Plain Language Summary

What is it about? Health technology assessment (HTA) frameworks currently lack adequate methods to evaluate the environmental impacts of digital health technologies (DHTs). This is problematic because the healthcare sector generates approximately 4.6% of global greenhouse gas emissions, with supply chains accounting for 71% of healthcare's carbon footprint. While digital health technologies, such as telehealth platforms, electronic health records, and artificial intelligence tools, can reduce emissions by limiting patient travel and optimizing resources, they also create environmental impacts through energy consumption, data storage, and electronic waste. The existing HTA models provide limited guidance for incorporating environmental factors, potentially undermining health systems' net-zero commitments by 2050. This study proposes integrating environmental sustainability into HTA to ensure DHTs deliver value for both population and planetary health.

How was the research conducted? The research employs a comprehensive review of current HTA frameworks and environmental assessment approaches for DHTs. The authors analyzed existing literature on environmental impacts of DHTs, examining both benefits, like reduced travel emissions, and drawbacks, such as data center energy consumption and electronic waste. They evaluated 2 main assessment approaches: a parallel approach where environmental data is presented alongside traditional HTA domains, and an integrated approach where health and environmental effects are combined into a single function. The researchers examined case examples of telehealth platforms, electronic health records, and artificial intelligence (AI) diagnostic tools to illustrate potential environmental impacts. This methodology was chosen to identify gaps in current assessment frameworks and propose practical solutions for integration.

What were the results? The primary finding is that environmental sustainability must be systematically incorporated into HTA frameworks for DHTs through environmental lifecycle assessments that evaluate impacts from creation to disposal. The authors identified that digital infrastructure generates substantial emissions, with data storage and transfer responsible for more than 60% of many systems' environmental impact. They discovered that while DHTs can reduce healthcare's environmental footprint through telemedicine and optimized resource use, these benefits must be balanced against impacts from electronic waste, rare mineral extraction, and energy consumption. Surprisingly, the top 20 AI systems alone produce approximately 103 million metric tons of carbon dioxide-equivalent emissions—comparable to the annual footprint of 22 million people.

Why are the results important? These findings have significant real-world implications for ensuring digital health innovations advance both human and planetary health simultaneously. The integration of environmental sustainability into HTA could fundamentally change how healthcare technologies are evaluated, designed, and implemented, promoting lower-impact innovations that maintain clinical effectiveness. Healthcare providers, patients, and technology developers would benefit from clearer environmental impact information, supporting more sustainable purchasing decisions and incentivizing eco-friendly design practices. Long-term, this approach could help healthcare systems meet their net-zero commitments by 2050, while preventing the estimated $1.1 trillion in additional healthcare costs and 14.5 million deaths projected from climate-related disasters.

What are the strengths and weaknesses of this study? The study's primary strength is its comprehensive examination of both parallel and integrated approaches to environmental sustainability assessment in HTA, providing practical frameworks for implementation. However, a significant limitation is the lack of standardized methods and tools for healthcare-specific environmental lifecycle assessments, particularly for DHTs in lower and middle-resource settings. Future research should focus on developing validated environmental impact "aversion parameters" equivalent to inequality aversion parameters used in distributional cost-effectiveness analysis, which would help quantify societal preferences for balancing health outcomes against environmental impacts across different global contexts.

Note: This content was created with assistance from artificial intelligence (AI) and has been reviewed and edited by ISPOR staff. For more information or for inquiries on ISPOR’s AI policy, click here or contact us at info@ispor.org.