Validation of a modified bedside Pediatric Early Warning System score for detection of clinical deterioration in hospitalized pediatric oncology patients: A prospective cohort study

Oncological pediatric early warning score: a dedicated tool to predict patient's clinical deterioration and need for pediatric intensive care treatment

Pediatric oncohematological patients frequently require PICU admission during their clinical history. The O-PEWS is a specific score developed to predict the need for PICU admission of oncohematological children. This study aimed at i) describing the trend of the O-PEWS in a cohort of patients hospitalized in the Pediatric Oncohematology ward and transferred to the PICU of Padua University Hospital, measured at different time-points in the 24 hours before PICU admission and to evaluate its association with mortality and presence of organ failure; ii) investigating the association between the recorded O-PEWS, and PIM3, number of organ failure and the need for ventilation, dialysis and inotropes.

This retrospective single-center study enrolled oncohematological children admitted to the PICU between 2017 and 2021. The O-PEWS, ranging between 0 and 15, was calculated on the available medical records and the TIPNet-Network database at 24 (T-24), 12 (T-12), 6 (T-6) and 0 (T0) hours before PICU admission.

RESULTS: 101 PICU admissions, related to 80 children, were registered. During the 24 hours prior to PICU admission, the O-PEWS progressively increased in all the patients. At T-24 the median O-PEWS was 3 (IQR 1-5), increasing to a median value of 6 (IQR 4-8) at T0. The O-PEWS was positively associated with mortality, organ failure and the need for ventilation at all the analyzed time-points and with the need for dialysis at T-6.

The O-PEWS appears as a useful tool for predicting early clinical deterioration in oncohematological patients and for anticipating the initiation of life-support treatments.

Improving Pediatric Intensive Care Unit Discharge Timeliness of Infants with Bronchiolitis Using Clinical Decision Support

BACKGROUND

Identifying children ready for transfer out of the pediatric intensive care unit (PICU) is an area that may benefit from clinical decision support (CDS). We previously implemented a quality improvement (QI) initiative to accelerate the transfer evaluation of non-medically complex PICU patients with viral bronchiolitis receiving floor-appropriate respiratory support.

OBJECTIVES

Design a CDS tool adaptation of this QI initiative to further accelerate transfer evaluation of appropriate patients.

METHODS

The original initiative focused on identifying for transfer evaluation otherwise healthy children admitted to the PICU with bronchiolitis who had been receiving floor-appropriate levels of respiratory support for at least 6 hours. However, this initiative required that clinicians manually track the respiratory support of qualifying patients. We designed an electronic health record (EHR)-based CDS tool to automate identification of transfer-ready candidates. The tool parses EHR data to identify children meeting prior QI initiative criteria and alerts clinicians to assess transfer readiness once a child has been receiving floor-appropriate respiratory support for 6 hours. We compared time from reaching floor-appropriate support to placement of the transfer order ("time-to-transfer"), PICU length of stay (LOS), and hospital LOS between patients admitted prior to our QI initiative (December 1, 2018-October 19, 2019, "pre-QI phase"), during the initiative but before CDS tool implementation (October 20, 2019-February 7, 2022, "QI phase"), and after CDS implementation (February 8-November 11, 2022, "CDS phase").

RESULTS

CDS-phase patients (n = 131) had a shorter median time-to-transfer of 5.23 (interquartile range [IQR], 3.38-10.0) hours compared with QI-phase patients (n = 304) at 5.93 (IQR, 4.23-12.2) hours (p = 0.04). PICU and hospital LOS values decreased from the pre-QI (n = 150) to QI phase. Though LOS reductions were sustained during the CDS phase, further reductions from QI to CDS phase were not statistically significant.

CONCLUSION

An EHR-based CDS adaptation of a prior QI initiative facilitated timely identification of PICU patients with bronchiolitis ready for transfer evaluation. Such tools might allow PICU clinicians to focus on other high-acuity tasks while accelerating transfer evaluation of appropriate patients.