Life-cycle health technology assessment (HTA) requires an index economic model to establish how estimated cost-effectiveness evolves with emerging evidence. We developed an open-source index economic evaluation of entrectinib, a tumor-agnostic therapy with conditional market authorization. Our objective was to replicate the initial HTA report from publicly available information, aiming to identify key operational and methodological aspects for operationalizing life-cycle decision-making.

We used partitioned survival analysis to determine tumor-agnostic and tumor-specific cost-effectiveness, using publicly available HTA reviews for parameterization. We estimated incremental costs in 2021 Canadian and US dollars (CAD and USD) from a public-payer healthcare perspective, quality-adjusted life years (QALYs), and incremental net monetary benefit (INMB). We assessed the impact of treatment effectiveness, extrapolation assumptions, and next-generation sequencing (NGS) costs.

One-third of the parameters (n = 30) were unavailable in the Canadian reimbursement review and were sourced from international reviews. Tumor-agnostic incremental costs were CAD 68,451 (95 percent confidence interval: 35,466, 92,155) and USD 54,608 (28,294, 73,518), and QALYs were 0.13 (−0.42, 0.42), yielding INMB CAD −55,803 at 100,000/QALY (USD −44,518). Full extrapolation of treatment effectiveness also yielded negative INMB (CAD −66,664). Inclusion of NGS costs diminished the expected value. Heterogeneity was considerable across tumor indications.

We developed an open-source index economic evaluation to operationalize life-cycle HTA for a conditionally authorized tumor-agnostic therapy. Our findings outline key operational and methodological considerations necessary for the development of index economic models that support life-cycle HTA, offering insights into their potential integration into regular HTA and policy decision-making processes.

To systematize the information and perspectives shared during the 2024 LATAM policy forum, which explored advancements in horizon scanning and early dialogue processes in the region, by analyzing the main discussion and identifying the main lessons.

This article is based on the discussions and background materials provided during the 1.5 days in-person 2024 Latin American Policy Forum (59 representatives from 11 countries). We gathered and systematized the information shared during the forum, including the results of a pre-forum survey. The Forum agenda included keynote presentations, breakout group activities, and plenary discussions to identify the main lessons and key messages from all different stakeholders’ points of view.

The forum highlighted the growing recognition of the need for structured horizon scanning and early dialogue processes in Latin America. Key barriers were identified, including the absence of clear legal frameworks, limited data availability, and the need for capacity-building. Potential solutions included fostering regional cooperation, improving transparency, and creating pilot programs for early engagement. Engaging patients and the pharmaceutical industry was deemed essential for trust and foster alignment between HTA agencies and regulators.

Horizon scanning and early dialogue represent critical tools for improving health system preparedness and aligning innovation with local needs. Their implementation, however, requires coordinated efforts across multiple stakeholders, enhanced dialogue, and the development of supportive legal and regulatory frameworks.

Health technology assessment of medical devices (HTA-MDs) presents unique challenges compared to pharmaceuticals. Total MD expenditure continues to grow in Europe, and countries typically conduct their own HTA-MDs evaluations, with varying institutionalization arrangements. European Union’s (EU’s) HTA Regulation aims to establish collaborative clinical assessments across Member States, potentially expediting the path from EU safety certification of MDs to pricing and reimbursement decisions. This study aims to identify emergent configurations among institutionalizations of HTA-MDs in the EU, European Economic Area (EEA), and European Free Trade Association (EFTA) countries.

Publicly available data were cross-sectionally collected for EU, EEA, and EFTA countries until August 2024 to allow a cross-country analysis of HTA-MDs institutionalizations. Countries were included if they had at least one publicly mandated body for HTA-MDs. Data sources were scientific databases, institutional websites, and HTA bodies’ documentation. A framework of 16 elements, qualitatively describing the institutionalization of HTA-MDs, was developed based on a document review and used as a dataset for agglomerative hierarchical cluster analysis to identify patterns of HTA-MDs institutionalization.

The 21 included countries formed three clusters: Cluster 1 featured regulatory-focused, legally bound HTA-MDs systems with mandatory assessments determining reimbursement decisions; Cluster 2 was characterized by regulatory functions, external expert collaboration, formal prioritization processes, and organized Horizon Scanning; Cluster 3 showed recommendatory functions, nonmandatory assessments, and limited impact on reimbursement decisions.

