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Appl Clin Inform. 2018 Jul;9(3):576-587. doi: 10.1055/s-0038-1667122. Epub 2018 Aug 1.

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

Author information

1
Department of General Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States.
2
Department of Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States.
3
Department of Respiratory Therapy, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States.
4
Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States.
5
Division of Critical Care Medicine, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, United States.

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.

PMID:
30068013
PMCID:
PMC6070387
DOI:
10.1055/s-0038-1667122
[Indexed for MEDLINE]
Free PMC Article

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