To promote robust prevention strategies and reflect broader economic impacts, we developed the productivity-adjusted life years (PALYs) metric, which captures a more comprehensive view of health’s societal value. This systematic review explores the use of PALYs across various disease contexts, illustrating its application as a novel outcome measure in health economic evaluations.

We conducted a comprehensive review of studies utilizing PALYs to identify effective methods for decision-making and to illustrate their applications. Using a snowball search, we selected studies that applied PALYs to quantify societal health burdens in specific diseases or contexts. Extracted data included health conditions, country setting, time frame, model type, outcomes, data type (incidence or prevalence), discounting, time horizon, prevention strategies, working-age population, productivity index components, PALY economic value, gross domestic product (GDP), and sensitivity analysis details. Income-level classifications were based on World Bank standards, and findings were summarized through narrative synthesis.

We reviewed 34 studies published from 2018 to 2024, covering conditions like cardiovascular and kidney disease, and environmental factors such as PM2.5 exposure. Most were conducted in high-income countries (n=20). Life table models (n=23) and dynamic models (n=8) were predominant, with other methods including mathematical projections, questionnaires, and cross-sectional designs. Studies focused more on prevention (n=18) than on chronic disease management (n=14). Diabetes, hypertension, sleep apnea, and non-optimal temperatures had the greatest societal impact, while epilepsy led to significant losses in life years and PALYs. Productivity indices varied, with losses ranging from USD1,137 to USD217,983 per full-time worker.

The diversity of health conditions and economic contexts covered in these studies highlighted a broad interest in the determinants of health as measured by the PALY. This diversity is essential, as it provides a comprehensive understanding of the economic impacts and health challenges. Moreover, the emphasis on prevention over chronic disease management suggests a strategic shift toward averting disease onset.

Geriatric assessment and management (GAM) is a guideline-recommended strategy for optimizing cancer management among older adults. In a recent cost-utility analysis of the Canadian 5C randomized controlled trial (RCT), GAM appeared cost effective only in selective patients. We assessed the cost-utility of GAM plus usual care (UC) versus UC alone in older adults with cancer using a decision model and best available evidence from four international RCTs: GAIN, GAP70, INTEGERATE, and 5C.

We conducted a model-based economic evaluation using pooled data from four international RCTs (GAIN, GAP70, INTEGERATE, and 5C), supplemented by additional evidence from the literature. Deterministic and probabilistic analyses were performed from the healthcare payer perspective, applying a six-month time horizon. The base case and main analyses used Canadian cost data. Sensitivity analyses included per-trial scenario analyses, one-year time horizon, and the use of USA costs. We reported healthcare costs per quality-adjusted life year (QALY) and the incremental net monetary benefit (INMB) using a CAD50,000(USD36,277) per QALY threshold.

The base case analysis using Canadian costs indicated that GAM was cost effective with an INMB of CAD1,117 (USD819) (95% credibility interval [CrI]: −CAD2,450 [−USD1,796], CAD5,035 [USD3,692]) and 70.7 percent probability of GAM being cost effective at a cost-effectiveness threshold of CAD50,000 (USD36,666) per QALY. Trial-specific results varied, with the GAP70 and INTEGERATE trials yielding positive INMB values (CAD2,635 [USD1932] and CAD2,886 [USD2,116], respectively), while 5C and GAIN resulted in negative INMB values (−CAD642 [−USD471] and −CAD268 [−USD196], respectively). Sensitivity analyses revealed that chemotherapy costs were the main driver of costs in both GAM and UC strategies.

Evidence showed that GAM is generally cost effective. However, GAM’s cost effectiveness varied across trial scenarios, driven primarily by differences in chemotherapy costs. Future research should focus on identifying key GAM components that most effectively reduce severe toxicity, hospitalizations, and chemotherapy-related costs to optimize overall cost effectiveness.

Equity-informed economic evaluations require the baseline distribution of health across equity subgroups upon which the equity impact of interventions is evaluated. The distribution of health status, measured as quality-adjusted life expectancy (QALE), by socioeconomic status (SES) is unknown for Australia. We aimed to estimate QALE across SES groups, stratified by sex and year of age, for the Australian population.