HTA-MDs institutionalizations could benefit from implementing prioritization processes of evaluations, establishing networks of collaborative assessment centers, and ensuring links between evaluations and reimbursement decisions.

Evaluate how a foundation-supported fellowship employs early health-technology assessment (eHTA) to guide the development and positioning of emerging health innovations.

We reviewed all eHTA reports conducted under the Fellowship from 2018 to 2021 (n = 10), extracting technology class, development stage, economic modeling, and recommendations. In 2023, we conducted thirty-minute structured video interviews with developers of each technology (eleven invitees, ten responses). The interview comprised Likert questions on perceived usefulness and intention to update the model in later stages, and six open-ended questions on perceived advantages, implementation barriers, and downstream actions. Likert data were summarized descriptively; open-ended responses were summarized and discussed within the research team until consensus on key themes.

The eHTA subject technologies were four diagnostics, three therapeutics, two predictive algorithms, and one curative device, all preclinical. Analyses used six Markov or decision-tree frameworks, four hybrid models or simulations, and six value-based-pricing scenarios. Five technologies were potentially cost-effective, three conditionally cost-effective, one unlikely to be cost-effective without stronger evidence, and one cost-effective yet unlikely to break even. Eight developers rated eHTA “useful” or “very useful”; three had already leveraged results in grant or investor materials and two planned to do so when more data emerged. Reported barriers included evidence gaps, funding constraints, and misalignment with pharmaceutical partners on codevelopment strategies; two projects were discontinued.

eHTA supplies developers with early economic insight, but its guidance is most reliable when interpreted alongside budget impact, feasibility, regulatory, and adoption considerations.

Short-course regimens are currently explored to improve multidrug-resistant tuberculosis effects, reduce costs, as well as enhance patient adherence. Currently, we are determining the most cost-effective shorter regimen out of seven short-course regimens (6–9 months) to treat drug-resistant tuberculosis (DR-TB) compared to the current standard of care (SoC) 9- to 11-month regimen.

Cost-effectiveness of various short-course DR-TB treatment regimens, namely BEAT, BPaL, BPaLM, BPaLC, mBPaL1, mBPaL2, and mBPaL3, was compared to the current SoC in India. Decision tree model was used from a health system perspective. The information on various costs – such as preinvestigations, regimens, adverse drug reactions (ADRs) management, inpatient treatment – and on effect – such as clinical outcomes and ADRs – was collected from different published sources. It estimated costs, quality-adjusted life years, and incremental cost-effectiveness ratios (ICERs). Sensitivity analyses were performed to validate outcomes against the willingness-to-pay threshold.

When all the short-course regimens were compared with the current SoC regimen, the ICERs were ₹5,385, ₹2,014, ₹2,008, ₹2,435, ₹1,462, ₹1,159, and ₹1,895 for BEAT, BPaL, BPaLM, BPaLC, mBPaL1, mBPaL2, and mBPaL3, respectively. Among the short-course regimens, mBPaL2 is the dominant strategy, and mBPaL1 has extended dominance. For all Bedaquiline-containing regimens, the cost of the drug is a crucial factor in determining cost effectiveness. The cost-effectiveness acceptability curve showed that all shorter regimens were 100 percent cost-effective.

The implementation of Bedaquiline-based regimen to treat DR-TB has become more effective, shorter in duration, and less burdensome to the health system.

The rising cost of oncology care has motivated efforts to quantify the overall value of cancer innovation. This study aimed to apply the MACBETH approach to the development of a value assessment framework (VAF) for lymphoma therapies.

A multi-attribute value theory methodological process was adopted. Analogous MCDA steps developed by the International Society for Health Economics and Outcomes Research (ISPOR) were carried out and a diverse multi-stakeholder group was recruited to construct the framework. The criteria were identified through a systematic literature review and selected according to the importance score of each criterion given by stakeholders, related research and expert opinions. The MACBETH method was used to score the performance of alternatives by establishing value functions for each criterion and to assign weight to criteria.

