Prior to the 2014 implementation of a new kidney allocation system by the United Network for Organ Sharing, white patients were more likely to receive a kidney transplant than black or Hispanic patients. To determine the effect of the new kidney allocation system on these disparities, we examined 179,071 waitlisting events from the United Network for Organ Sharing database from June 2013 to September 2016 and calculated monthly kidney transplantation rates among waitlisted patients. Implementation of the new system was associated with a narrowing of the disparity in the average monthly kidney transplantation rate by 0.29 percentage points for blacks compared to whites (p<0.001) and 0.24 percentage points for Hispanics compared to whites (p<0.001), resulting in both disparities becoming insignificant after implementation of the new system (p=0.45, p=0.18).

We previously developed a mobile- and web-based decision aid (iChoose Kidney) that displays individualized risk estimates of survival and mortality, for the treatment modalities of dialysis versus kidney transplantation. We examined the effect of iChoose Kidney on change in transplant knowledge and access to transplant in a randomized controlled trial among patients presenting for evaluation in three transplant centers. A total of 470 patients were randomized to standard transplantation education (control) or standard education plus iChoose Kidney (intervention). Change in transplant knowledge (primary outcome) among intervention versus control patients was assessed using nine items in pre- and postevaluation surveys. Access to transplant (secondary outcome) was defined as a composite of waitlisting, living donor inquiries, or transplantation. Among 443 patients (n = 226 intervention; n = 216 control), the mean knowledge scores were 5.1 ± 2.1 pre- and 5.8 ± 1.9 postevaluation. Change in knowledge was greater among intervention (1.1 ± 2.0) versus control (0.4 ± 1.8) patients (P < .0001). Access to transplantation was similar among intervention (n = 168; 74.3%) versus control patients (n = 153; 70.5%; P = .37). The iChoose Kidney decision aid improved patient knowledge at evaluation, but did not impact transplant access. Future studies should examine whether combining iChoose Kidney with other interventions can increase transplantation. (Clinicaltrials.gov NCT02235571).

The impact of a new national kidney allocation system (KAS) on access to the national deceased-donor waiting list (waitlisting) and racial/ethnic disparities in waitlisting among US end-stage renal disease (ESRD) patients is unknown. We examined waitlisting pre- and post-KAS among incident (N = 1 253 100) and prevalent (N = 1 556 954) ESRD patients from the United States Renal Data System database (2005-2015) using multivariable time-dependent Cox and interrupted time-series models. The adjusted waitlisting rate among incident patients was 9% lower post-KAS (hazard ratio [HR]: 0.91; 95% confidence interval [CI], 0.90-0.93), although preemptive waitlisting increased from 30.2% to 35.1% (P < .0001). The waitlisting decrease is largely due to a decline in inactively waitlisted patients. Pre-KAS, blacks had a 19% lower waitlisting rate vs whites (HR: 0.81; 95% CI, 0.80-0.82); following KAS, disparity declined to 12% (HR: 0.88; 95% CI, 0.85-0.90). In adjusted time-series analyses of prevalent patients, waitlisting rates declined by 3.45/10 000 per month post-KAS (P < .001), resulting in ≈146 fewer waitlisting events/month. Shorter dialysis vintage was associated with greater decreases in waitlisting post-KAS (P < .001). Racial disparity reduction was due in part to a steeper decline in inactive waitlisting among minorities and a greater proportion of actively waitlisted minority patients. Waitlisting and racial disparity in waitlisting declined post-KAS; however, disparity remains.

Living ACTS is effective at increasing and maintaining knowledge about LDKT among African American patients with end-stage renal disease who are considering transplant.

Background Racial disparities persist in access to kidney transplantation. Racial differences in preemptive referral, or referral prior to dialysis start, may explain this discrepancy. Methods Patient-level data on kidney transplant referrals (2005–2012) from all Georgia transplant centers were linked to the United States Renal Data System to examine racial disparities in preemptive referral, waitlisting, and living donor transplant. Adjusted logistic regression and Cox proportional hazard models determined the associations between race (African American vs. white) and preemptive referral, and placement on the waitlist or receipt of a living donor kidney, respectively. Results Among 7,752 adults referred for transplant evaluation, 20.38% (n=1,580) were preemptively referred. The odds of African Americans being preemptively referred for transplant evaluation were 37% (OR=0.63; (95% CI: 0.55 0.71)) lower than whites. Among preemptively referred patients, there was no racial difference (African Americans compared to whites HR=0.96; (95% CI 0.88, 1.04)) in waitlisting. However, African Americans were 70% less likely than whites to receive a living donor transplant (HR=0.30; (95% CI: 0.21, 0.42)). Conclusion Racial disparities in transplant receipt may be partially explained by disparities in preemptive referral. Interventions to reduce racial disparities in kidney transplant access may need to be targeted earlier in the disease process.

