Patients considering renal transplantation face an increasingly complex array of choices as a result of the revised kidney transplant allocation system. Decision aids have been shown to improve patient decision-making through the provision of detailed, relevant, individualized clinical data. A mobile iOS-based application (app) including animated patient education and individualized risk-adjusted outcomes following kidney transplants with varying donor characteristics and DSA waiting times was piloted in two large US transplant programs with a diverse group of renal transplant candidates (N = 81). The majority (86%) of patients felt that the app improved their knowledge and was culturally appropriate for their race/ethnicity (67%-85%). Patients scored significantly higher on transplant knowledge testing (9.1/20 to 13.8/20, P < .001) after viewing the app, including patients with low health literacy (8.0 to 13.0, P < .001). Overall knowledge of and interest in living and deceased donor kidney transplantation increased. This pilot project confirmed the benefit and cultural acceptability of this educational tool, and further refinement will explore how to better communicate the risks and benefits of nonstandard donors.

BACKGROUND: Kidney transplant (KT) candidates with HIV face higher mortality on the waitlist compared with candidates without HIV. Because the HIV Organ Policy Equity (HOPE) Act has expanded the donor pool to allow donors with HIV (D + ), it is crucial to understand whether this has impacted transplant rates for this population. METHODS: Using a linkage between the HOPE in Action trial (NCT03500315) and Scientific Registry of Transplant Recipients, we identified 324 candidates listed for D + kidneys (HOPE) compared with 46 025 candidates not listed for D + kidneys (non-HOPE) at the same centers between April 26, 2018, and May 24, 2022. We characterized KT rate, KT type (D + , false-positive [FP; donor with false-positive HIV testing], D - [donor without HIV], living donor [LD]) and quantified the association between HOPE enrollment and KT rate using multivariable Cox regression with center-level clustering; HOPE was a time-varying exposure. RESULTS: HOPE candidates were more likely male individuals (79% versus 62%), Black (73% versus 35%), and publicly insured (71% versus 52%; P  < 0.001). Within 4.5 y, 70% of HOPE candidates received a KT (41% D + , 34% D - , 20% FP, 4% LD) versus 43% of non-HOPE candidates (74% D - , 26% LD). Conversely, 22% of HOPE candidates versus 39% of non-HOPE candidates died or were removed from the waitlist. Median KT wait time was 10.3 mo for HOPE versus 60.8 mo for non-HOPE candidates ( P  < 0.001). After adjustment, HOPE candidates had a 3.30-fold higher KT rate (adjusted hazard ratio = 3.30, 95% confidence interval, 2.14-5.10; P  < 0.001). CONCLUSIONS: Listing for D + kidneys within HOPE trials was associated with a higher KT rate and shorter wait time, supporting the expansion of this practice for candidates with HIV.