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Using workload capacity indicators to evaluate rule-based early warning tools and their relationship to escalation

Anton H van der Vegt1, Victoria Campbell2,3,4, Imogen Mitchell5,6

  • 1Centre for Health Services Research, The University of Queensland, Brisbane, QLD, Australia.

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Summary

This study compared early warning tools (EWTs) for patient deterioration, finding NEWS2 had superior accuracy but Q-ADDS offered better workload capacity. Healthcare organizations should consider both metrics when selecting EWTs.

Keywords:
Clinical deterioration predictiondigital healthearly warning toolhealth informatics

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Area of Science:

  • Medical Informatics
  • Clinical Decision Support
  • Patient Safety

Background:

  • Early Warning Tools (EWTs) are crucial for detecting patient deterioration.
  • Evaluating EWTs traditionally focuses on accuracy metrics like AUROC and PPV.
  • Hospital workload capacity is an important, yet often overlooked, factor in EWT performance.

Purpose of the Study:

  • To compare the prediction accuracy of four rule-based EWTs using a large electronic medical record (EMR) dataset.
  • To re-evaluate EWT performance using a novel hospital workload capacity evaluation method.
  • To inform healthcare organizations on selecting appropriate EWTs and alert thresholds.

Main Methods:

  • Retrospective analysis of adult inpatient admissions across 11 Australian hospitals.
  • Evaluation of four EWTs: National Early Warning Score (NEWS), Between the Flags (BTF), Modified Early Warning Score (MEWS), and Queensland Adult Deterioration Detection Systems (Q-ADDS).
  • EWTs assessed using Area Under the Receiver Operating Curve (AUROC), sensitivity, positive predictive value (PPV), and a novel clinician workload capacity analysis.

Main Results:

  • NEWS2 demonstrated superior AUROC compared to Q-ADDS, MEWS, and BTF.
  • Q-ADDS exhibited superior PPV at each alert threshold.
  • Q-ADDS and MEWS operated at the lowest alert burden, indicating better workload capacity.

Conclusions:

  • A precision-recall workload capacity analysis visually displays EWT operational characteristics.
  • Healthcare organizations should consider clinician workload capacity alongside traditional accuracy metrics when selecting EWTs.
  • This approach aids in setting effective EWT alert thresholds for improved patient care and resource management.