Background and objectives Barriers exist in access to kidney transplantation, where minority and patients with low socioeconomic status are less likely to complete transplant evaluation. The purpose of this study was to examine the effectiveness of a transplant center-based patient navigator in helping patients at high risk of dropping out of the transplant evaluation process access the kidney transplant waiting list.Design, setting, participants & measurements We conducted a randomized, controlled trial of 401 patients (n=196 intervention and n=205 control) referred for kidney transplant evaluation (January 2013 to August 2014; followed through May 2016) at a single center. A trained navigator assisted intervention participants from referral to waitlisting decision to increase waitlisting (primary outcome) and decrease time from referral to waitlisting (secondary outcome). Time-dependent Cox proportional hazards models were used to determine differences in waitlisting between intervention and control patients.Results At study end, waitlisting was not significantly different among intervention (32%) versus control (26%) patients overall (P=0.17), and time from referral to waitlisting was 126 days longer for intervention patients. However, the effectiveness of the navigator varied from early (,500 days from referral) to late ($500 days) followup. Although no difference in waitlisting was observed among intervention (50%) versus control (50%) patients in the early period (hazard ratio, 1.03; 95% confidence interval, 0.69 to 1.53), intervention patients were 3.3 times more likely to be waitlisted after 500 days (75% versus 25%; hazard ratio, 3.31; 95% confidence interval, 1.20 to 9.12). There were no significant differences in intervention versus control patients who started evaluation (85% versus 79%; P=0.11) or completed evaluation (58% versus 51%; P=0.14); however, intervention patients had more living donor inquiries (18% versus 10%; P=0.03).Conclusions A transplant center-based navigator targeting disadvantaged patients improved waitlisting but not until after 500 days of follow-up. However, the absolute effect was relatively small.

Background Despite a significant survival advantage of kidney transplantation compared to dialysis, nearly one-third of end stage renal disease (ESRD) patients are not educated about kidney transplantation as a treatment option at the time of ESRD diagnosis. Access to individualized, evidence-based prognostic information is needed to facilitate and encourage shared decision making about the clinical implications of whether to pursue transplantation or long-term dialysis. Study Design We utilized a national cohort of incident ESRD patients in the U.S. Renal Data System surveillance registry from 2005 to 2011 to develop and validate prediction models for risk of 1- and 3-year mortality among dialysis vs. kidney transplantation. Using these data, we developed a mobile clinical decision aid that provides estimates of risks of death and survival on dialysis compared to kidney transplantation. Results Factors included in the mortality risk prediction models for dialysis and transplantation included age, race/ethnicity; dialysis vintage, and comorbidities, including diabetes, hypertension, cardiovascular disease, and low albumin. Among the validation cohorts, the discriminatory ability of the model for 3-year mortality was moderate (c-statistic = 0.7047 [95% CI: 0.7029-0.7065] for dialysis and 0.7015 [95% CI: 0.6875-0.7155] for transplant). We used these risk prediction models to develop an electronic, user-friendly, mobile (iPad, iPhone, and website) clinical decision aid called iChoose Kidney. Conclusions The use of a mobile clinical decision aid comparing individualized mortality risk estimates for dialysis vs. transplantation could enhance communication between ESRD patients and their clinicians when making decisions about treatment options.

BACKGROUND: A patient navigation process is required for accreditation by the National Accreditation Program for Breast Centers (NAPBC). Patient navigation has previously been shown to improve timely diagnosis in patients with breast cancer. This study sought to assess the effect of nurse navigation on timeliness of care following the diagnosis of breast cancer by comparing patients who were treated in a comprehensive cancer center with and without the assistance of nurse navigation. METHODS: Navigation services were initiated at an NAPBC-accredited comprehensive breast center in July 2010. Two 9-month study intervals were chosen for comparison of timeliness of care: