Factors associated with 30-day unplanned pediatric surgical readmission

Am J Surg. 2016 Sep;212(3):426-32. doi: 10.1016/j.amjsurg.2015.12.012. Epub 2016 Feb 26.

Abstract

Background: Unplanned readmissions are costly to family satisfaction and negatively associated with quality of care. We hypothesized that patient, operative, and hospital factors would be associated with pediatric readmission.

Methods: All patients with an inpatient operation from 10/1/2008 to 7/28/2014 at a freestanding children's hospital were included. A retrospective cohort study using multivariable forward stepwise logistic regression determined factors associated with unplanned readmission within 30 days of discharge.

Results: Among 20,785 patients with an operation there were 26,978 encounters and 3,092 readmissions (11.5%). Thirteen of 33 candidate variables considered in the stepwise regression were significantly associated with readmission. Patients with an emergency department visit within 365 days of operation, American Society of Anesthesiologists class 4 or greater, Hispanic ethnicity and late-day or holiday/weekend discharges were more likely to have an unplanned readmission (odds ratio [OR] = 1.96; 95% confidence interval [CI] = 1.76 to 2.19, OR = 2.00; 95% CI = 1.58 to 2.53, OR = 1.16; 95% CI = 1.04 to 1.29, OR = 2.27; 95% CI = 1.55 to 3.63. respectively).

Conclusions: Patient and hospital factors may be associated with readmission. Day and time of discharge represent variability of care and are important targets for hospital initiatives to decrease unplanned readmission.

Keywords: Pediatric; Readmission; Surgical discharge.

MeSH terms

  • Adolescent
  • Child
  • Child, Preschool
  • Female
  • Follow-Up Studies
  • Hospitals, Pediatric / statistics & numerical data*
  • Humans
  • Incidence
  • Infant
  • Infant, Newborn
  • Length of Stay / trends
  • Male
  • Odds Ratio
  • Patient Readmission / statistics & numerical data*
  • Postoperative Complications / epidemiology*
  • Retrospective Studies
  • Risk Factors
  • Time Factors
  • Washington / epidemiology