Shira Winter, PhD, RN, FNP-BC
Postdoctoral Fellow
Stanford University School of Medicine, United States
Disclosure information not submitted.
Jonathan Ling, MS
Graduate Student
Stanford University, United States
Disclosure information not submitted.
Timothy Cornell, MD
Chambers-Okamura Endowed Professor of Pediatric Critical Care Medicine
Stanford University - Lucille Packard Children's Hosptal Stanford, United States
Disclosure information not submitted.
David Scheinker, PhD
Clinical Associate Professor
Stanford University School of Medicine, United States
Disclosure information not submitted.
Title: Factors Associated with Prolonged Discharge Delays in a Pediatric ICU
INTRODUCTION/HYPOTHESIS: Discharge delays from pediatric intensive care units (PICUs) are costly and may have adverse impacts on patient outcomes. We investigated the association between discharge delays from the PICU and environmental and operational factors: time of day, day of the week, unit turnover (% new patients in 12 hour period before discharge), nurse staffing ratios, and receiving unit occupancy.
Methods: Data collected from Apr 2018 - Dec 2019 at a 36 bed PICU in a single center were analyzed retrospectively. A discharge was classified as delayed if a patient left the PICU more than 12 hours after they had been deemed medically ready for discharge. We used multivariate logistic regression to calculate the odds of prolonged discharge delay adjusted for the following factors: occupancy of the receiving unit, hospital, and PICU, patient age, gender, weight, race, surgical status, primary diagnosis, number of diagnoses recorded, and number of PICU procedures.
Results: The study included 3,854 patient discharges of which 407 (10.6%) were delayed. The odds of discharge delay were highest at noon (OR with 95% CI: 1.26 [1.08, 1.48]) and on the weekdays (vs weekends: 1.32 [1.04, 1.69]). Higher unit turnover increased the odds of delay (at 10% turnover: 0.91 [0.86, 0.97] vs 30%: 1.50 [1.13, 1.99]) and higher nurse-to-patient ratios increased the odds of discharge delay at ratios at or above 1.50 patients per nurse (1.69 [1.40, 2.03]). Higher receiving unit occupancy above 90% increased odds of discharge delay (at 85%: 0.74 [0.68, 0.80]; vs 95%: 3.60 [2.99, 4.35]).
Conclusions: Prolonged discharge delays in the PICU were significantly associated with the time of day, day of the week, PICU turnover, nurse-to-patient ratios, and receiving unit occupancy. These findings help identify operational interventions to reduce the odds of discharge delays. For instance, the rapid increase in discharge delays observed when receiving unit occupancy exceeds 90% suggests a bottleneck where small interventions may yield large improvements. Conversely, the effects of nurse staffing on discharge delay appear to saturate at 1.5 patients per nurse, which leaves little room for intervention due to already high nurse-to-patient ratios in the PICU. A thorough understanding of discharge delays should include these environmental factors.