SES was measured with the Socio-Economic Indexes for Areas Index of Relative Socio-Economic Disadvantage, from quintile one (Q1) most socioeconomically disadvantaged, to quintile five (Q5) least disadvantaged, and remoteness categories from the Australian Statistical Geography Standard: major cities, inner regional, and outer regional to very remote. Life expectancy (LE) was estimated from 2022 Australian Bureau of Statistics mortality data. Mean short form (SF-6D) utility by age, sex, and SES was estimated from the Household, Income and Labour Dynamics in Australia Survey (2022) using linear regression. Person-years were multiplied by utility to determine the QALE for each sex-SES group.

At birth, LE for all individuals in Q1 was 78.7 years, compared with 86.3 years for those in Q5. Incorporating health-related quality of life amplified disparities, with those in Q1 experiencing a QALE of 43.9 (95% confidence interval [CI]: 42.6, 45.2) years, compared with 55.6 (95% CI: 54.1, 57.1) years for Q5, a 27 percent relative difference. There were modest disparities by remoteness. Individuals in major cities had a LE of 83.1 years and a QALE of 50.8 (95% CI: 49.8, 51.7) years, while those in outer regional to remote areas had a LE of 80.5 years and a QALE of 47.0 (95% CI: 44.2, 49.7) years.

There is clear disparity in QALE by SES in Australia, whereby both the quantity and quality of life decrease with increasing socioeconomic disadvantage and geographical remoteness. These findings highlight the need for targeted interventions to address health inequalities. These detailed QALE estimates can be applied to future equity-informed economic evaluations.

Incorporating patient preferences into health technology assessment represents a promising avenue for its enhancement. However, the complexity and diversity of methods for evaluating preferences, coupled with uncertainties regarding their impact on decision-making processes, present significant challenges to their effective integration. Consequently, the objective of this study was to evaluate the application of the MaxDiff analysis methodology for determining patient preferences, with a focus on pharmaceutical services as a case study.

The experimental design for scaling MaxDiff was developed using Sawtooth Lighthouse software. The design parameters included 12 pharmaceutical services. Descriptive statistics, hierarchical Bayesian analysis, latent class analysis, and logistic regression methods were employed to generate preference results.

The most preferred services were identified as follows: the creation of a personalized list of safe medications to address patient needs, with a quantitative contribution of 0.5; and the provision of rapid tests (for influenza and Helicobacter) and stroke risk assessment (quantitative contribution of 0.31). In contrast, patients did not prioritize services related to contraception selection or weight control and weight loss program development. Descriptive statistics, hierarchical Bayesian analysis, and logistic regression methods sequentially identified the most preferred services. Latent class analysis revealed two distinct consumer segments: Segment 1 (39%) and Segment 2 (60%), which differed in their sociodemographic characteristics and preferred services.

The obtained results can be utilized as patient-based evidence to understand patients’ unmet needs in the assessment of technologies such as pharmaceutical services, taking into account the local context. Despite the simplicity of the MaxDiff analysis methodology, the resource intensity and the level of knowledge among specialists and patients regarding preference collection methods remain significant barriers to its implementation.

Constraints on surgical capacity due to budgetary and workforce shortages necessitate prioritization. Lessons learned from the COVID-19 pandemic emphasize the societal debate around these decisions and stress the need to align decisions with societal preferences. This study examined societal preferences for prioritizing patients with three different conditions—breast cancer, deafness, or knee arthrosis—for scarce surgical capacity.

We conducted a labeled discrete choice experiment among 1,046 members of the Dutch public. Respondents completed 14 choice tasks in which they prioritized patients for surgery, based on condition, age, health-related quality of life (HRQoL) before and after surgery, and waiting time until surgery.

Respondents were more likely to prioritize patients suffering from breast cancer over patients suffering from knee arthrosis or deafness. Respondents were also more likely to prioritize patients with lower levels of HRQoL before surgery, larger surgery-related increases in HRQoL, and longer waiting times until surgery. They were less likely to prioritize patients who were relatively older, although the opposite held true for patients suffering from deafness. Observed preference heterogeneity largely resulted from differences in preference strength, rather than preference direction.

Our results provided insight into societal preferences for prioritizing patients with different conditions for surgery. This insight aids in understanding public outcry that may follow decisions deviating from societal preferences. Aligning prioritization decisions with societal preferences may increase their legitimacy. Further research may examine the relevance of these preferences for physicians and their willingness to be guided by this.

