OBJECTIVES: Many healthcare systems around the world have pledged to contribute towards 'net zero' targets to reduce carbon emissions and other environmental harm. However, little has been said about how this will be done, nor whether those healthcare systems are prepared to trade off population health against environmental impact. This study explores the potential methods to incorporate environmental sustainability outcomes into health technology assessment (HTA).

METHODS: We assessed the different methods that are used to quantify environmental outcomes in areas such as (i) greenhouse gas emissions, (ii) water pollution, (iii) air pollution, (iv) waste, (v) biodiversity and (vi) resource depletion. We also interviewed a range of stakeholders to understand how different methods might be used to combine these outcomes with traditional health economic outcomes such as quality-adjusted life years and health system costs.

RESULTS: Of the domains examined, greenhouse gas emissions was the only area in which well-established methods currently exist to quantify the impact of a healthcare intervention. Some other domains (in particular biodiversity and resource depletion) are highly unlikely to be able to be quantified accurately, although this does not imply that the impact in these areas is small or does not matter. We also found that defining 'impact' is problematic, because an HTA should include all 'downstream' consequences, including those caused by the displacement of other interventions. When multiple comparators, pathways and scenarios are included in an evaluation, we demonstrate that this will be highly complex and/or unfeasible.

CONCLUSIONS: Healthcare interventions are likely to impact on several or all of the environmental domains and, therefore, it would not be appropriate to limit the inclusion of sustainability effects to only those that can be easily measured. As such, we recommend that sustainability outcomes are included in a deliberative manner in healthcare decision making, rather than be included in a quantitative framework.