were invited to attend an online interview. Semi-structured interviews were designed to focus on: (1) comparing the 3-level and 5-level versions of the EQ-5D-Y; (2) source of preferences for valuation (adults vs. children); (3) perspective of valuation tasks; and (4) methods for valuation (discrete choice experiment [DCE] and its variants versus time trade-off [TTO]). Participants were probed to consider HTA guidelines, cognitive capacity, and potential ethical concerns. All interviews were recorded and transcribed verbatim. Framework analysis with the incidence density method was used to analyze the data.ResultsFifteen interviews were conducted between May and September 2022. 66.7% (N = 10) of participants had experience with economic evaluations, and 86.7% (N = 13) were parents. Eleven participants preferred the EQ-5D-Y-5L. 12 participants suggested that adolescents should be directly involved in child health valuation from their own perspective. The participants were split on the ethical concerns. Eight participants did not think that there was ethical concern. 11 participants preferred DCE to TTO. Among the DCE variants, 6 participants preferred the DCE with duration to the DCE with death.ConclusionsMost Canadian stakeholders supported eliciting the preferences of adolescents directly from their own perspective for child health valuation. DCE was preferred if adolescents are directly involved.

Using Patient Preferences in Health Technology Assessment: Evaluating Quality-Adjusted Survival Equivalents (QASE) for the Quantification of Non-health Benefits.

Interest in using patient preference (PP) data alongside traditional economic models in health technology assessment (HTA) is growing, including using PP data to quantify non-health benefits. However, this is limited by a lack of standardised methods. In this article, we describe a method for using discrete choice experiment (DCE) data to estimate the value of non-health benefits in terms of quality-adjusted survival equivalence (QASE), which is consistent with the concept of value prevalent among HTA agencies. We describe how PP data can be used to estimate QASE, assess the ability to test the face-validity of QASE estimates of changes in mode of administration calculated from five published DCE oncology studies and review the methodological and normative considerations associated with using QASE to support HTA. We conclude that QASE may have some methodological advantages over alternative methods, but this requires DCEs to estimate second-order effects between length and quality of life. In addition, empirical work has yet to be undertaken to substantiate this advantage and demonstrate the validity of QASE. Further work is also required to align QASE with normative objectives of HTA agencies. Estimating QASE would also have implications for the conduct of DCEs, including standardising and defining more clear attribute definitions.

Added benefit and revenues of oncology drugs approved by the European Medicines Agency between 1995 and 2020: retrospective cohort study

ObjectivesTo evaluate the added benefit and revenues of oncology drugs, explore their association, and investigate potential discrepancies between added benefit and revenues across different approval pathways of the European Medicines...

Use of Healthcare Claims Data to Generate Real-World Evidence on Patients With Drug-Resistant Epilepsy: Practical Considerations for Research.

Objectives: Regulatory bodies, health technology assessment agencies, payers, physicians, and other decision-makers increasingly recognize the importance of real-world evidence (RWE) to provide important and relevant insights on treatment patterns, burden/cost of illness, product safety, and long-term and comparative effectiveness. However, RWE generation requires a careful approach to ensure rigorous analysis and interpretation. There are limited examples of comprehensive methodology for the generation of RWE on patients who have undergone neuromodulation for drug-resistant epilepsy (DRE). This is likely due, at least in part, to the many challenges inherent in using real-world data to define DRE, neuromodulation (including type implanted), and related outcomes of interest. We sought to provide recommendations to enable generation of robust RWE that can increase knowledge of "real-world" patients with DRE and help inform the difficult decisions regarding treatment choices and reimbursement for this particularly vulnerable population. Methods: We drew upon our collective decades of experience in RWE generation and relevant disciplines (epidemiology, health economics, and biostatistics) to describe challenges inherent to this therapeutic area and to provide potential solutions thereto within healthcare claims databases. Several examples were provided from our experiences in DRE to further illustrate our recommendations for generation of robust RWE in this therapeutic area. Results: Our recommendations focus on considerations for the selection of an appropriate data source, development of a study timeline, exposure allotment (specifically, neuromodulation implantation for patients with DRE), and ascertainment of relevant outcomes. Conclusions: The need for RWE to inform healthcare decisions has never been greater and continues to grow in importance to regulators, payers, physicians, and other key stakeholders. However, as real-world data sources used to generate RWE are typically generated for reasons other than research, rigorous methodology is required to minimize bias and fully unlock their value.

