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. 2024 Mar;31(1):153-162.
doi: 10.1007/s10880-023-09953-5. Epub 2023 Mar 23.

Predicting Kidney Transplant Evaluation Non-attendance

Affiliations

Predicting Kidney Transplant Evaluation Non-attendance

C Graham Ford et al. J Clin Psychol Med Settings. 2024 Mar.

Abstract

Non-attendance to kidney transplant evaluation (KTE) appointments is a barrier to optimal care for those with kidney failure. We examined the medical and socio-cultural factors that predict KTE non-attendance to identify opportunities for integrated medical teams to intervene. Patients scheduled for KTE between May, 2015 and June, 2018 completed an interview before their initial KTE appointment. The interview assessed various social determinants of health, including demographic (e.g., income), medical (e.g. co-morbidities), transplant knowledge, cultural (e.g., medical mistrust), and psychosocial (e.g., social support) factors. We used multiple logistic regression analysis to determine the strongest predictor of KTE non-attendance. Our sample (N = 1119) was 37% female, 76% non-Hispanic White, median age 59.4 years (IQR 49.2-67.5). Of note, 142 (13%) never attended an initial KTE clinic appointment. Being on dialysis predicted higher odds of KTE non-attendance (OR 1.76; p = .02; 64% of KTE attendees on dialysis vs. 77% of non-attendees on dialysis). Transplant and nephrology teams should consider working collaboratively with dialysis units to better coordinate care, (e.g., resources to attend appointment or outreach to emphasize the importance of transplant) adjusting the KTE referral and evaluation process to address access issues (e.g., using tele-health) and encouraging partnership with clinical psychologists to promote quality of life for those on dialysis.

Keywords: Kidney transplantation; Non-attendance; Transplant evaluation.

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Conflict of interest statement

C. Graham Ford, Yuridia Leyva, Eric S. Kruger, Yiliang Zhu, Emilee Croswell, Kellee Kendall, Chethan Puttarajapa, Mary Amanda Dew, Yue Harn Ng, Mark L. Unruh, Larissa Myaskovsky declare that they have no conflict of interest.

Figures

Fig. 1
Fig. 1
Forest plot of predictors of clinic non-attendance in adjusted model

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