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Healthcare contributes up to 8.5 percent of global carbon emissions, amongst other environmental impacts including intensive water consumption, plastics in our environment and pharmaceutical associated pollution. Healthcare supply chains are the largest contributor of environmental impact, accounting for up to 80 percent of total health sector emissions. Health technology assessment (HTA) can help support the mitigation of this impact by integrating sustainability considerations into policy making. Current literature indicates emission values are being included in some procurement decisions, and some HTA agencies are collecting environmental data or developing environmental domains in their strategies. However, there are no HTA agencies globally that officially include environmental outcomes as part of the decision-making framework. Adapting HTA to include environmental impacts will require integrating multidisciplinary approaches to make decisions that promote environmental sustainability. A scoping review was undertaken to identify such multidisciplinary methods. Multiple databases and gray literature sources were searched to identify relevant studies. The identified methods were appraised based on predefined criteria for HTA suitability, focusing on comprehensiveness, feasibility, and transparency. Key methods and frameworks identified include environmental life cycle assessment, cost–benefit analysis, and discrete choice experiments. Frameworks were ranked based on their potential suitability for implementing environmental impacts into HTA. Approaches such as One Health and circular economy provide possible foundations for environmental sustainability frameworks in HTA. Combining assessment methods to support trade-off considerations may strengthen decision making, although further research should examine stakeholder perspectives and implementation barriers.
BACKGROUND: The NHS Health Check is designed to identify individuals at high risk of preventive diseases such as cardiovascular disease (CVD) – but uptake remains low. This study aims to evaluate the one-year incremental cost and lifetime cost effectiveness of community-based lipid testing (PocDoc Health Heart Check) compared with the NHS Health Check or primary care medication reviews.
METHODS: An early economic model was developed, which evaluated PocDoc testing in five settings: the workplace, community, pharmacy, at-home via-pharmacy invitation and case-finding from the CVD register. Deterministic sensitivity analysis was used to evaluate uncertainty, and a threshold of £20,000 per quality-adjusted life year (QALY) was used for the incremental cost-effectiveness ratio (ICER).
RESULTS: PocDoc’s per-person test cost is lower than the NHS Health Check. However, its higher uptake leads to higher short-term costs. In the short term, the incremental cost compared with standard of care ranges from £6.08 to £36.66 per person. In the long term, PocDoc is a cost-effective use of resources in all test settings: the ICER ranges from £1,915 to £7,884 per QALY. The long-term results are sensitive to changes in lifetime costs and QALYs.
CONCLUSIONS: Community-based lipid testing using PocDoc Healthy Heart Checks in pharmacies, workplaces and the community could be a cost-effective intervention to identify individuals at high risk of CVD compared with the NHS Health Check. PocDoc testing could also be a cost-effective alternative to medication reviews for people on the UK CVD register who are non-adherent.
When environmental outcomes are included in health economic analyses, many studies tend to focus only on the direct carbon footprint of the technologies being assessed. However, this narrow approach ignores several highly important factors. This article is intended to be an opening proposition rather than claiming to have fully formed answers. It proposes four additions to the environmental evaluation of healthcare interventions. The first is to include all downstream impacts. The second is to account for the environmental impact of displaced healthcare funding. The third is to account for the environmental impact of changes in life expectancy. Finally, the fourth recommendation is to use a decision rule to compare trade-offs between health gains (or losses) and environmental harm (or benefit). A hypothetical case study is used to illustrate how each of these recommendations can change the results of an evaluation. It is demonstrated that, whilst the narrow approach implied that a new technology might reduce environmental harm (a 5 kg reduction in CO2 equivalent emissions), the wider considerations demonstrate that the impact may be far larger (an increase of 19,119 kg CO2 equivalent emissions). Although the case study is hypothetical, the principles demonstrate that ignoring the wider impacts of health policies may miss important consequences.
BACKGROUND AND AIMS: Long-term strong opioid use for chronic non-malignant pain (CNMP) represents a significant public health challenge, associated with reduced health-related quality of life (HRQoL) and increased mortality. The Improving the Wellbeing of people with Opioid Treated CHronic pain (I-WOTCH) trial demonstrated that a multicomponent intervention supporting opioid withdrawal in people with CNMP successfully reduced opioid consumption compared with best usual care (BUC), without adversely affecting perceived pain levels. This study aimed to assess the value-for-money of the strategies tested in the I-WOTCH trial, from the perspective of the United Kingdom National Health Service (NHS) and Personal and Social Services.
DESIGN, SETTING AND PARTICIPANTS: Within-trial cost-consequence (CCA) and model-based cost-effectiveness analyses (CEA), over one year and lifetime horizons, respectively. Data were sourced from the I-WOTCH trial, which recruited 608 participants from 191 primary care centres in England between May 2017 and January 2019 and followed them up for up to 12 months. Participants received either BUC or 3 group sessions (lasting one day each) led by a trained intervention nurse and by a lay person with CNMP and lived experience with opioid tapering. These sessions, designed to develop self-management skills, were supplemented by ongoing one-to-one support from nursing and lay personnel during follow-up. We used a probabilistic state-transition model to predict expected quality-adjusted life years (QALYs) and costs (in UK £) of each strategy over the lifetime of an individual. Model input parameters were derived mostly from the I-WOTCH trial. Opioid-related excess mortality and fracture rates were extracted from the literature.
MEASUREMENTS: Individual-level healthcare resource use and generic HRQoL [measured using the EuroQOL five dimensions questionnaire (Equation 5D)] were collected at baseline, 4, 8 and 12 months, and analysed to estimate total costs and health consequences for the I-WOTCH and BUC groups.