Use of Healthcare Claims Data to Generate Real-World Evidence on Patients With Drug-Resistant Epilepsy: Practical Considerations for Research

Objectives: Regulatory bodies, health technology assessment agencies, payers, physicians, and other decision-makers increasingly recognize the importance of real-world evidence (RWE) to provide important and relevant insights on treatment patterns, burden/cost of illness, product safety, and long-term and comparative effectiveness. However, RWE generation requires a careful approach to ensure rigorous analysis and interpretation. There are limited examples of comprehensive methodology for the generation of RWE on patients who have undergone neuromodulation for drug-resistant epilepsy (DRE). This is likely due, at least in part, to the many challenges inherent in using real-world data to define DRE, neuromodulation (including type implanted), and related outcomes of interest. We sought to provide recommendations to enable generation of robust RWE that can increase knowledge of “real-world” patients with DRE and help inform the difficult decisions regarding treatment choices and reimbursement for this particularly vulnerable population. Methods: We drew upon our collective decades of experience in RWE generation and relevant disciplines (epidemiology, health economics, and biostatistics) to describe challenges inherent to this therapeutic area and to provide potential solutions thereto within healthcare claims databases. Several examples were provided from our experiences in DRE to further illustrate our recommendations for generation of robust RWE in this therapeutic area. Results: Our recommendations focus on considerations for the selection of an appropriate data source, development of a study timeline, exposure allotment (specifically, neuromodulation implantation for patients with DRE), and ascertainment of relevant outcomes. Conclusions: The need for RWE to inform healthcare decisions has never been greater and continues to grow in importance to regulators, payers, physicians, and other key stakeholders. However, as real-world data sources used to generate RWE are typically generated for reasons other than research, rigorous methodology is required to minimize bias and fully unlock their value.

Real-World Evidence to Inform Regulatory Decision Making: A Scoping Review.

Real-world evidence (RWE) is increasingly considered in regulatory decision making. When, and to which extent, RWE is considered relevant by regulators likely depends on many factors. This review aimed to identify factors that make RWE necessary or desirable to inform regulatory decision making. A scoping review was conducted using literature databases (PubMed, Embase, Emcare, Web of Science, and Cochrane Library) and websites of regulatory agencies, health technology assessment agencies, research institutes, and professional organizations involved with RWE. Articles were included if: (1) they discussed factors or contexts that impact whether RWE could be necessary or desirable in regulatory decision making; (2) focused on pharmacological or biological interventions in humans; and (3) considered decision making in Europe or North America, or without a focus on a specific region. We included 118 articles in the scoping review. Two major themes and six subthemes were identified. The first theme concerns questions addressable with RWE, with subthemes epidemiology and benefit-risk assessment. The second theme concerns contextual factors, with subthemes feasibility, ethical considerations, limitations of available evidence, and disease and treatment-specific aspects. Collectively, these themes encompassed 43 factors influencing the need for RWE in regulatory decisions. Although single factors may not make RWE fully necessary, their cumulative influence could make RWE essential and pivotal in regulatory decision making. This overview contributes to ongoing discussions emphasizing the nuanced interplay of factors influencing the necessity or desirability of RWE to inform regulatory decision making.

Acceptability of Using Real-World Data to Estimate Relative Treatment Effects in Health Technology Assessments: Barriers and Future Steps

ObjectivesEvidence about the comparative effects of new treatments is typically collected in randomized controlled trials (RCTs). In some instances, RCTs are not possible, or their value is limited by an inability to capture treatment effects over the longer term or in all relevant population subgroups. In these cases, nonrandomized studies (NRS) using real-world data (RWD) are increasingly used to complement trial evidence on treatment effects for health technology assessment (HTA). However, there have been concerns over a lack of acceptability of this evidence by HTA agencies. This article aims to identify the barriers to the acceptance of NRS and steps that may facilitate increases in the acceptability of NRS in the future. MethodsOpinions of the authorship team based on their experience in real-world evidence research in academic, HTA, and industry settings, supported by a critical assessment of existing studies. ResultsBarriers were identified that are applicable to key stakeholder groups, including HTA agencies (eg, the lack of comprehensive methodological guidelines for using RWD), evidence generators (eg, avoidable deviations from best practices), and external stakeholders (eg, data controllers providing timely access to high-quality RWD). Future steps that may facilitate future acceptability of NRS include improvements in the quality, integration, and accessibility of RWD, wider use of demonstration projects to highlight the value and applicability of nonrandomized designs, living, and more detailed HTA guidelines, and improvements in HTA infrastructure relating to RWD. ConclusionNRS can represent a crucial source of evidence on treatment effects for use in HTA when RCT evidence is limited.

