Date: Tuesday, June 4, 2019
Session Time: 6:00pm-7:00pm
Presentation Time: 6:00pm-7:00pm
Location: Hall C & D
*Purpose: Patient and graft survival have been criticized as imprecise measures of transplant program quality. Thirty-day (30d) readmission rates, available nationally and attainable locally, may better reflect the efficacy of multi-disciplinary transplant care and are therefore an important benchmark for quality improvement purposes. Nationally, renal transplant recipients incur a 31% readmission rate in the first month. The impact of early (30d) readmission rates at single centers provides a useful benchmark and may identify modifiable program-specific issues to reduce readmission and improve patient outcomes.
*Methods: We reviewed 269 consecutive kidney transplant recipients over a five-year period (2012-2016). Readmissions were identified from RIH transplant clinic records and individual patient records were reviewed to abstract data with >1 year follow-up on all patients. Prior to discharge all patients met with a transplant coordinator (RN), pharmacist, and nutritionist for formal teaching sessions. All patients were seen by a visiting nurse (VNA) at home, typically for two weeks after discharge. All statistical analyses were conducted using SAS Software 9.4 (SAS Inc., Cary, NC). Alpha was established at the .05 level and all interval estimates were calculated for 95% confidence.
*Results: The patients were male (59%), white (72%), diabetic (27%) and the majority (63.9%) had only public insurance. The median age at transplant was 55, days on dialysis 1039, and cold ischemia time 15 hours (deceased donors). Deceased donors (n=187, 78 DCD, 109 DBD) predominated and 1/3 of these developed DGF. Median length of stay was 6 days (IQR 5-7) days. Twenty-one percent were readmitted within 30d; 75% for surgical, metabolic, infectious complications, or acute kidney injury. Deceased kidney donation, ATG induction, diabetes, public insurance, and weekend discharge were all identified as risk factors for readmission (Table 1). Readmission was not correlated with risk of death (5.4% at 44 months: HR 2.2 (95% CI [0.7, 6.6]; p=0.1473) or graft loss.
*Conclusions: Early readmission after renal transplantation was common. The reasons were multiple and not associated with demographic factors beyond insurance type, which may reflect socioeconomic status. Deceased donation and poor early allograft function were associated with increased risk for readmission. A multi-disciplinary approach to discharge planning and home VNA care may reduce readmissions, but most complications and adverse events were unpredictable and required hospital-level of care.
|Item||OR||95% CI||P value|
|DGF||2.4||1.3 – 4.5||0.006|
|IDDM||2.1||1.1 – 3.9||0.02|
|Public Insurance||2.2||1.1 – 4.4||0.03|
|ATG use||2.3||1.2 – 4.3||0.01|
|PRA > 20%||1.7||0.9 – 3.2||0.09|
|DCD vs, live donor||3.4||1.4 – 8.3||0.007|
|DBD vs. live donor||3.0||1.3 – 7.1||0.01|
To cite this abstract in AMA style:Kim S, Osband A, Merhi B, Bayliss G, Gohh R, Morrissey P. Early Readmission After Renal Transplant As A Valuable Quality Measure [abstract]. Am J Transplant. 2019; 19 (suppl 3). https://atcmeetingabstracts.com/abstract/early-readmission-after-renal-transplant-as-a-valuable-quality-measure/. Accessed April 15, 2021.
« Back to 2019 American Transplant Congress