Leveraging Natural Language Processing to Identify Variation in Kidney Transplant Access

There are significant sex, racial, ethnic, and socioeconomic disparities in kidney transplantation in the United States, but upstream factors driving these disparities are understudied because prewaitlisting data are not yet routinely collected by national data surveillance systems.

To address this gap, we developed a rule-based semiautomated natural language processing (NLP) pipeline to extract prewaitlist milestones from nephrologist and social worker clinical notes at a nonprofit dialysis organization in New York City. Our outcomes were (i) transplant discussed with the patient; (ii) patient interest in transplant; (iii) transplant referral; and (iv) receipt of a kidney transplant. In a retrospective observational cohort study of patients with incident end-stage kidney disease (ESKD) receiving dialysis, we evaluated sex-based, racial and ethnic, and socioeconomic variation (on the basis of primary insurance payer and census block group-level Area Deprivation Index [ADI]) in the outcomes of interest using multivariable logistic regression and Cox models.

Our NLP pipeline showed excellent precision, recall, and F1 scores > 0.8. Among 2624 patients, documentation of transplant discussion (adjusted subhazard ratio [sHR]: 1.30; 95% confidence interval [CI]: 1.01-1.67) and patient interest (sHR: 2.11; 95% CI: 1.65-2.69) were associated with a greater likelihood of receiving a kidney transplant. Patients with Medicaid (vs. non-Medicaid, adjusted odds ratio [OR]: 0.73; 95% CI:, 0.59-0.90) were less likely to have interest in transplant documented. Sex, race and ethnicity, and ADI were not associated with time to transplant referral in adjusted analyses. Non-Hispanic Black race (adjusted sHR: 0.40; 95% CI: 0.23-0.69), Medicaid insurance (adjusted sHR: 0.73; 95% CI: 0.56-0.94), and below-median ADI (adjusted sHR: 0.77; 95% CI: 0.60-0.98) were associated with lower receipt of a kidney transplant.

Using a novel NLP pipeline, we identified socioeconomic disparities in the documentation of patient interest in transplant, but not referrals. Patient-level interventions to increase interest in transplantation may be needed to address disparities in kidney transplantation.