Decisions to not reimburse or discontinue reimbursement of health technologies from public funding are considered increasingly necessary. However, such decisions remain politically sensitive and often provoke public opposition. Such opposition may be considerable and puts pressure on decision-makers to revoke or revise a decision; however, the specifics of this opposition remain largely unclear. Our aim was to obtain insight into these specifics by mapping the scientific literature on this topic.

We performed a systematic review following PRISMA guidelines. The electronic search was performed in Embase and using the Google Scholar, Google, and Startpage search engines and supplemented with a hand search in 2021. Both the electronic searches and the hand search were updated in 2022 and 2024.

Based on 81 articles, we developed a framework of 27 categories grouped under the ‘who, what, when, where, and why’ of public opposition to negative reimbursement decisions. Our findings indicated that patient representatives, physicians, and citizens are the primary actors opposing such decisions—often influenced by industry and politicians. These actors typically challenge the outcomes and arguments underlying decisions, driven by unrealistically high expectations of technology effectiveness and the assumption that decision-makers prioritize cost containment above all else. Additionally, our findings indicate increasing distrust among these actors toward decision-makers and evidence-based processes, leaving them vulnerable to commercial exploitation and misinformation.

Understanding the dynamics between actors is crucial for understanding public opposition to negative reimbursement decisions in health care. Aligning decision-making processes with public values, addressing misconceptions, and countering misinformation may enhance the legitimacy of reimbursement decisions. Further research should explore strategies to mitigate distrust and foster evidence-based engagement among actors to ensure more informed and equitable healthcare decision-making.

The Shared Learning model redefines patient engagement in health technology assessment (HTA) by combining immersion, knowledge sharing, and network expansion. Through flexible programs like Patient Voice Initiative (PVI) Patient Partners, it empowers advocates to deepen their understanding of HTA processes and disseminate insights broadly. This innovative, scalable approach ensures patient voices are central to decision-making, fostering informed contributions and addressing the challenges of rapidly evolving health technologies.

The Shared Learning model piloted by the PVI supported three patient advocates through a structured immersion in HTA processes. Advocates engaged directly in HTA discussions, meetings, and consultations, attending the HTAi Annual Meeting 2024 for deeper insights and networking. The model emphasized peer knowledge dissemination through webinars, workshops, and community forums, creating a ripple effect of shared learning. Advocates reflected on their experiences, identifying insights to benefit broader patient networks. This approach combined immersive learning, knowledge-building, and capacity expansion, fostering both vertical engagement with HTA stakeholders and horizontal knowledge-sharing within patient communities.

The Shared Learning pilot demonstrated success in enhancing patient engagement within HTA. Advocates deepened their understanding of HTA processes through direct participation and shared insights with wider patient networks, fostering a multiplier effect. Peer-to-peer knowledge dissemination expanded patient capacity, strengthening advocacy communities. Advocates utilized their experiences to host webinars, workshops, and community forums, broadening the reach of HTA knowledge. The initiative also improved the ability of patient networks to contribute meaningfully to decision-making processes. These outcomes highlight the model’s potential for creating sustainable, informed, and resilient advocacy communities equipped to address the challenges of rapidly evolving health technologies.

The Shared Learning model revolutionized patient engagement in HTA by emphasizing immersion, knowledge sharing, and network expansion. Through flexible programs like PVI Patient Partners, the model deepened engagement while enabling broader dissemination of insights. As health technologies rapidly evolve, this scalable approach ensures patient voices remain central to HTA decision-making, fostering informed, sustainable contributions within patient communities.

Restricted access to orphan drugs significantly challenges rare disease patients, impairing health outcomes and quality of life. In Türkiye, systemic barriers such as regulatory inefficiencies, economic limitations, and inadequate stakeholder collaboration persist. This study evaluated these issues through stakeholder perspectives, proposing a collaborative framework to improve access, ensure equity, and enhance systemic efficiency in addressing rare disease challenges in Türkiye.

This qualitative study employed semi-structured focus group discussions with 19 patients and caregivers and 13 in-depth interviews with healthcare providers, policymakers, industry representatives, and regulatory bodies. Thematic analysis of 1,996 coded excerpts identified key barriers to orphan drug access, categorized as direct or indirect impacts. Grounded theory was applied to synthesize these findings into a cohesive framework addressing economic, regulatory, and systemic challenges. Data triangulation enhanced validity, ensuring the perspectives of diverse stakeholders were accurately represented. Stakeholder feedback on the framework was incorporated iteratively, ensuring practicality and adaptability for policy and decision-making in Türkiye. Supported by TUBITAK 2224-A Program for participation in HTAi 2025; it had no role in the study conduct.

The study revealed multifaceted barriers to orphan drug access in Türkiye, including fragmented regulatory processes, high costs, and inadequate inter-stakeholder collaboration. Indirect factors, such as limited public awareness and insufficient professional education, exacerbated these challenges. The proposed framework emphasizes centralized regulatory mechanisms to streamline approvals, public–private partnerships to mitigate financial constraints, and enhanced communication to ensure transparency and accountability. Stakeholder feedback highlights the framework’s adaptability and potential impact, particularly in addressing disparities within Türkiye. Success metrics, such as improved regulatory efficiency and patient outcomes, were defined to support future implementation and continuous improvement.

The proposed framework addresses critical systemic barriers to orphan drug access in Türkiye by fostering collaboration, streamlining regulatory pathways, and enhancing equity. It emphasizes the importance of stakeholder alignment and sustainable policy solutions for rare disease patients. Future research may focus on piloting the framework, adapting it for broader contexts, and developing evaluation tools to measure its long-term impact.

Generic medicines form the backbone of affordable health care in low- and middle-income countries (LMICs), constituting a significant portion of pharmaceutical consumption. However, issues such as fragmented pricing policies and insufficient regulatory frameworks hinder equitable access and affordability. This study evaluated pricing models that address these challenges by integrating best practices, including tiered pricing mechanisms and enhanced transparency. The aim was to guide policymakers toward sustainable solutions that improve medicine affordability, equity, and market resilience.

A comparative analysis was conducted across 20 countries, chosen for their diverse healthcare profiles and potential to be best practice examples for LMIC contexts. Key elements analyzed included pricing mechanisms (e.g., tiered pricing, external reference pricing, internal reference pricing), regulatory frameworks, and incentives for local production. Data were gathered from government reports, healthcare provider feedback, and industry insights. A policy evaluation framework was applied to assess each model’s effectiveness in addressing affordability, accessibility, and equity. The analysis prioritized generalizability to LMICs while accounting for contextual adaptations such as regional economic challenges and varying levels of regulatory capacity.

Supported by TUBITAK 2224-A Program for participation in HTAi 2025; it had no role in the study conduct.

The findings revealed that tiered pricing structures significantly enhanced affordability by incentivizing market competition and reducing prices as generics enter. Transparent regulatory practices, including centralized databases and consistent price reviews, mitigated regional price disparities and increased trust among stakeholders. Countries fostering domestic production reduced import dependencies, stabilizing supply chains and ensuring medicine availability. These strategies, when applied collectively, have great potential to improve equitable access to generics in resource-constrained settings. The results highlighted the importance of adapting global best practices to the economic and healthcare realities of LMICs, emphasizing sustainability and resilience in pharmaceutical markets.

Integrating tiered pricing frameworks, regulatory transparency, and local production incentives provided a pragmatic pathway to improve generic medicine access in LMICs. These approaches align with global best practices and address affordability and equity challenges. Policymakers should prioritize such strategies while leveraging stakeholder collaboration. Future research should examine dynamic pricing models and their long-term impacts on market stability and healthcare outcomes.

Social media listening studies (SMLS) analyze online dialogue from patients, caregivers, and clinicians to gain insights into the lived experience of disease including treatment efficacy and safety, and unmet needs. This analysis aims to understand whether SMLS is a feasible method for generating real-world data that can shape pivotal trial design or supplement trial data for health technology assessment (HTA).

A targeted literature search was conducted on PubMed to identify articles published in English that describe and report the findings of SMLS specifically investigating health conditions and diseases. No limits were placed on date of publication or geographical scope. Information was extracted from these papers and used to map concepts and themes covered in SMLS to key domains of HTA submission dossiers in the UK, France, and Germany, as well as the upcoming joint clinical assessments (JCA). This analysis was used to determine the extent to which SMLS can be used to generate payer-relevant data.

A total of 19 papers were included in this analysis. All studies used a retrospective approach, and the majority (84%) analyzed data from more than one market. The most common markets included were the UK (74%), USA (58%), France, and Germany (53%). Thirty-two percent included only patient conversations; 47 percent included conversations from patients, caregivers, family, and friends; and 21 percent included physicians. The most common themes covered were quality of life (89%), burden of disease or symptomology (79%), and treatment patterns (79%), which align closest to the dossier templates for HAS (French National Authority for Health) and the JCA.

All studies in this analysis included data that would be relevant for HTA submission, and the majority provided data that would speak to multiple payer concerns. While there are no published guidelines for leveraging SMLS for HTA, this analysis indicated that this methodology could potentially be used alongside trial data to highlight the patient experience within reimbursement submissions.

Structured expert elicitation (SEE) is a method of formally collecting expert opinions and beliefs using a statistical framework that can be used to generate qualitative data for health technology assessment (HTA). SEE is a particularly useful strategy for rare diseases and innovative technologies, where clinical trial data can be subject to additional uncertainty.

To investigate how SEE evidence has been used in HTA submissions for rare diseases, a targeted literature search was conducted to identify relevant submissions to the National Institute for Health and Care Excellence (NICE) in the UK via the highly specialized technology (HST) pathway. HST reports were screened to ensure that the company submission documents were publicly available and that details of any SEE studies were included. Fields of extraction included the methods used by SEE, the value drivers that SEE data justified, and the consideration of such evidence by the NICE decision-making committee in the final appraisal document (FAD).

All 27 submissions included in the final analysis leveraged SEE; eight submissions used two SEE methods, and 11 submissions used three methods. The most popular method was semi-structured interviews (81%), followed by surveys (59%), advisory boards (33%), and Delphi panels (26%). The majority of SEE evidence supported core value elements such as quality-adjusted life years (81%). However, SEE evidence was also used to support innovative value elements including family spillover (59%) and productivity (29%). Expert evidence was assessed in the majority of FADs but was accepted mostly when supporting core value elements.

Commonalities in submissions that successfully leveraged SEE to support holistic value elements included providing clear justification for why the data could not be sourced elsewhere, conducting multiple formats of expert engagement, recruiting large samples of experts, and including a detailed overview of the SEE study design. Manufacturers should consider these critical success factors when including SEE in evidence generation strategies.

Neurodivergent children and young people (CYP) experience delays in accessing diagnostic services (two years and three months in the UK). This may harm their development and create missed opportunities for support. Telehealth offers alternative solutions to streamline services and improve the identification of neurodivergence. An early economic analysis was developed to estimate telehealth’s likely costs and consequences in delivering care to CYP.

A conceptual care pathway involving assessment using a telehealth platform—vCreate Neuro—compared to an assessment without vCreate Neuro, was derived from expert consultation and published UK clinical guidelines. A cost-consequence analysis was conducted from a societal perspective in Glasgow, Scotland using data from ongoing pilot studies in National Health Service (NHS) and published literature. Surveys and expert consultations with clinicians assessed trade-offs between costs and consequences associated with the delivery of care in the care pathway. Cost data included direct and overhead expenses related to service delivery.

Costs incurred in the vCreate Neuro pathway were estimated to be GBP1,141.50 (USD1,569.50) and GBP1,220.00 (USD1,677.45) (per patient) without vCreate Neuro, which resulted in GBP78.50 (USD107.90) savings. The clinician survey results indicated possible improvements in time to diagnosis by several weeks to months, with an average decrease of up to four unnecessary appointments. Clinician-to-patient relationships and quality of care may also improve, with 90 minutes of medical time liberated per patient. Additionally, clinicians reported potential improvements in the quality of relationships with parents. Results from the expert consultation highlighted a likely increase in administrative burden for clinicians using the telehealth platform.

The possible administrative burden of using the vCreate Neuro care pathway was rewarded by resource use savings and reduced time to diagnosis. Further evaluation of the system’s costs, benefits, and acceptability by parents or carers is required. This study is relevant for health systems with limited resources, complex services requiring multidisciplinary teams, and the need to overcome barriers to care.

