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During the congress, E-Posters will be accessible to all participants on the congress website 24/7, as well as in the E-poster stations in the congress center.
Preparing your E-Poster
Please review the E-Poster format requirements carefully when preparing your E-Poster. Should your E-Poster not meet the mentioned requirements, it may not be displayed as described above.
E-Poster Submission Deadline
Please prepare and upload your E-Poster no later than March 14, 2026 11.59PM CET. After this date, you will no longer be able to prepare and upload your E-poster and it will not be displayed and accessible on the congress website.
Please follow the instructions below to input your abstract title.
Abstract titles should be brief and reflect the content of the abstract.
While many mortality risk prediction tools for people with kidney failure are available, none involved end-users during the design process, nor are widely used in clinical practice. We aimed to identify the needs and preferences of end-users to inform the development and enhance the usability of a mortality risk prediction tool for people with kidney failure.
A half-day, online consensus workshop was conducted using a modified nominal group technique. People with lived experience of kidney failure (patients with or without receipt of kidney replacement therapy and their caregivers) or kidney failure management (healthcare providers and policymakers) were recruited from across Canada. Preferences were elicited in three topic areas: the tool’s intended use, timing (prediction horizon and update frequency), and relevant predictor variables. Conventional content analysis of discussion transcripts was conducted to elaborate on the findings.
Eighteen individuals from across five provinces participated in the workshop, including seven patients, three caregivers, and eight healthcare providers or policymakers. Participants prioritized the following: (1) Tool use within clinics and in consultation with nephrologists; (2) Personalization of the prediction time horizons and reassessment of risk prediction following changes in clinical condition; (3) Inclusion of co-existing conditions, kidney failure characteristics (e.g., unplanned dialysis start), and frailty status as key predictor variables. Analysis of transcripts identified several factors influencing the tool’s usability, including provider trust, comfort in discussing mortality risk, patient privacy, availability of follow-up and support systems, patient readiness, and feasibility of incorporating desired predictor variables.
End-users of mortality prediction tools for people with kidney failure prioritized design and use considerations that have not been addressed in existing tools. Co-design of future tools to align with end-user preferences may enhance their usability and currently limited uptake.
