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Smart Triage + QI: A digital triaging platform to improve quality of care for critically ill children Kissoon, Niranjan; Kasyaba, Ronald; Kenya-Mugisha, Nathan; Ansermino, Mark; Opar, Bernard; Dumont, Guy; Wiens, Matthew; Komugisha, Clare; Agaba, Collins; Mwaka, Savio; Pillay, Yashodani
Description
Dataset Description: This dataset contains materials from a parent study within the Smart Triage program of research. Materials include the parent study protocol and associated documents. See the Metadata section below for links to related publications and datasets.
Background: Pediatric sepsis remains a leading cause of under-five mortality in low- and middle-income countries (LMICs), where delayed recognition and treatment contribute to high fatality rates. While early intervention with antibiotics and fluids improves outcomes, timely care depends on effective triage—yet many facilities lack standardized, validated tools suited to their context. Existing triage systems like WHO’s ETAT are widely used but face limitations in adaptability and evaluation due to inconsistent data and resource constraints. Quality of care—timely, safe, and efficient services—remains suboptimal in many LMICs, hindered by nonspecific clinical presentations, staffing shortages, and systemic barriers. To address these gaps, we developed Smart Triage, a digital triage platform incorporating predictive modeling, vital sign measurement, and treatment tracking to streamline pediatric sepsis management. Feasibility studies show it expedites treatment and improves clinician satisfaction. We are now expanding Smart Triage + QI to four sites in Uganda to enhance sepsis care through evidence-based quality improvement and optimize resource use for sustainable health system strengthening.
Methods: This is a pre- (Phase I) and post- (Phase II) evaluation of Smart Triage + QI at 4 Ugandan hospitals.
Phase I: Collect data on pre-selected clinical predictors and outcomes. This data provides baseline information to evaluate the effectiveness of the quality improvement system and potential target areas.
Phase II: Collect data to evaluate the effectiveness of Smart Triage + QI based on the primary and secondary outcomes. This period is a component of the quality improvement program with the goal of optimizing care of children with severe infections/suspected sepsis.
Ethics Declaration: This study was approved by the Makerere University School of Public Health Institutional Review Board in Uganda (SPH-2021-41) and the Uganda National Institute of Science and Technology (HS1745ES) .
Associated datasets:
Smart Triage: Clinical Data - QI
NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days.
Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at sepsiscolab@bcchr.ca or visit our website.
Item Metadata
| Title |
Smart Triage + QI: A digital triaging platform to improve quality of care for critically ill children
|
| Creator | |
| Contributor | |
| Date Issued |
2025-07-28
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| Description |
Dataset Description: This dataset contains materials from a parent study within the Smart Triage program of research. Materials include the parent study protocol and associated documents. See the Metadata section below for links to related publications and datasets. Background: Pediatric sepsis remains a leading cause of under-five mortality in low- and middle-income countries (LMICs), where delayed recognition and treatment contribute to high fatality rates. While early intervention with antibiotics and fluids improves outcomes, timely care depends on effective triage—yet many facilities lack standardized, validated tools suited to their context. Existing triage systems like WHO’s ETAT are widely used but face limitations in adaptability and evaluation due to inconsistent data and resource constraints. Quality of care—timely, safe, and efficient services—remains suboptimal in many LMICs, hindered by nonspecific clinical presentations, staffing shortages, and systemic barriers. To address these gaps, we developed Smart Triage, a digital triage platform incorporating predictive modeling, vital sign measurement, and treatment tracking to streamline pediatric sepsis management. Feasibility studies show it expedites treatment and improves clinician satisfaction. We are now expanding Smart Triage + QI to four sites in Uganda to enhance sepsis care through evidence-based quality improvement and optimize resource use for sustainable health system strengthening. Methods: This is a pre- (Phase I) and post- (Phase II) evaluation of Smart Triage + QI at 4 Ugandan hospitals. Phase I: Collect data on pre-selected clinical predictors and outcomes. This data provides baseline information to evaluate the effectiveness of the quality improvement system and potential target areas. Phase II: Collect data to evaluate the effectiveness of Smart Triage + QI based on the primary and secondary outcomes. This period is a component of the quality improvement program with the goal of optimizing care of children with severe infections/suspected sepsis. Ethics Declaration: This study was approved by the Makerere University School of Public Health Institutional Review Board in Uganda (SPH-2021-41) and the Uganda National Institute of Science and Technology (HS1745ES) . Associated datasets: Smart Triage: Clinical Data - QI ; NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days. Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at sepsiscolab@bcchr.ca or visit our website. |
| Subject | |
| Type | |
| Language |
English
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| Date Available |
2025-07-16
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| Provider |
University of British Columbia Library
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| License |
CC BY-NC-SA 4.0
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| DOI |
10.14288/1.0449507
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| URI | |
| Publisher DOI | |
| Rights URI | |
| Aggregated Source Repository |
Dataverse
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License
CC BY-NC-SA 4.0