Exploratory Approach to Incorporating Carbon Footprint in Health Technology Assessment (HTA) Modelling: Cost-Effectiveness Analysis of Health Interventions in the United Kingdom.

BACKGROUND: Health interventions contribute to the production of greenhouse gas emissions. Thus, reducing carbon footprint is essential in supporting the UK National Health Service (NHS) pathway to net zero. This study explores the approach in which carbon footprint can be included when applying Health Technology Assessment (HTA) modelling using obesity intervention in the United Kingdom (UK) as a case study. METHODS: Using decision analytic modelling, we conducted an HTA incorporating the impacts of obesity-related treatment decisions on UK carbon emissions. A cohort Markov model was used to track the emissions of the UK population after receiving one of two obesity treatments: semaglutide and bariatric surgery. RESULTS: This study introduced two new carbon measurement tools that may be useful for future policymaking, incremental carbon footprint effectiveness ratio (ICFER) and incremental carbon footprint cost ratio (ICFCR), which made it possible to assess the emission impacts of proposed health policies. Using the obesity intervention case study, we found that both treatments have an incremental cost-effectiveness ratio (ICER) of < £20,000 per quality-adjusted life-years (QALYs) gained. This is below the UK threshold, indicating that these are cost-effective treatments for obesity, but could increase the NHS carbon footprint. However, it could reduce the overall UK societal carbon footprint by reducing the number of people with obesity. The ICFCR shows a reduction of 1.13-4.51 kgCO2e (kilogram of carbon dioxide equivalent) for every pound spent on obesity treatment. CONCLUSION: This study illustrates a case study for estimating the effect of health policies on carbon emissions and provides a quantitative measure for obesity-related treatment decisions.

Evaluation of Global Post-Outbreak COVID-19 Treatment Interventions: A Systematic Review and Bibliometric Analysis of Randomized Controlled Trials.

Purpose: The outbreak of COVID-19 has led to a global pandemic with millions of cases and deaths. Many randomized controlled trials (RCTs) were conducted to establish effective therapies. However, the methodological quality of these trials is paramount, as it directly impacts the reliability of results. This systematic review and bibliometric analysis aim to assess the methodological approach, execution diversity, global trends, and distribution of COVID-19 treatment RCTs post-outbreak, covering the period from the second wave and onward up to the present. Methods: We utilize articles from three electronic databases published from September 1, 2020, to April 1, 2023. Inclusion and exclusion criteria were applied to identify relevant RCTs. Data extraction involved the collection of various study details. Risk of Bias (RoB) 2 tool assessed methodological quality, while implementation variability was evaluated against registration information. Bibliometric analysis, including keyword co-occurrence and country distribution, used VOSviewer and Tableau software. Results: Initially, 501 studies were identified, but only 22 met the inclusion criteria, of which 19 had registration information. The methodological quality assessment revealed deficiencies in five main domains: randomization process (36%), deviations from intended interventions (9%), missing outcome data (4%), measurement of the outcome (18%), and selection of reported results (4%). An analysis of alignment between research protocols and registration data revealed common deviations in eight critical aspects. Bibliometric findings showcased global collaboration in COVID-19 treatment RCTs, with Iran and Brazil prominently contributing, while keyword co-occurrence analysis illuminated prominent research trends and terms in study titles and abstracts. Conclusion: This study offers valuable insights into the evaluation of COVID-19 treatment RCTs. The scarcity of high-quality RCTs highlights the importance of enhancing trial rigor and transparency in global health emergencies.