Karen Fryer

PROPER: Development of an Early Pediatric Intensive Care Unit Readmission Risk Prediction Tool

Objective: No risk prediction model is currently available to measure patient’s probability for readmission to the pediatric intensive care unit (PICU). This retrospective case–control study was designed to assess the applicability of an adult risk prediction score (Stability and Workload Index for Transfer [SWIFT]) and to create a pediatric version (PRediction Of PICU Early Readmissions [PROPER]). Design: Eighty-six unplanned early (<48 hours) PICU readmissions from January 07, 2007, to June 30, 2014, were compared with 170 random controls. Patient- and disease-specific data and PICU workload factors were compared across the 2 groups. Factors statistically significant on multivariate analysis were included in the creation of the risk prediction model. The SWIFT scores were calculated for cases and controls and compared for validation. Results: Readmitted patients were younger, weighed less, and were more likely to be admitted from the emergency department. There were no differences in gender, race, or admission Pediatric Index of Mortality scores. A higher proportion of patients in the readmission group had a Pediatric Cerebral Performance Category in the moderate to severe disability category. Cases and controls did not differ with respect to staff workload at discharge or discharge day of the week; there was a much higher proportion of patients on supplemental oxygen in the readmission group. Only 2 of 5 categories in the SWIFT model were significantly different, and although the median SWIFT score was significantly higher in the readmissions group, the model discriminated poorly between cases and controls (area under the curve: 0.613). A 7-category PROPER score was created based on a multiple logistic regression model. Sensitivity of this model (score ≥12) for the detection of readmission was 81% with a positive predictive value of 0.50. Conclusion: We have created a preliminary model for predicting patients at risk of early readmissions to the PICU from the hospital floor. The SWIFT score is not applicable for predicting the risk for pediatric population.

Overcoming Barriers to Delirium Screening in the Pediatric Intensive Care Unit

BACKGROUND Delirium is associated with poor outcomes in adults but is less extensively studied in children. OBJECTIVES To describe a quality improvement initiative to implement delirium assessment in a pediatric intensive care unit and to identify barriers to delirium screening completion. METHODS A survey identified perceived barriers to delirium assessment. Failure modes and effects analysis characterized factors likely to impede assessment. A randomized case‐control study evaluated factors affecting assessment by comparing patients always assessed with patients never assessed. RESULTS Delirium assessment was completed in 57% of opportunities over 1 year, with 2% positive screen results. Education improved screening completion by 20%. Barriers to assessment identified by survey (n = 25) included remembering to complete assessments, documentation outside workflow, and “busy patient.” Factors with high risk prediction numbers were lack of time and paper charting. Patients always assessed had more severe illness (median Pediatric Index of Mortality 2 score, 0.90 vs 0.36; P < .001), more developmental disabilities (moderate to severe pediatric cerebral performance category score, 54% vs 32%; P = .007), and admission during lower pediatric intensive care unit census (median [interquartile range], 10 [9‐12] vs 12 [10‐13]; P < .001) than did those never assessed (each group, n = 80). Patients receiving mechanical ventilation were less likely to be assessed (41.0% vs 51.2%, P < .001). CONCLUSIONS Successful implementation of pediatric delirium screening may be associated with early use of quality improvement tools to identify assessment barriers, comprehensive education, monitoring system with feedback, multidisciplinary team involvement, and incorporation into nursing workflow models.