Mounting evidence shows that gene expression signatures in early breast cancer enable more precise chemotherapy recommendations, targeting those most likely to benefit and safely avoiding it for others. International guidelines highlight their role in optimizing adjuvant chemotherapy decisions. This study examined chemotherapy recommendation patterns in Brazil, providing decision-makers with locally specific data to support evidence-based and patient-centered care.

We conducted an online survey with 10 independent clinical oncology experts, blinded to each other’s responses, to evaluate average chemotherapy recommendations considering age, menopausal status, and clinical risk assessment using the MINDACT study criteria with and without the Oncotype DX Breast Recurrence Score test. For node-negative patients, we analyzed recommendations by clinical risk level (high versus low), age category (over or under 50 years), and recurrence score (RS) ranges (<11; 11 to 25; >25). For node-positive patients, menopausal status and RS ranges (<14; 14 to 25; >25) were evaluated. The results were summarized as the arithmetic means of observed responses.

Chemotherapy recommendations were as follows.

• • For node-negative patients under 50 years by clinical risk (low/high risk): Without Oncotype DX: 36 percent/89 percent; with Oncotype DX and RS less than 11: zero percent/eight percent; RS 11 to 25: 41 percent/70 percent; RS greater than 25: 88 percent/98 percent.

• • For patients older than 50 years without Oncotype DX (low/high risk): 17 percent/77 percent; with Oncotype DX and RS less than 11: zero percent/six percent; RS 11 to 25: one percent/30 percent; RS greater than 25: 88 percent/98 percent.

• • For node-positive patients: Premenopausal women had high chemotherapy rates (82 to 100%) regardless of RS, while in postmenopausal women rates ranged from three percent (RS<11) to 94 percent (RS>25), compared with 81 percent without testing.

Oncotype DX Breast Recurrence Score reduced chemotherapy use in node-negative and postmenopausal node-positive patients, improving treatment targeting. This study revealed differences in chemotherapy recommendations between local Brazilian data and prior Oncotype DX models. Next-generation HTA should prioritize local realities to avoid misrepresentations that could misguide policymakers and to support sustainable and personalized healthcare frameworks in Brazil.

Since 2023, the Agency for Care Effectiveness (ACE) has included lived experiences from patients and caregivers in health technology assessments (HTAs) for wearable or home-based medical devices. This presentation discusses the impact of patient experience data on the HTA and subsequent subsidy recommendations for continuous glucose monitoring (CGM) systems for type 1 diabetes mellitus (T1DM) in Singapore.

All local patient organizations with an interest in CGM systems or T1DM were invited to share their views using a structured, qualitative survey or simple free-text patient journey form. Testimonials were analyzed by ACE to extract key themes and insights and incorporated into the HTA report alongside clinicians’ input and clinical and economic evidence to inform subsidy recommendations made by the Ministry of Health Medical Technology Advisory Committee. The impact of patient experience data on the Committee’s deliberations and recommendations for CGM systems was determined by reviewing the HTA report, minutes from Committee meetings, and the published HTA guidance document.

Eighty testimonials were received from patients and caregivers about the impact T1DM has on their lives, and their experiences using different blood glucose monitors. They also confirmed real-world CGM usage across different age groups, informing assumptions for budget impact calculations. Testimonials highlighted benefits and drawbacks of different monitoring methods, unmet needs, patient preferences, and expectations for new technologies to be more affordable and less invasive. While scientific evidence for children with T1DM was limited, testimonials confirmed CGM systems could improve outcomes for both adults and children, which influenced the subsidy criteria recommended by the Committee to cover both age groups.

Incorporating patients’ lived experiences in ACE’s HTAs validated and strengthened the scientific evidence, addressed uncertainties by filling data gaps, and led to patient-centered subsidy recommendations for CGM systems, demonstrating the value of systematic patient involvement. Post-recommendation, ACE co-developed a factsheet on CGM systems with local patient organizations to explain the subsidy recommendations in plain language and encourage HTA guidance adoption.

Health technology assessment (HTA) evaluates the cost effectiveness and clinical efficacy of health technologies to inform policy decisions. Established in 2017 by the Department of Health Research, the Office of Health Technology Assessment in India is housed within the Ministry of Health and Family Welfare; however, challenges remain. This study analyzed gaps in India’s HTA framework to aid policymakers in making improvements.

