Health Technology Assessment Agencies Research Articles

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.

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.

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.

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.

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.

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.

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.

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:...

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.

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 2494 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

AbstractIntroductionWith 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.ObjectivesThe 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.MethodologyWe 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.ResultsThe 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.ConclusionThis 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.Patient or Public ContributionOne patient–researcher has contributed to the preparation and writing of this manuscript.

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.

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

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. 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). 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). 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. 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.

Synthesis of relevant information around non-core domains to support Multi-Criteria Decision Analysis (MCDA) for decision making.

Countries fundamentally base macro and micro decision making in the field of health on economic considerations, the budgetary impact of technologies being a major criterion. Nevertheless, the value of the technology of interest and its dimensions are more complex if we seek to take decisions based on the value itself. The use of structured and explicit approaches that require the assessment of multiple criteria that reflect the dimensions of this value may significantly improve the quality of the decision making. Multi-criteria decision analysis (MCDA) is a complementary decision-making tool that is able to systematically incorporate dimensions or domains such as ethical, organisational, legal, environmental and social considerations, as well as costs and benefits of medical interventions, together with the distinct perspectives of the interested parties. The objective of this article is to propose the implementation of analysis of non-core domains, in reports of Health Technology Assessment (HTA) agencies/units. To assess the scientific evidence on MCDA techniques a systematic review was conducted using structured searches in biomedical databases and websites of various HTA organisations. A consensus group was held using the nominal group technique and involving users of healthcare services, providers, managers and academics. Complementary, a survey was sent to HTA agencies to ascertain the degree of implementation of MCDA in their methods. 42 articles reporting the use of non-core criteria for the assessment of health technologies were included in the analysis. From these articles, a total of 216 non-core criteria were retrieved and categorised into domains by the researchers, and of these, 56 were classified as socioeconomic, 59 as organisational, 10 as legal, 8 as environmental and 47 as ethical, while 36 were considered to relate to other domains. The consensus group, based on the 216 non-core criteria obtained from the systematic review, proposed, and defined 26 criteria that participants considered necessary for decision making in healthcare. The consensus group did not consider that any of the domains should be given more weight than others or that any individual criteria should dominate. These approaches can serve as a framework of reference for a well-structured systematic discussion concerning the basis of individual criteria and the evidence supporting them.