<p><b><i>Background:</i></b> Thirty-day hospital readmissions are common
among maintenance dialysis patients. Prior studies have evaluated
easily measurable readmission risk factors such as comorbid conditions,
laboratory results, and hospital discharge day. We undertook this
prospective study to investigate the associations between
hospital-assessed depression, health literacy, social support, and
self-rated health (separately) and 30-day hospital readmission among
dialysis patients. <b><i>Methods:</i></b> Participants were recruited
from the University of North Carolina Hospitals, 2014-2016. Validated
depression, health literacy, social support, and self-rated health
screening instruments were administered during index hospitalizations.
Multivariable logistic regression models with 30-day readmission as the
dependent outcome were used to examine readmission risk factors. <b><i>Results:</i></b>
Of the 154 participants, 58 (37.7%) had a 30-day hospital readmission.
In unadjusted analyses, individuals with positive screening for
depression, lower health literacy, and poorer social support were more
likely to have a 30-day readmission (vs. negative screening). Positive
depression screening and poorer social support remained significantly
associated with 30-day readmission in models adjusted for race, heart
failure, admitting service, weekend discharge day, and serum albumin:
adjusted OR (95% CI) 2.33 (1.02-5.15) for positive depressive symptoms
and 2.57 (1.10-5.91) for poorer social support. The area under the
receiver operating characteristic curve (AUC) of the multivariable model
adjusted for social support status was significantly greater than the
AUC of the multivariable model without social support status (test for
equality; <i>p</i> value = 0.04). <b><i>Conclusion:</i></b> Poor social
support and depressive symptoms identified during hospitalizations may
represent targetable readmission risk factors among dialysis patients.
Our findings suggest that hospital-based assessments of select
psychosocial factors may improve readmission risk prediction.</p