Nine criteria were included in the final framework and a reusable model was built: quality adjusted life years (QALYs), median progression-free survival, objective response rate, the incidence of serious adverse events (grade 3–4), rates of treatment discontinuation due to adverse events, annual direct medical costs, dosage and administration, the number of alternative medicines with the same indication and mechanism, mortality of the disease. The weights of each criterion in the order presented above are 17.43 percent, 16.11 percent, 14.39 percent,13.54 percent,11.83 percent,11.30 percent,7.08 percent,4.59 percent, and 3.73 percent.

A criterion-based valuation framework was constructed using multiple perspectives to provide a quantitative assessment tool in facilitating the delivery of affordable and valuable lymphoma treatment. Further research is needed to optimize its use as part of policy-making.

Prioritization of health technologies for insurance coverage is usually based on explicit and implicit criteria. This study presents the development of the multi-criteria decision analysis (MCDA) model, the Iranian Health Insurance Benefit Optimization Model (IR-HIBOM), to inform the design of basic health insurance benefit packages.

An initial set of twenty-nine potential allocation criteria was identified through a review of available evidence and other relevant literature. Review of this set by three specialized panels yielded a final set of thirteen criteria. A cross-sectional survey using the best–worst scaling method was then fielded to 163 health system experts to evaluate their preferences regarding the relative importance of the allocation criteria. The mixed logit method was employed to determine the weight of the relative importance of each criterion. Subsequently, a multilevel criteria scoring framework was defined based on a review of similar models and input from a panel of five expert members of the study team. Finally, model’s appraisal was conducted.

Thirteen criteria, including relative safety, efficacy, disease severity, access to alternative health technologies, budget impacts, cost-effectiveness, quality of evidence, population size, age, job absenteeism, economic status, daily care needs, and ease-of-use/acceptance were selected. Cost-effectiveness and ease-of-use criteria had the highest and lowest relative importance weights, with 30.5 percent and 1 percent, respectively. Furthermore, scores were determined for the several levels of each criterion, and decision rules were defined for the cost-effectiveness and budget impact criteria. The final model’s appraisal, based on weighted scores of thirteen selected technologies, indicated that it was valid and applicable.

The IR-HIBOM demonstrated its potential utility in the health resource allocation.

The increasing relevance of horizon scanning (HS), early awareness (EA), and disinvestment (DIS) highlights the need for a structured approach to capacity building. Although these fields are essential for evidence-based policy decisions, a harmonized education and training framework to develop necessary competencies is lacking. This article presents the development of a curriculum designed to address this gap in training.

A transdisciplinary working group was established, drawing on international stakeholders from academia, the public sector, and industry. Using an iterative consensus-driven approach, the group developed a modular curriculum. The curriculum design incorporated best practices from existing education programs in related fields and emphasized case-based learning strategies to ensure contextual adaptability.

The resulting curriculum covers theoretical foundations, practical applications, and decision-making processes related to HS, EA, and DIS in eight modules. It supports diverse learner needs, including trainees, training institutions, and public and private organizations, and is designed to be flexible, scalable, and applicable across different regional and organizational contexts.

This curriculum initiative represents a major step toward harmonizing capacity building in HS, EA, and DIS. It fosters sustainability, enhances global health system preparedness, and provides a structured educational platform to support the effective integration of emerging health technologies and evidence-based disinvestment strategies.

In 2020, RWE4Decisions, a multi-stakeholder initiative commissioned by the Belgian payer, published stakeholder actions to support the generation, analysis, and interpretation of real-world evidence (RWE) to inform the decision making of health technology assessment (HTA) bodies/payers for highly innovative medicines in the European Union (EU). Since 2020, changes in the decision-making environment and advancements in RWE have created an impetus to update stakeholder actions for the EU and Canada.

RWE4Decisions’ experts led focus groups with individual stakeholder groups (HTA bodies/payers, pharmaceutical industry, clinicians, patients, registry holders, and data analytical experts). Each focus group crafted new actions for their stakeholder, then the actions were discussed and revised in a multi-stakeholder meeting, a public webinar, and a public consultation. Themes across actions and meetings were identified.

Detailed new actions for each stakeholder group are presented. Key themes identified are the need to address interorganizational fragmentation regarding secondary data use and methodologies to build robust RWE. HTA bodies/payers need to develop a common vision about the potential use of RWE. The role of the whole clinical team as primary data collectors is critical. Opportunities for scientific advice across the life cycle of a medicine are essential, and the implementation of RWE guidance related to HTA is paramount. Progress requires specific, operational actions and a collective effort by a variety of stakeholders.

