Steps towards integrating environmental impacts into health economic evaluation: empirical starting points and methodological extensions

The healthcare sector is increasingly faced with the need to account for its environmental impacts, as reflected by various policies and research initiatives. While Health Economic Evaluation (HEE) is a key instrument for informing healthcare decisions, environmental impacts, such as eutrophication, ozone depletion, and fine particulate matter, among others, remain largely outside its scope. When environ-mental impacts are considered, the focus is often restricted to greenhouse gas emissions (GHG). Even for GHG, there is currently no standardized reporting framework to support the use of so-called cli-mate-extended HEE in evidence-based decision-making. This gap limits the potential of HEEs to con-tribute to sustainable healthcare systems by enabling greater climate and economic efficiency while enhancing health effects. This becomes particularly relevant in light of the rapid growth of digital health technologies. As interest in digital public health continues to grow, there is a need to assess how these innovations affect health outcomes at the population level and what their environmental footprint may entail.
Therefore, this cumulative dissertation addresses these challenges through four research questions (RQs): First, RQ1 investigates to what extent the Consolidated Health Economic Evaluation Reporting Standard (CHEERS) currently enables the reporting of climate impacts in climate-extended HEE and where specific extensions are necessary. Second, building on the previous research question, RQ2 ex-plores how a Delphi process can be designed to identify and validate reporting items for a climate-extended HEE. Third, by recognizing that only climate impacts are often included in HEE, RQ3 examines the feasibility of incorporating broader environmental impacts as costs into an existing HEE. Fourth, RQ4 assesses the health effects of a digital health application (DIHA) for obesity at the population level, as groundwork for a climate-extended HEE, which lies outside the scope of this dissertation.
These research questions are addressed across four modules (M): The first module (M1) analyses how climate impacts are considered in the CHEERS checklist, by reviewing current climate-extended HEE and ISO-Standards of Life Cycle Assessment (LCA) for measuring environmental impacts, and proposes a reporting standard called the CHEERS Climate Extension (CHEERS ClimatE). The second module (M2) outlines a study protocol for the development and validation of CHEERS ClimatE through the Delphi consensus process. The third module (M3) presents a feasibility study that incorporates environmental impacts as costs into an existing HEE of SARS-COV-2 surveillance strategies in Germany, using environ-mentally extended input-output LCA. The fourth module (M4) applies a dynamic health impact assess-ment (DYNAMO-HIA) to simulate and quantify the population-level health effects of an obesity inter-vention of a DIHA in Germany.
Together, these modules contribute to the growing body of research on climate- and environmental extended HEE and digital public health. The DYNAMO HIA model illustrates the potential of DIHA inter-vention for weight loss at the population level to reduce mortality and disease burden from stroke, diabetes, and ischemic heart disease. Thereby, it provides the foundation for a HEE currently in devel-opment, which links health outcomes from the HIA with associated (climate) costs. Furthermore, this dissertation contributes to the development of a broader methodological framework for reporting integrated climate impacts into HEE and advances methodological approaches for the inclusion of wid-er environmental impacts. Moreover, in response to the fact that six out of nine planetary boundaries have already been exceeded, groundwork has been laid to adapt a reporting standard that incorporates environmental impacts into HEE. This involves identifying areas where the CHEERS ClimatE proposal requires adaptation. Thus, this dissertation can promote sustainability in healthcare decision-making. In addition to methodological uncertainties, data limitations, and pricing variability, the findings highlight the need for standardized values for the integration of environmental and climate impacts as outcomes or costs. Future research should consider this when developing and validating the CHEERS ClimatE re-porting or even a future “CHEERS Environmental Extended" standard. Moreover, a further implication for research could be the use of environmental-extended HEE to capture, for instance, air pollution resulting from an intervention, which may subsequently be linked to a HIA to assess the associated health impacts. Further limitations of the dissertation relate to underlying assumptions made due to data gaps regarding the environmental footprint calculations, as well as the HIA. Future investigations should focus on generating openly accessible epidemiological and environmental data, particularly in the context of digital interventions for weight loss and long-term weight maintenance.