Real-world evidence for coverage determination of treatments for rare diseases

Health technology assessment (HTA) decisions for pharmaceuticals are complex and evolving. New rare disease treatments are often approved more quickly through accelerated approval schemes, creating more uncertainties about clinical evidence and budget impact at the time of market entry. The use of real-world evidence (RWE), including early coverage with evidence development, has been suggested as a means to support HTA decisions for rare disease treatments. However, the collection and use of RWE poses substantial challenges. These challenges are compounded when considered in the context of treatments for rare diseases. In this paper, we describe the methodological challenges to developing and using prospective and retrospective RWE for HTA decisions, for rare diseases in particular. We focus attention on key elements of study design and analyses, including patient selection and recruitment, appropriate adjustment for confounding and other sources of bias, outcome selection, and data quality monitoring. We conclude by offering suggestions to help address some of the most vexing challenges. The role of RWE in coverage and pricing determination will grow. It is, therefore, necessary for researchers, manufacturers, HTA agencies, and payers to ensure that rigorous and appropriate scientific principles are followed when using RWE as part of decision-making.

Tools for assessing quality of studies investigating health interventions using real-world data: a literature review and content analysis

ObjectivesWe aimed to identify existing appraisal tools for non-randomised studies of interventions (NRSIs) and to compare the criteria that the tools provide at the quality-item level.DesignLiterature review through three approaches:...

AOTMiT reimbursement recommendations compared to other HTA agencies

Our objective was to compare AOTMiT (Polish: Agencja Oceny Technologii Medycznych i Taryfikacji) recommendations to other HTA (Health Technology Assessment) agencies for newly registered drugs and new registration indications issued by the European Medicines Agency between 2014 and 2019. The study aims to assess the consistency and justifications of AOTMiT recommendations compared to that of other HTA agencies in 11 countries. A total of 2496 reimbursement recommendations published by 12 HTA agencies for 464 medicinal products and 525 indications were analyzed. Our analysis confirmed that the Polish AOTMiT agency seems to bear the closest resemblance to the corresponding HTA agencies from Canada (CADTH) and New Zealand (PHARMAC), when it comes to the outcome of HTA recommendations (positive or negative). Poland had a general scheme for justifying recommendations, similar to that of Ireland—four aspects (i.e., clinical efficacy, safety profile, cost-effectiveness, and impact on the payer’s budget) are important for Poland when formulating the final decision. Compared to other countries, Poland shows a noticeably different pattern of justifying reimbursement recommendations, as revealed primarily in terms of budget impact and somewhat less so for cost-effectiveness rationales.

How to mobilise users' experiential knowledge in the evaluation of advanced technologies and practices in Quebec? The example of the permanent users' and relatives' panel.

With the purpose of supporting scientific professionals and helping them to better integrate the expertise of users in their work, a users' and relatives' panel (URP) was set up at the National Institute for Excellence in Health and Social Services in Quebec (INESSS), Canada for the social services and mental health directorate. URPs are advisory structures that mobilise the experiential knowledge of people affected by various issues. The objective of this study is to assess from a diverse stakeholders' perceptions: (1) the experience of developing and implementing the URP within the context of an Agencies for Health Technology Assessment and Assessment of Social Services (AHTAASS), (2) the contribution of such a URP, (3) the challenges encountered and (4) the perspectives of improvement for the following years. We conducted a qualitative descriptive evaluation study. Nineteen interviews were conducted: six with URP members and 13 with staff representatives. The documents related to the creation of the panel, the URP minutes summarising the discussions and the reports published during that period were collected and analysed. Following a preliminary round of data analysis, a debriefing meeting was conducted with a few participants to validate the results. The panel was set up as part of the INESSS' desire to better integrate experiential knowledge into its recommendations. Twelve projects were presented to the panel on various themes. The URP enabled health professionals to consider dimensions they had not identified, to better integrate the experiential data collected from users into their work and to develop recommendations that made more sense to users. Panel members and INESSS professionals learned to work together, moving the working methods from consultation to collaboration and even coconstruction. Based on the panel's significant contribution, the INESSS decided to maintain it and to strengthen its place in its system to better integrate the experiential knowledge of users into its work. This research illustrates how AHTAASS can set up a URP composed exclusively of users, and how it can contribute and be evaluated. It shows that URPs are structures that value the sharing of experiential knowledge of its members, humanise decision-making and give meaning to the work done by scientific professionals. One patient-researcher has contributed to the preparation and writing of this manuscript.

