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The Vitals Risk Index—Retrospective Performance Analysis of an Automated and Objective Pediatric Early Warning System

Title: The Vitals Risk Index—Retrospective Performance Analysis of an Automated and Objective Pediatric Early Warning System
Authors: Gorham, Tyler J.; Rust, Steve; Rust, Laura; Kuehn, Stacy; Yang, Jing; Lin, James Shuhan; Hoffman, Jeffrey; Huang, Yungui; Lin, Simon; McClead, Richard; Brilli, Richard; Bode, Ryan; Maa, Tensing
Source: Pediatric Quality & Safety ; volume 5, issue 2, page e271 ; ISSN 2472-0054
Publisher Information: Ovid Technologies (Wolters Kluwer Health)
Publication Year: 2020
Description: Introduction: Pediatric in-hospital cardiac arrests and emergent transfers to the pediatric intensive care unit (ICU) represent a serious patient safety concern with associated increased morbidity and mortality. Some institutions have turned to the electronic health record and predictive analytics in search of earlier and more accurate detection of patients at risk for decompensation. Methods: Objective electronic health record data from 2011 to 2017 was utilized to develop an automated early warning system score aimed at identifying hospitalized children at risk of clinical deterioration. Five vital sign measurements and supplemental oxygen requirement data were used to build the Vitals Risk Index (VRI) model, using multivariate logistic regression. We compared the VRI to the hospital’s existing early warning system, an adaptation of Monaghan’s Pediatric Early Warning Score system (PEWS). The patient population included hospitalized children 18 years of age and younger while being cared for outside of the ICU. This dataset included 158 case hospitalizations (102 emergent transfers to the ICU and 56 “code blue” events) and 135,597 control hospitalizations. Results: When identifying deteriorating patients 2 hours before an event, there was no significant difference between Pediatric Early Warning Score and VRI’s areas under the receiver operating characteristic curve at false-positive rates ≤ 10% (pAUC 10 of 0.065 and 0.064, respectively; P = 0.74), a threshold chosen to compare the 2 approaches under clinically tolerable false-positive rates. Conclusions: The VRI represents an objective, simple, and automated predictive analytics tool for identifying hospitalized pediatric patients at risk of deteriorating outside of the ICU setting.
Document Type: article in journal/newspaper
Language: English
DOI: 10.1097/pq9.0000000000000271
Availability: https://doi.org/10.1097/pq9.0000000000000271; https://journals.lww.com/10.1097/pq9.0000000000000271
Rights: http://creativecommons.org/licenses/by-nc-nd/4.0/
Accession Number: edsbas.5CD0246B
Database: BASE