Sustainability Publication Digest: Estimation of the Economic and Environmental Impact of Single-Use Instruments in Routine Cataract Surgery

MTRC shares the most relevant and impactful publications in the field of market access and HEOR for medical technologies in Europe through its Health Economic Publications Digest. In a recent publication, Reason et al. introduced how generative artificial intelligence (GenAI), particularly large language models (LLMs) like ChatGPT, can support health economics and outcomes research (HEOR). The authors highlight that LLMs can streamline a range of HEOR activities, including literature summary, data extraction, report drafting, and statistical code generation. However, they also point out key limitations, such as the risk of hallucinated outputs, security vulnerabilities, reproducibility issues, and potential bias. Implementing LLMs in HEOR necessitates robust security measures to ensure compliance with the European Union’s General Data Protection Regulation (GDPR) and the United States’ Health Insurance Portability and Accountability Act (HIPAA) when handling sensitive data.

MTRC shares the most relevant and impactful publications in the field of market access and HEOR for medical technologies in Europe through its EU HTA Publications Digest. In a recent publication, Gupte et al. conducted a review of accelerated approval pathways for medical devices in the United States and the European Union. The authors found that while the US Breakthrough Devices Program granted marketing authorization to just 12.3% of 1,041 designated devices between 2015 and 2024, approval was achieved substantially faster than through standard routes. In the EU, where no specific accelerated pathway exists, newly introduced Medical Device and Health Technology Assessment Regulations aim to harmonize approvals, with joint clinical assessments set to begin in 2026. The authors highlight that aligning regulatory, funding, and coverage policies is essential for device accessibility, and call for global convergence of standards and post-market surveillance to balance innovation with patient safety.

MTRC shares the most relevant and impactful publications in the field of market access and HEOR for medical technologies in Europe through its Publications Digest. In a recent publication, Dietrich examined the current and potential roles of artificial intelligence in pricing, reimbursement, and market access (PRMA) processes, focusing on Germany and broader EU implications. The study highlighted that AI could help forecast HTA agency decisions and streamline tasks like literature reviews and submissions. However, its use in HTA remains limited due to strict transparency demands, the need for explainability and human oversight, and the sensitive nature of PRMA documentation, especially in critical negotiations. The author concludes that while AI has transformative potential, its adoption should be gradual and supported by close collaboration among stakeholders. Broader use will depend on robust evidence of performance and cost-effectiveness compared to traditional methods.

MTRC shares the most relevant and impactful publications in the field of market access and HEOR for medical technologies in Europe through its Sustainability Publications Digest. In a recent publication, Godard et al. assessed the carbon footprint of a French nuclear medicine department by comprehensively analyzing both direct and indirect greenhouse gas emissions from diagnostic and therapeutic activities. The study found that, in 2022, total emissions reached 772 tons of CO2 equivalent, with patient and staff transport accounting for the majority (67%) of emissions, followed by procurement and energy use. These findings highlight that indirect emissions constitute the primary environmental burden in tertiary healthcare settings.

MTRC shares the most relevant and impactful publications in the field of market access and HEOR for medical technologies in Europe through its Health Economic Publications Digest. In a recent publication, Fleurence et al. introduced a structured taxonomy of generative AI in health economics and outcomes research (HEOR). The authors explore foundational concepts and map emerging applications across domains such as economic modeling, real-world evidence, and dossier development. Key methodological tools - including prompt engineering, retrieval-augmented generation, domain-specific models, and model fine-tuning - are discussed as means to enhance performance and reliability. While the transformative potential of generative AI in HEOR is recognized, the study highlights ongoing challenges around bias, reproducibility, and practical implementation. The report calls for deeper integration of HEOR expertise into AI development to leverage these technologies in health decision-making responsibly.