Abstract: PUB105
Leveraging Life Cycle Assessment to Improve Sustainability and Resiliency of Dialysis Options for Patients with ESKD
Session Information
Category: Dialysis
- 801 Dialysis: Hemodialysis and Frequent Dialysis
Authors
- Li, Amy Shijia, University of Colorado Anschutz Medical Campus School of Medicine, Aurora, Colorado, United States
- Yoder, Eli, University of Colorado Boulder, Boulder, Colorado, United States
- Young, Sarah Elizabeth, University of Colorado Anschutz Medical Campus School of Medicine, Aurora, Colorado, United States
- Cook, Sherri Sherri Cook, University of Colorado Boulder, Boulder, Colorado, United States
Background
Dialysis is a lifesaving but water, power, and resource-hungry treatment for patients with end-stage kidney disease (ESKD), who rely on a range of modalities including in-center hemodialysis (HD), home peritoneal dialysis (PD), and home HD, and are vulnerable to extreme weather events. Namely, Hurricane Helene in 2024 disabled a major manufacturing plant vital to the PD supply chain for 8 months. Hurricane Katrina in 2005 caused extended closures of 94 dialysis centers, affecting >6,000 patients. In the face of increasing extreme weather threats, there is a need to make dialysis treatment more resilient, so patients retain consistent access to their lifesaving treatments. Herein, we propose the first comparative analysis of different dialysis modalities utilizing life cycle assessment (LCA) that will provide an urgently needed framework to inform technological improvements to increase the resiliency and sustainability of each dialysis modality after extreme weather events.
Methods
This study will use quantitative sustainable design, including LCA, to quantify resource consumption, including power and water, to identify opportunities to reduce resource use. Digital twins will be created from a range of representative patients to model clinical outcomes after various extreme weather events (e.g., hurricane, heat wave). In-depth improvement analysis – including uncertainty, sensitivity, and process contribution analyses – will also be performed to maximize patient outcomes and minimize burden shifting (defined as a change in technology that results in changes to the type, timing, or location of pollution rather than achieving a global reduction in pollution).
Results
We expect to identify the most resilient modality based on key patient characteristics (e.g., rural vs urban) and extreme event. We will also gain valuable insight into key sustainability targets for each dialysis modality. These data can then be used to build resilience in the dialysis population, especially by informing dialysis technology development, deployment, and selection under various conditions.
Conclusion
Our study will provide critical insight into how dialysis care can be optimized in the face of extreme weather events, informing clinical decision-making, best practices, technological innovations, and policymaking.