title: Potentially Preventable 30-Day Hospital Readmissions at a Children's Hospital.
abstract: Hospital readmission rates are increasingly used to assess quality. Little is known, however, about potential preventability of readmissions among children. Our objective was to evaluate potential preventability of 30-day readmissions using medical record review and interviews.
  
  
  
  A cross-sectional study in 305 children (<18 years old) readmitted within 30 days to a freestanding children's hospital between December 2012 and February 2013. Interviews (N = 1459) were conducted with parents/guardians, patients (if ≥13 years old), inpatient clinicians, and primary care providers. Reviewers evaluated medical records, interview summaries, and transcripts, and then rated potential preventability. Multivariate regression analysis was used to identify factors associated with potentially preventable readmission. Adjusted event curves were generated to model days to readmission.
  
  
  
  Of readmissions, 29.5% were potentially preventable. Potentially preventable readmissions occurred sooner after discharge than non-potentially preventable readmissions (5 vs 9 median days; P < .001). The odds of a readmission being potentially preventable were greatest when the index admission and readmission were causally related (adjusted odds ratio [AOR]: 2.6; 95% confidence interval [CI]: 1.0-6.8) and when hospital (AOR: 16.3; 95% CI: 5.9-44.8) or patient (AOR: 7.1; 95% CI: 2.5-20.5) factors were identified. Interviews provided new information about the readmission in 31.2% of cases.
  
  
  
  Nearly 30% of 30-day readmissions to a children's hospital may be potentially preventable. Hospital and patient factors are associated with potential preventability and may provide targets for quality improvement efforts. Interviews contribute important information and should be considered when evaluating readmissions.
authors.affiliation: Division of General Pediatrics, Department of Medicine, and Department of Pediatrics, Harvard Medical School, Boston, Massachusetts; and sara.toomey@childrens.harvard.edu.
authors.forename: Sara L
authors.initials: SL
authors.lastname: Toomey
authors.affiliation: Division of General Pediatrics, Department of Medicine, and Robert Wood Johnson Foundation Clinical Scholars Program, Yale University School of Medicine, New Haven, Connecticut.
authors.forename: Alon
authors.initials: A
authors.lastname: Peltz
authors.affiliation: Division of General Pediatrics, Department of Medicine, and.
authors.forename: Samuel
authors.initials: S
authors.lastname: Loren
authors.affiliation: Division of General Pediatrics, Department of Medicine, and.
authors.forename: Michaela
authors.initials: M
authors.lastname: Tracy
authors.affiliation: Clinical Research Center, Boston Children's Hospital, Boston, Massachusetts;
authors.forename: Kathryn
authors.initials: K
authors.lastname: Williams
authors.affiliation: Division of General Pediatrics, Department of Medicine, and.
authors.forename: Linda
authors.initials: L
authors.lastname: Pengeroth
authors.affiliation: Division of General Pediatrics, Department of Medicine, and Department of Pediatrics, Harvard Medical School, Boston, Massachusetts; and.
authors.forename: Allison
authors.initials: A
authors.lastname: Ste Marie
authors.affiliation: Division of General Pediatrics, Department of Medicine, and.
authors.forename: Sarah
authors.initials: S
authors.lastname: Onorato
authors.affiliation: Division of General Pediatrics, Department of Medicine, and Department of Pediatrics, Harvard Medical School, Boston, Massachusetts; and.
authors.forename: Mark A
authors.initials: MA
authors.lastname: Schuster
mesh_terms: D000293:Adolescent; D001900:Boston; D002648:Child; D002675:Child, Preschool; D003430:Cross-Sectional Studies; D005260:Female; D006776:Hospitals, Pediatric / Q000592:standards / Q000706:statistics & numerical data*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007407:Interviews as Topic; D008297:Male; D015999:Multivariate Analysis; D010359:Patient Readmission / Q000706:statistics & numerical data*; D058996:Quality Improvement; D019984:Quality Indicators, Health Care / Q000706:statistics & numerical data*; D012189:Retrospective Studies