Carrying out these actions will facilitate the development of methodological best practices for generating RWE to inform HTA of highly innovative medicines and build trust between stakeholders in the use of RWE.

Medicines and devices have significant negative impacts on the environment. Increasingly, Health Technology Assessment (HTA) agencies, which inform healthcare decision making, are expected to integrate environmental issues into their assessments. This study assessed how HTA agencies have responded to these calls, with a focus on two national agencies that have committed to this agenda.

This descriptive study was conducted using document review. All relevant documents from both agencies were systematically collected and analyzed using descriptive statistics and content analysis.

Thirty documents (2015–2024), from Canada’s Drug Agency (CDA) (17) and England’s National Institute for Health and Care Excellence (NICE) (13) that included environmental considerations were analyzed. Although no HTAs have assessed environmental data, primarily due to a lack of data and methods, documents demonstrate that CDA and NICE are employing varied strategies to incorporate environmental considerations through technology guidance. The agencies demonstrate both differences and similarities in approach: NICE focused on carbon and the use phase, whereas CDA focused on multiple environmental impacts across the lifecycle; both agencies are beginning to address the environmental impacts of devices, but there is a notable absence of medicines-related work.

This study demonstrates that the agencies are exploring alternative strategies to elevate attention to the environmental impacts of health technologies. Differences in focus (e.g., whether to prioritize carbon emissions) and shared inattention to medicines point to deeper tensions. Thus, although both agencies have taken important steps forward, much work remains to fully address the environmental harms of health technologies.

Patient involvement enhances transparency, legitimacy, and responsiveness in pharmaceutical reimbursement decisions. Guided by the mosaic model, this study recognizes effective patient engagement requires diverse context-specific approaches. Despite Taiwan’s National Health Insurance Administration (NHIA) implementing policies, gaps remain between intent and practice. This study evaluates NHIA’s incorporation of patient inputs into reimbursement decisions and examines factors influencing involvement.

We analyzed pharmaceutical company-initiated reimbursement submissions for catastrophic illnesses reviewed by the Pharmaceutical Benefit and Reimbursement Scheme Joint Committee (PBRS) from 2016 to 2023. Data sources included PBRS meeting records, the Online Patient Opinion Platform (OPOP), and NHIA notification E-mails. Generalized linear models identified predictors of patient involvement. The association between patient involvement and PBRS decisions was also explored.

Patient involvement occurred in 28.4 percent (80/282) of all submissions, increasing from 17 percent (2016) to 44 percent (2023). Despite aligning with OPOP criteria, patient involvement remained incomplete. Discussion-type submissions, oncology drugs, and new drug applications showed higher involvement, whereas autoimmune diseases and new indication submissions had lower involvement. Budget impact and innovation categories were not significant predictors in adjusted models. The presence of patient involvement was not significantly associated with the PBRS approval rate. Ad hoc analysis revealed increased involvement for new indications following policy expansion.

Despite NHIA’s efforts, patient involvement implementation remains suboptimal. Structured mechanisms and expanded patient involvement beyond high-profile submissions and PBRS are crucial to broaden patient involvement. This study provides practical insights for East Asian healthcare systems advancing patient involvement amid limited empirical research.

Evaluate the extent to which delivery constraints were considered during the health technology assessment (HTA) of cell and gene therapies.

Constraints on delivering cell and gene therapies were identified from guidance documents by the National Institute for Health and Care Excellence Technology Appraisal and Highly Specialised Technologies streams until October 2024. Inductive coding was performed to identify delivery constraints reported within the guidance documents. A quantitative analysis established the proportion of guidance documents that reported delivery constraints, and the distribution of these constraints across the guidance documents (frequency, mean range).

Sixteen guidance documents for cell and gene therapies were identified. Thirteen guidance documents (81.3 percent of the sample) reported constraints on delivering cell and gene therapies. Thirty-one examples of delivery constraints were reported. The mean number of constraints per guidance document was 1.9 (range: 0–6 constraints). The reported constraints were grouped by six different themes: provider experience (n = 8); testing constraints (n = 7); geographical constraints (n = 5); payment constraints (n = 5); maturity of developments in care (n = 4); and infrastructure constraints (n = 2).