Assessing medical devices: a qualitative study from the validate perspective.

Our objective was to explore procedures and methods used at health technology assessment (HTA) agencies for assessing medical devices and the underlying views of HTA practitioners about appropriate methodology to identify challenges in adopting new methodologies for assessing devices. We focused on the role of normative commitments of HTA practitioners in the adoption of new methods. An online survey, including questions on procedures, scoping, and assessments of medical devices, was sent to members of the International Network of Agencies for Health Technology Assessment. Interviews were conducted with survey respondents and HTA practitioners involved in assessments of transcatheter aortic valve implantation to gain an in-depth understanding of choices made and views about assessing medical devices. Survey and interview questions were inspired by the "values in doing assessments of health technologies" approach towards HTA, which states that HTA addresses value-laden questions and information. The current practice of assessing medical devices at HTA agencies is predominantly based on procedures, methods, and epistemological principles developed for assessments of drugs. Both practical factors (available time, demands of decision-makers, existing legal frameworks, and HTA guidelines), as well as commitments of HTA practitioners to principles of evidence-based medicine, make the adoption of a new methodology difficult. There is a broad recognition that assessments of medical devices may need changes in HTA methodology. In order to realize this, the HTA community may require both a discussion on the role, responsibility, and goals of HTA, and resulting changes in institutional context to adopt new methodologies.

Health technology assessment in traditional and complementary medicine: a scoping review of international activity and examples of acupuncture.

Traditional therapies are crucial in maintaining and improving human well-being. China's healthcare policymakers are attempting to use health technology assessment (HTA) as a decision-making supportive tool. The value assessment framework for Chinese patent medicine (CPM) has been developed and is being adopted and validated widely by research institutions. Subsequently, the healthcare decision-makers particularly hanker for the value framework of traditional non-pharmacological therapies. To construct a practical value framework for traditional non-pharmacological therapies, a scoping review methodology was adopted to identify the evaluation domains and obstacles. A search, screening, and analysis process was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Evidence was retrieved from scientific databases and HTA agencies' websites. The search strategy identified 5 guidelines records and 17 acupuncture HTA reports. By synthesizing the valuable reports of CPM and acupuncture evaluation in representative countries, this study found that Mainland China was promoting the comprehensive value assessment of CPM, whereas the United Kingdom, Singapore, Canada, the United States, and Malaysia had carried out the HTA evaluation of acupuncture for various conditions among which chronic pain was the most common. UK and Singapore applied the HTA results to support acupuncture reimbursement decisions. Three domains, including safety, effectiveness, and economy, were commonly adopted. The identified biggest challenge of evaluating traditional non-pharmacological therapies is the scarce high-quality clinical evidence. This study identified value domains and issues of traditional therapies, and pointed out future research implications, to promote the development value framework of traditional therapies.

Economic evaluation of fixed-dose drug combinations: A systematic review

This study aimed to review the quality of published evidence on the cost-effectiveness of fixed-dose drug combinations (FDCs), summarize key methodologic assumptions, and make recommendations for future economic evaluations of FDCs. The search was conducted on four databases, namely Medline, Embase, Web of Science, and the International Network of Agencies for Health Technology Assessment. Studies were selected if they assessed the cost-effectiveness of FDCs compared to one or more single active ingredient dosage forms or placebo. The Consolidated Health Economic Evaluation Reporting Standards 2022 checklist was utilized for evaluating the quality of studies. The study protocol was registered in PROSPERO (CRD42021295388). A total of 39 studies were eligible for inclusion in the review. While most of the studies (n = 29) reported that FDCs are cost-effective, the comparator in the economic evaluations was not justified explicitly in most studies (n = 34). Modelling that examined cost-effectiveness did not incorporate medication adherence (n = 22), failing to consider a key advantage of FDCs. The majority of studies investigating FDCs reported that they were cost-effective interventions. However, further economic evaluations based on long-term clinical trials with larger populations are necessary. Also, future economic studies should incorporate superior treatment adherence with FDC into the model structure.