Personalized Risk‑Prediction Tool for Deceased Donor Kidney Offers: Stakeholder Perspectives from a Qualitative Study

Background: Rising kidney discard rates and uncertainty around accepting higher-risk donor kidneys highlight the need for decision-support tools that integrate donor and recipient factors and communicate risk in ways that are understandable and usable at the time of offer. Conventional indices (e.g., KDPI/KDRI) provide population-level signals but do not deliver individualized, cognitively accessible information aligned with real-time clinical workflows. Objective: To describe how key transplant stakeholders—patients, coordinators, and providers—interpret and evaluate a prototype Kidney Risk Calculator app that generates donor–recipient–specific survival projections, and to identify the content, format and features, and functionality needed for clinically meaningful, patient-centered decision support. Design: Qualitative study using focus groups and individual interviews. Setting: University of New Mexico Hospital (UNMH) Kidney Transplant Center. Participants: Five patients (four transplant candidates and one patient advocate), three transplant coordinators, and five transplant providers (3 attending physicians and 2 advanced practice practitioners). Methods: Semi-structured sessions (45–60 minutes) with 13 stakeholders (patients, coordinators, and providers) included a live app demonstration and explored usability, interpretability, contextual information needs, perceived clinical utility, and anticipated barriers/facilitators. Data were collected via one coordinator focus group, one patient focus group, and five provider interviews; sessions were recorded, transcribed, de-identified, and analyzed using inductive reflexive thematic analysis. Results: Stakeholders affirmed the value of personalized projections as an adjunct to clinical judgment, particularly for higher-risk offers. Participants prioritized: 1) Content—clear education on hepatitis C virus (HCV)-positive donors and Public Health Service (PHS) risk criteria; plain explanations of Calculated Panel Reactive Antibody (CPRA); and framing that makes time on dialysis and trade-offs salient; 2) Format & Features—plain-language narratives, percentages rather than decimals, simple visuals, minimized acronyms, U.S. customary units, and a stepwise (“TurboTax‑like”) input flow preferred by patients; and 3) Functionality—attention to cognitive load and workflow alignment, given phone-based time pressure and digital-access constraints. Stakeholders emphasized that the tool’s value hinges on clarity, context, and workflow fit—not predictive accuracy alone. Limitations: Single‑center, formative prototype study with a modest sample; findings are illustrative and may have limited transferability. Participants reacted to a demonstration rather than using the app during real‑time offer calls; convenience/email recruitment and Zoom‑only English sessions may introduce selection bias; team involvement in app development may contribute residual confirmation bias despite mitigation. Conclusions: Early stakeholder input suggests that a kidney offer decision support tool should integrate individualized predictions with plain language explanations, contextual information that addresses common misconceptions, workflow aligned functionality, and accessible outputs. Tools designed and implemented with these features may support acceptance of medically complex kidneys and may help reduce offer bypass and organ discard. These inferences reflect stakeholder perceptions in a formative qualitative study and warrant prospective evaluation.