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UBC

University of British Columbia
Country: Canada
Funder (10)
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851 Projects, page 1 of 171
  • Funder: WT Project Code: 215695
    Funder Contribution: 835,847 GBP

    We are proposing a new and innovative precision approach to the identification of severe infections and sepsis in children. This data-driven approach to diagnosis will overcome many of the limitations of current expert opinion-based triage guidelines. Smart technology has the potential to overcome the barrier of limited clinical expertise in the identification of the child at risk. This mobile health platform, with sensors and data-driven applications, will provide real-time individualised risk prediction to facilitate timely and effective targeted treatment at first contact, regardless of location. This low-cost technology will provide rapid triage in remote areas globally where specialists are not regularly available. We will trigger rapid, highly effective and low-cost interventions such as antibiotics, fluid, oxygen therapy and other special investigations to children determined to be most at risk of sepsis, based on data-driven prediction. Thus, these innovations will improve timely access to life-saving treatments for children in the poorest countries where deaths from infection and sepsis are common. Children in poor families or in populations marginalized by health and social inequities are especially vulnerable to infections. In these children, infection is a major contributor to disability and years of life lost and has a great economic and social cost. Sepsis is the leading cause of death and disability in children, every hour of delay in treatment is associated with greater organ damage and ultimately death. The challenges, especially in poor countries, are the delays in diagnosis and the inability to identify children in urgent need of treatment. To circumvent these challenges, we propose the implementation and evaluation of a trigger tool that will reduce the time to diagnosis and prompt the timely initiation of life-saving treatment. The key innovations are 1) a data-driven approach to rapid diagnosis of sepsis severity and 2) a low-cost digital tagging system to track the time to treatment. The tool will require minimal cost, clinical expertise and training or time to use. The tool will identify high risk children and reduce time to treatment. Our mobile platform (mobile device and dashboard) will create a low-cost, highly scalable solution for children with sepsis.

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  • Funder: NIH Project Code: 1R01DA033147-01
    Funder Contribution: 373,949 USD
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  • Funder: NIH Project Code: 5R01GM076990-10
    Funder Contribution: 240,592 USD
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  • Funder: NIH Project Code: 5R01AG012721-11
    Funder Contribution: 230,171 USD
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  • Funder: NIH Project Code: 5R01MH071893-03
    Funder Contribution: 618,557 USD
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