Appl Clin Inform 2018; 09(03): 576-587
DOI: 10.1055/s-0038-1667122
Research Article
Georg Thieme Verlag KG Stuttgart · New York

Design and Implementation of a Pediatric ICU Acuity Scoring Tool as Clinical Decision Support

Eric Shelov
Department of General Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
,
Naveen Muthu
Department of General Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
,
Heather Wolfe
Department of Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
,
Danielle Traynor
Department of Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
,
Nancy Craig
Department of Respiratory Therapy, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
,
Christopher Bonafide
Department of General Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
,
Vinay Nadkarni
Department of Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
,
Daniela Davis
Department of Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
,
Maya Dewan
Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States
Division of Critical Care Medicine, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, United States
› Author Affiliations
Further Information

Publication History

28 February 2018

05 June 2018

Publication Date:
01 August 2018 (online)

Abstract

Background and Objective Pediatric in-hospital cardiac arrest most commonly occurs in the pediatric intensive care unit (PICU) and is frequently preceded by early warning signs of clinical deterioration. In this study, we describe the implementation and evaluation of criteria to identify high-risk patients from a paper-based checklist into a clinical decision support (CDS) tool in the electronic health record (EHR).

Materials and Methods The validated paper-based tool was first adapted by PICU clinicians and clinical informaticians and then integrated into clinical workflow following best practices for CDS design. A vendor-based rule engine was utilized. Littenberg's assessment framework helped guide the overall evaluation. Preliminary testing took place in EHR development environments with more rigorous evaluation, testing, and feedback completed in the live production environment. To verify data quality of the CDS rule engine, a retrospective Structured Query Language (SQL) data query was also created. As a process metric, preparedness was measured in pre- and postimplementation surveys.

Results The system was deployed, evaluating approximately 340 unique patients monthly across 4 clinical teams. The verification against retrospective SQL of 15-minute intervals over a 30-day period revealed no missing triggered intervals and demonstrated 99.3% concordance of positive triggers. Preparedness showed improvements across multiple domains to our a priori goal of 90%.

Conclusion We describe the successful adaptation and implementation of a real-time CDS tool to identify PICU patients at risk of deterioration. Prospective multicenter evaluation of the tool's effectiveness on clinical outcomes is necessary before broader implementation can be recommended.

Protection of Human and Animal Subjects

This study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects, and was approved by the Institutional Review Board of CHOP with a waiver of consent.