THE INFLUENCE OF ILLNESS BURDEN AND SOCIAL SUPPORT ON THE COMPLETION OF KIDNEY TRANSPLANT EVALUATION

Kidney transplantation is the preferred method of treatment to dialysis for end stage renal disease (ESRD) because of its many proven benefits over dialysis treatment. Patients interested in kidney transplantation must undergo a kidney transplant (KT) evaluation to determine their medical and psychosocial eligibility. A timely completion of the KT evaluation is critical for prompt listing for or the receipt of a KT. However, ESRD patients suffer from significant illness burden that interferes in their participation of life activities, which can affect their completion of KT evaluations. At the same time, the presence of social support is known to abate symptom burden and the perception of illness burden. This implies that social support has the potential to facilitate completions of KT evaluations by moderating illness burden. This novel study is the first to examine how social support buffers illness burden in affecting KT evaluation completion. This quantitative study involves 1,130 study participants recruited from the Starzl Transplant Institute of University of Pittsburgh Medical Center. The goals of this study are 1) to understand how demographic factors (age, gender, race and income), illness burden and social support independently affects time taken to complete KT evaluation, and 2) to assess how these factors interact in influencing time to complete KT evaluation. The hypothesis that social support buffers illness burden in the completion of KT evaluation was not supported. Instead social support demonstrated main effects on the completion of KT evaluation: higher level of perceived social support was associated with a higher rate of KT evaluation completion. Older age, lower income, African American race and greater illness comorbidity were associated with lower KT evaluation completion rates. Limitations of the study include: a single-center study with non-random patient participation, a limited examination of social network based on network size, and the violation of proportionality of hazard assumption in the Cox regression analysis.