PLoS ONE (Jan 2020)

Evaluation of a digital triage platform in Uganda: A quality improvement initiative to reduce the time to antibiotic administration.

  • Victor Lee,
  • Dustin Dunsmuir,
  • Stephen Businge,
  • Robert Tumusiime,
  • James Karugaba,
  • Matthew O Wiens,
  • Matthias Görges,
  • Niranjan Kissoon,
  • Sam Orach,
  • Ronald Kasyaba,
  • J Mark Ansermino

DOI
https://doi.org/10.1371/journal.pone.0240092
Journal volume & issue
Vol. 15, no. 10
p. e0240092

Abstract

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BackgroundSepsis is the leading cause of death in children under five in low- and middle-income countries. The rapid identification of the sickest children and timely antibiotic administration may improve outcomes. We developed and implemented a digital triage platform to rapidly identify critically ill children to facilitate timely intravenous antibiotic administration.ObjectiveThis quality improvement initiative sought to reduce the time to antibiotic administration at a dedicated children's hospital outpatient department in Mbarara, Uganda.Intervention and study designThe digital platform consisted of a mobile application that collects clinical signs, symptoms, and vital signs to prioritize children through a combination of emergency triggers and predictive risk algorithms. A computer-based dashboard enabled the prioritization of children by displaying an overview of all children and their triage categories. We evaluated the impact of the digital triage platform over an 11-week pre-implementation phase and an 11-week post-implementation phase. The time from the end of triage to antibiotic administration was compared to evaluate the quality improvement initiative.ResultsThere was a difference of -11 minutes (95% CI, -16.0 to -6.0; p ConclusionA data-driven patient prioritization and continuous feedback for healthcare workers enabled by a digital triage platform led to expedited antibiotic therapy for critically ill children with sepsis. This platform may have a more significant impact in facilities without existing triage processes and prioritization of treatments, as is commonly encountered in low resource settings.