The study conducted a systematic review of HTA literature and a focus group discussion with Ministry of Health representatives. A search on PubMed using “HTA” AND “India” yielded 74 papers from the last seven years, with 12 additional papers found through Google. Using the PRISMA methodology, titles, abstracts, and full texts were evaluated, and duplicates were managed with Zotero. Data were collected in an excel sheet, and the HTA scorecard from Türkiye helped identify context-specific gaps in India, which were discussed with six focus-group members from the HTA department at the Ministry of Health and Family Welfare and the National Health Systems Resource Centre.

The desk review identified gaps in India’s data usage, including a fragmented data ecosystem, limited electronic health records, and challenges with real-world evidence that affect HTA effectiveness. A major issue was the scarcity of trained professionals for high quality HTA and insufficient public funding for HTA research. The potential of HTA remains underutilized. Barriers to effective HTA legislation include the complexity of central policies, incoherence with state administration, and fragmented insurance schemes. Focus group participants recommended capacity building and orientation programs for the HTA department and state procurement, highlighting the need for funding to support implementation research for benchmark development.

India faces challenges in data infrastructure, stakeholder involvement, funding, and policy integration for HTA. Investments in data collection and training are essential. With initiatives such as Digital India and Make in India, the country aims to establish itself as a global digital economy. Strengthening HTA institutionalization and implementing an artificial intelligence-based HTA framework can position India as a leader in HTA.

In 2023, we published widely cited cost-effectiveness thresholds (CETs) for 174 countries. This update refined our approach by incorporating gross domestic product (GDP) growth projections to adjust target increases in life expectancy and health expenditure. This methodology provides more precise estimates tailored to the economic and health contexts of individual countries, enabling better informed resource allocation decisions.

We revised our 2023 methodology by integrating International Monetary Fund projections of GDP growth for the next five years to establish customized targets for life expectancy (LE) and health expenditure (HE) growth. This update accommodates countries where the prior assumption of median growth within income groups was less applicable. The CETs were derived so that the effect of new interventions on the evolution of LE and HE is set within predefined goals. To provide guidance on CETs, we projected country-level HE and LE increases by income level based on World Bank data to ensure the estimates align with individual country realities.

The updated thresholds yielded values consistent with our 2023 estimates, yet notable differences emerged in countries with distinct GDP growth trajectories or unique health spending patterns. For example, thresholds for India and similar countries adjusted upward to reflect ambitious yet realistic targets for HE and LE growth. Across 174 countries, most thresholds remained below one GDP per capita, confirming their relevance for guiding economic evaluations. These nuanced updates demonstrate the flexibility and applicability of our approach in diverse contexts, particularly for low- and middle-income countries.

By incorporating GDP growth projections, this study enhanced the precision of cost-effectiveness thresholds, ensuring their applicability across varying country contexts. These updates provide critical guidance for health systems aiming to balance efficiency, equity, and sustainability, particularly in resource constrained settings.

Countries face challenges in prioritizing scarce health resources, often relying on evaluations based on quality-adjusted life years (QALYs). However, QALY gains may not fully capture intervention value, especially for rare disease treatments, which are often perceived as more valuable. This study examined whether Chinese health insurance decision-makers prioritize rare disease treatments and sought to quantify any additional value assigned.

We conducted two sequential discrete choice experiments (DCEs). The first, labeled DCE, compared drugs for common and rare disease using five attributes—disease severity, childhood onset, catastrophic expenditure, treatment novelty, and clinical benefit—to explore conditions for prioritizing rare disease coverage. The second, unlabeled DCE, compared rare disease scenarios, adding QALY gains and social insurance premium increments to estimate willingness-to-pay per QALY and derive incremental cost-effectiveness ratio (ICER) thresholds. A D-efficiency design produced 16 and 20 choice sets, blocked into two versions. In 2023, 120 decision-makers were invited for online data collection via interviews. Analysis used conditional logit models to assess preferences.

In total, 101 eligible decision-makers provided complete responses and were included in the analysis. Nearly half of the respondents were female (47.5%), with 58.4 percent having over 10 years of professional experience. Many participants had expertise in health insurance system research (48.5%) and pharmacoeconomics (77.2%). The first DCE found rarity alone did not add value; decision-makers prioritized disease severity, drug innovation, and health benefits, especially the first two. The second DCE estimated an ICER threshold for rare diseases of 1.9 times the gross domestic product per capita—around three times China’s current baseline threshold—reflecting equity considerations.

Chinese decision-makers demonstrated a willingness to assign higher value to rare disease treatments, particularly when considering severity and novelty. This study provided empirical evidence that supports higher ICER thresholds for rare disease treatments to account for equity considerations. The findings offer valuable insights for policymakers seeking to refine health insurance reimbursement strategies and ensure a more equitable allocation of resources.

Globally, knee osteoarthritis (OA) is a prevalent and disabling condition. Intra-articular glucocorticoid injection (IAGI) is widely used to treat knee OA. However, there is conflicting evidence on the benefit-harm profile of IAGI for this indication. This study aimed to determine the clinical effectiveness and safety of IAGI for knee OA.

Systematic literature searches were conducted in three biomedical databases (MEDLINE, Embase, the Cochrane Library) through to 4 October 2023. Randomized controlled trials (RCTs) that compared IAGI with no treatment, sham injection, or oral placebo in patients with knee OA were included. RCTs were appraised using the revised Cochrane risk-of-bias tool. Longitudinal meta-analysis (LMA) was conducted for predetermined outcomes (i.e., pain, function, health-related quality of life [HRQoL], care utilization, adverse events [AEs], and serious adverse events) at one month, three months, six months, and 12 months. Pairwise meta-analyses were conducted at individual time points if there was insufficient evidence to conduct a LMA. The research project was funded by the Swiss Federal Office of Public Health.

In total, 16 RCTs comprising 1,522 patients with knee OA were included. The LMA reported a small reduction in pain at one month (standardized mean difference: −0.30, 95% confidence interval [CI]: −0.52, −0.08), but no clinically or statistically significant differences from three to 12 months. Regarding function, the LMA found no significant differences at any time point. Pairwise meta-analyses at one month showed reduced care utilization favoring IAGI (mean difference −0.43; 95% CI: −0.81, −0.05), but not at other time points, and no differences in HRQoL at any time point. No significant safety concerns were found in relation to AEs and serious AEs.

IAGI provided short-term pain relief for knee OA at one month post-injection, with beneficial effects diminishing by three months and beyond. There were no substantial improvements in function or HRQoL. No significant safety concerns were identified. To guide clinical decision-making, further research should focus on HRQoL as well as potential subgroups of patients that may benefit in the longer term.

The climate crisis is a health crisis. The health technology assessment (HTA) community is lacking appropriate support and resources to adequately support the evaluation of health technology environmental sustainability. There is a need for reporting guidance to help authors, journal editors, and peer reviewers in their identification and interpretation of sustainability outcomes within HTA. The goal of the Sustainability in HTA (SUSHTA) checklist is to promote key collaboration that aids sustainable healthcare development.

The key aims of the SUSHTA checklist were to validate an environmental model created by industry and provide recommendations to support appropriate framing and reporting of the environmental data. International methodological guideline sources, HTA principles including reproducibility and transparency, and best practice health economics model validity frameworks were used with an interdisciplinary, multidimensional approach. The framework supports pertinent, high quality evidence that extends beyond conventional sources. The checklist has been used as a tool to facilitate collaboration with industry in reporting an information conduit to further aid data sharing and reduce data paucity among HTA agencies and to support healthcare decision-making.

The SUSHTA checklist is holistic and comprehensive through its interpretation of environmental models, including validity checks of terminology, labeling and referencing, model justification, data collection and calculation techniques, assumptions, sensitivity and scenario analysis, and uncertainty modeling. The framework also supports applying the same principles to environmental impacts other than greenhouse gas emissions. Therefore, this framework can be applied to assess a wider range of environmental outcomes (data) for human health impact (disability-adjusted life years), resource use (e.g., water or fossil fuel use), and biodiversity loss (number of species lost per year). The checklist is generalizable and integrates well with healthcare system frameworks.

The SUSHTA checklist is primarily intended for researchers to recommend the minimum amount of information required for reporting environmental data. However, familiarity with reporting requirements will be useful for analysts when planning studies. It may also be useful for HTA agencies seeking guidance on reporting, as there is an increasing emphasis on transparency and reproducibility in more sustainable decision-making processes.