Formal HTA processes are one effective way to identify constraints on delivering cell and gene therapies. Proactive identification of potential delivery constraints will help decision-makers, providers, and manufacturers generate strategies that improve the implementation of cell and gene therapies. Overcoming delivery constraints will strengthen the likelihood of realizing the expected incremental net health benefit of cost-effective cell and gene therapies for patients across a healthcare system.

Predictive biomarkers can identify patients who are more likely to respond to immunotherapy, which can guide treatment decisions. The objective of this study was to assess the potential value of predictive biomarkers in advanced NSCLC patients to guide the development of cost-effective biomarkers in this field.

A decision analytical model was constructed to compare theoretical new strategies with biomarkers to the current standard of care. The analysis was performed for three different patient groups based on PD-L1 status. Differences in health outcomes (QALYs) and costs were assessed between the current practice and these biomarker strategies.

Omitting immunotherapy in NSCLC patients with a PD-L1 score < 1 percent or between 1 and 49 percent, and a negative biomarker test, could potentially reduce healthcare costs significantly a small loss in QALYs. In these groups, a biomarker test is potentially cost-effective as the incremental cost-effectiveness ratio largely exceeds a willingness-to-accept threshold of €80,000 saved per QALY lost. For patients with a PD-L1 score > 50 percent, a considerable QALY gain can potentially be realized by adding chemotherapy to patients with a negative biomarker test. However, this comes at a significant increase in costs and appears not to be cost-effective.

In general, predictive biomarkers seem to have the potential to increase the cost-effectiveness of treatment with immunotherapy in patients with advanced NSCLC. Optimal positioning of a biomarker depends on the weighing between health impact and costs.

Value frameworks play a crucial role in bridging the gap between evidence and decision making in health care, particularly in settings with limited resources as low- and middle-income countries (LMIC). In this study, we present the development of a value framework (VF) targeted to provide coverage recommendations in rapid health technology assessment reports (rHTA) as well as its first 5 years of implementation.

We performed an exhaustive literature search with the aim to identify existing VFs and their dimensions followed by the generation of a VF proposal through a mixed methods, qualitative–quantitative approach including a Delphi panel to weigh the criteria and correlate them with the subsequent recommendations. To describe its implementation, we present the results of 264 rHTA reports from 2017 to 2022.

The value framework has three main domains (quality of evidence, net benefit, and economic impact). We adapted widely used methodologies for quality of evidence and net benefit domains. The economic impact domain was the most complex to assess, so an ad hoc method was developed. Analysis of 265 HTAs revealed the distribution of recommendations across different criteria and technology types. Most were for drugs (40.5 percent) or therapeutic procedures (36 percent). With a five-category final recommendation, 0.8 percent were favorable, 19.7 percent were uncertain, and 44 percent were unfavorable.

The VF demonstrated its versatility and practicality in meeting the needs of rHTA audience, and can facilitate evidence-informed decision making. This VF serves as a valuable tool for conducting adaptive rHTAs and supports decision-making processes in Argentina and similar LMIC contexts.

This investigation evaluates the relationships between claims of patient and health system benefit, evidence in support of those claims, and the recommendation outcomes of medical technologies assessed by the National Institute for Health and Care Excellence (NICE).

Data on evidence, claims, and recommendation outcomes were gathered from published Medical Technologies Guidances (MTGs) on the NICE Web site between 1 December 2010 and 11 April 2023. Binary logistic regressions and descriptive data analyses were performed to investigate the correlation between claims, evidence, and recommendation outcomes.

The technology was fully or partially recommended in forty-six (67.7 percent) of sixty-eight MTGs. No correlation was found between types and number of claims and type and quantity of clinical evidence. However, claims supported directly by evidence were significantly correlated (p < 0.016) with recommendation.

Evidence supporting claims is crucial for receiving a full or partial guidance recommendation. There is no clear pattern in what kind of or quantity of evidence leads to a recommendation, and to increase the probability of receiving a favorable recommendation, the manufacturer needs to plan early in the development phases on how to articulate and refine the claims and to substantiate claims through clinical evidence. It is therefore advisable to take advantage of the opportunity for scientific advice, which NICE offers.