Predicting and Preventing 30-Day Readmission Following Kidney Transplantation: A Single Center Study

R. Khaim,¹ V. Nair.^1,2

¹Recanati Miller Transplant Institute, The Mount Sinai Hospital, NY, NY
²Medicine, Icahn School of Medicine at Mount Sinai, NY, NY.

Meeting: 2015 American Transplant Congress

Abstract number: 200

Keywords: High-risk, Kidney transplantation, Risk factors

Purpose: Readmissions are a major morbidity following kidney transplantation (KT). Prior studies report a 30-day readmission rate of 30%. Limited data exist on risk facotors and preventative stratigies for readmission. We reviewed 4 years of KT at our institution to identify incidence and risk factors for 30-day readmission. We evaluated our discharge (d/c) education protocol (DEP) as a strategy to prevent readmission.

Methods: Retrospective chart review of adult KT at Mt. Sinai between 2009 and 2013 was performed. Pts sent to a skilled facility, multi-organ transplants, primary non-function, and death before d/c were excluded. The following factors were assessed in relation to readmission: presence of diabetes (DM), gender, race, d/c yr, living vs deceased donor, delayed graft function (DGF), age and length of stay (LOS). We evaluated our DEP in preventing readmissions which includes 1:1 teaching, recipients attending a teaching class, and having support present for teaching. Chi-square test was used for categorical variables and the t-test and the Kruskal-Wallis test were used as appropriate for continuous variables. Multivariate logistic regression was performed to assess independent predictors of readmission.

Results: 681 patients meet study criteria of which 223 had a 30-day readmission (32.7%). Factors associated with readmission included DM status (52% vs 39%, p=0.002), LOS (6.2 va 5.1 days, p=0.006), ethnicity (p=0.024) and completing DEP (63% vs 91%, p<0.0001). DGF after KT and year of discharge (2009-2011 vs 2012) trended towards significance (p= 0.055; p=0.66 respectively). In the multivariate analysis the presence of DM increased odds of readmission while Asian ethnicity and completing DEP resulted in lower odds of readmission.

Predictors of 30-day Readmission

	Point estimate	95% CI
DM vs no DM	1.493	1.015	2.195
Age	0.992	0.978	1.006
LOS	1.032	0.994	1.070
Race: Asian vs White	0.409	0.210	0.797
Black vs White	0.707	0.460	1.087
Hispanic vs White	0.678	0.408	1.126
Mid-East vs White	3.050	0.704	13.218
DEP met vs not met	0.164	0.104	0.258

Conclusion: Readmissions were frequent and predominantly occurred in patients with DM, while Asian ethnicity and completing our DEP had a protective effect. Focusing on patients with DM and having patients engage in 1:1 teaching as well as group teaching with support present, may help lower readmission rates in this high risk population.

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