FINDINGS: I-WOTCH had higher costs and similar HRQoL outcomes compared with BUC at 12 months. When accounting for long-term reductions in mortality and morbidity from decreased exposure to strong opioids, our long-term model predicted I-WOTCH to yield higher costs and higher QALYs than BUC over the patient's lifetime, resulting in a base case incremental cost-effectiveness ratio of £29 543/QALY (2019 prices). Results were sensitive to structural assumptions in the model (i.e. cohort starting age, treatment effect weaning rate). Our probabilistic sensitivity analysis found I-WOTCH to have a 50% probability of being cost-effective compared with BUC for willingness-to-pay thresholds ranging between 0 and £100 000/QALY.
CONCLUSIONS: The Improving the Wellbeing of people with Opioid Treated CHronic pain intervention supporting opioid withdrawal in people with chronic non-malignant pain appears to be cost-effective on average, but further research is warranted to reduce current levels of decision uncertainty.
Systematic reviews of health economic evaluations (SR-HEEs) are perceived as mandatory components of the health technology assessment (HTA) process in many jurisdictions. However, HTA agencies vary in how they prescribe reviews of HEEs should be conducted and the explicit purpose they serve. This article identifies the requirements of prominent HTA agencies, reports on the real-world conduct of SR-HEEs by health technology developers (HTDs), and explores their utility in the HTA process. International HTA guidelines were consulted, alongside a targeted review of SR-HEEs submitted to the National Institute for Health and Care Excellence (NICE) in 2024. While a systematic approach is a constant requirement to reviews of HEEs, it is defined inconsistently across agencies, with clinical and safety systematic reviews (SRs) receiving more rigid prescription. Consequently, SR-HEEs submitted to NICE demonstrated mixed methods. Despite these pragmatic deviations of SR-HEEs, External Assessment Groups (EAGs) raised no major concerns, and reimbursement decisions do not appear to be influenced. Our findings suggest a rigor gap between SR theory and practice, driven by the inherent heterogeneity of economic models, which renders quantitative pooling inappropriate. We submit that a more pragmatic approach to reviews of HEEs would be appropriate for HTA. To maximize utility and reduce resource waste, we propose a two-stage framework: early pragmatic “landscape mapping” to inform early model conceptualization, followed by a formal SR-HEE only when a specific useful research question is identified. This strategic realignment, possibly supported by emerging technologies, would enable HTA resources to be reallocated toward higher-value activities.
We have read with great interest the published network meta-analysis (NMA) by Wang et al. (2026) in Frontiers in Endocrinology, which synthesised available randomised controlled trial (RCT) evidence to evaluate the relative efficacy and safety of rearranged during transfection (RET)-targeted agents for the treatment of advanced medullary thyroid cancer (MTC) (1). Through a comprehensive systematic literature review and NMA, their study provides relative effect estimates comparing RET-targeted agents, addressing a critical evidence gap due to the lack of direct evidence. Five studies were included in the NMA: ZETA (vandetanib) (2), EXAM (cabozantinib) (3), ALTER01031 (anlotinib) (4), LIBRETTO-531 (selpercatinib) (5), and EORTC-1209 (nintedanib) (6). All studies used placebo as the control arm except LIBRETTO-531, which used physician’s choice of cabozantinib or vandetanib. It should be noted that the publication incorrectly references the phase 1–2 LIBRETTO-001 trial instead of the phase 3 LIBRETTO-531 trial (reference 13 in Section 2.6.2 of the original publication). While the study demonstrated that selpercatinib exhibits superior efficacy, in terms of progression-free survival (PFS) and objective response rate (ORR), and a more favourable safety profile compared with other RET-targeted agents for advanced MTC, there are some important points for consideration that may affect the interpretation of the results. However, it should be noted that we did not reperform the NMA as part of this commentary, and the points we raise are methodological rather than quantifying their impact on the derived treatment effect estimates.
Firstly, in four of the five studies included, eligible patients were required to have documented disease progression. However, this criterion was not required in the ZETA trial (2). Differences in the median PFS in the placebo arms across trials, derived from observed Kaplan-Meier plots, suggest that patients included in the ZETA trial were healthier than patients enrolled in other trials where disease progression was an eligibility criterion (Table 1). If disease progression is a treatment effect modifier, this will introduce bias and violate the assumption of transitivity in the NMA. Therefore, it could be argued that the patients from the ZETA trial included in the current analysis represent a different treatment population compared to the other studies included in the analysis. However, it should be noted that despite these potential differences in population, the NMA-derived PFS treatment effect for cabozantinib versus vandetanib was not statistically significantly different (HR 0.61; 95% CI 0.35 to 1.05).
BACKGROUND: Research has shown that smoking post-diagnosis negatively impacts cancer outcomes. This study aimed to assess the health and cost impacts of introducing smoking cessation services at cancer diagnosis for people who smoke.
METHODS: A cost-effectiveness model was developed using a UK National Health Service (NHS) and Personal Social Services perspective. A partitioned survival model was built and survival analysis was used to estimate the proportion of the cohort in each health state (progression-free, progressed and dead) based on smoking status. Four populations were explored: lung cancer (stage 1–3a), head and neck cancer (stage 3–4), kidney cancer, and general cancer.
FINDINGS: Over a lifetime time horizon, offering smoking cessation at diagnosis resulted in an incremental cost-effectiveness ratio of £2606, £5495 and £4055 per quality-adjusted life-year (QALY), for lung, head and neck, and general cancer, respectively. The intervention was dominant for kidney cancer. Offering smoking cessation extended life by 2–8 months and slowed cancer progression by 2–6 months.
INTERPRETATION: This analysis indicates that implementing smoking cessation into NHS cancer care is cost effective at a £20,000 per QALY willingness-to-pay threshold, and provides large health benefits. Smoking cessation aligns with the NHS 10-year plan to move from treating sickness to preventing illnesses.
