title: Predictors of 30-Day Hospital Readmission among Maintenance Hemodialysis Patients: A Hospital's Perspective.
abstract: Over 35% of patients on maintenance dialysis are readmitted to the hospital within 30 days of hospital discharge. Outpatient dialysis facilities often assume responsibility for readmission prevention. Hospital care and discharge practices may increase readmission risk. We undertook this study to elucidate risk factors identifiable from hospital-derived data for 30-day readmission among patients on hemodialysis.
  
  
  
  Data were taken from patients on maintenance hemodialysis discharged from University of North Carolina Hospitals between May of 2008 and June of 2013 who received in-patient hemodialysis during their index hospitalizations. Multivariable logistic regression models with 30-day readmission as the dependent outcome were used to identify readmission risk factors. Models considered variables available at hospital admission and discharge separately.
  
  
  
  Among 349 patients, 112 (32.1%) had a 30-day hospital readmission. The discharge (versus admission) model was more predictive of 30-day readmission. In the discharge model, malignancy comorbid condition (odds ratio [OR], 2.08; 95% confidence interval [95% CI], 1.04 to 3.11), three or more hospitalizations in the prior year (OR, 1.97; 95% CI, 1.06 to 3.64), ≥10 outpatient medications at hospital admission (OR, 1.69; 95% CI, 1.00 to 2.88), catheter vascular access (OR, 1.82; 95% CI, 1.01 to 3.65), outpatient dialysis at a nonuniversity-affiliated dialysis facility (OR, 3.59; 95% CI, 2.03 to 6.36), intradialytic hypotension (OR, 3.10; 95% CI, 1.45 to 6.61), weekend discharge day (OR, 1.82; 95% CI, 1.01 to 3.31), and serum albumin <3.3 g/dl (OR, 4.28; 95% CI, 2.37 to 7.73) were associated with higher readmission odds. A decrease in prescribed medications from admission to discharge (OR, 0.20; 95% CI, 0.08 to 0.51) was associated with lower readmission odds. Findings were robust across different model-building approaches.
  
  
  
  Models containing discharge day data had greater predictive capacity of 30-day readmission than admission models. Identified modifiable readmission risk factors suggest that improved medication education and improved transitions from hospital to community may potentially reduce readmissions. Studies evaluating targeted transition programs among patients on dialysis are needed.
authors.affiliation: University of North Carolina Kidney Center, Division of Nephrology and Hypertension, Department of Medicine and.|The Cecil G. Sheps Center for Health Services Research, University of North Carolina, Chapel Hill, North Carolina.
authors.forename: Jennifer E
authors.initials: JE
authors.lastname: Flythe
authors.affiliation: University of North Carolina Kidney Center, Division of Nephrology and Hypertension, Department of Medicine and.
authors.forename: Suzanne L
authors.initials: SL
authors.lastname: Katsanos
authors.affiliation: University of North Carolina Kidney Center, Division of Nephrology and Hypertension, Department of Medicine and.
authors.forename: Yichun
authors.initials: Y
authors.lastname: Hu
authors.affiliation: University of North Carolina Kidney Center, Division of Nephrology and Hypertension, Department of Medicine and.
authors.forename: Abhijit V
authors.initials: AV
authors.lastname: Kshirsagar
authors.affiliation: University of North Carolina Kidney Center, Division of Nephrology and Hypertension, Department of Medicine and.
authors.forename: Ronald J
authors.initials: RJ
authors.lastname: Falk
authors.affiliation: Division of General Medicine and Clinical Epidemiology, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina; and.|The Cecil G. Sheps Center for Health Services Research, University of North Carolina, Chapel Hill, North Carolina.
authors.forename: Carlton R
authors.initials: CR
authors.lastname: Moore
mesh_terms: D000328:Adult; D000368:Aged; D000554:Ambulatory Care Facilities / Q000706:statistics & numerical data; D002408:Catheters, Indwelling / Q000706:statistics & numerical data; D015897:Comorbidity; D005260:Female; D006761:Hospitals; D006801:Humans; D007022:Hypotension / Q000453:epidemiology; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009369:Neoplasms / Q000453:epidemiology*; D010343:Patient Admission / Q000706:statistics & numerical data*; D010351:Patient Discharge / Q000706:statistics & numerical data*; D010359:Patient Readmission / Q000706:statistics & numerical data*; D019338:Polypharmacy; D006435:Renal Dialysis; D051436:Renal Insufficiency, Chronic / Q000453:epidemiology* / Q000628:therapy; D012307:Risk Factors; D012709:Serum Albumin / Q000378:metabolism; D013997:Time Factors
chemical_list: D012709:Serum Albumin
keywords: ESRD; Humans; Patient Discharge; Patient Readmission; Serum Albumin; hemodialysis; hospitalization; renal dialysis; risk factors