SEDRILIMS Phase III: Generating Evidence for Adoption and Sustainability of Laboratory Information Systems

Year of award: 2025

Grantholders

  • Prof Paul Turner

    University of Oxford, United Kingdom

  • Mr Christopher Painter

    University of Oxford, United Kingdom

  • Dr Thomasena O'Byrne

    Liverpool School of Tropical Medicine, United Kingdom

  • Prof Aaron Aboderin

    Obafemi Awolowo University, Nigeria

  • Prof Nicholas Feasey

    University of St Andrews, United Kingdom

  • Mr Matthew King

    Arcta Solutions Limited, United Kingdom

  • Mr Mauro Tobin

    The Software for Health Foundation, United Kingdom

Project summary

Accessible high quality data is a fundamental requirement for responses to the global health antimicrobial resistance (AMR) threat. Health informatics is a neglected area in AMR research. Linkage of laboratory and patient data (e.g. infection syndrome, origin, outcome) is crucial for AMR burden estimation and intervention assessment. Software to support such linkage, and data management tools to improve utilisation, are limited. To support policy decisions around implementation of digital health solutions for tracking AMR burden / impacts and improving antibiotic use (AMU) / consumption (AMC) at patient, facility, and national levels, we propose a project with three interconnected work-packages; software / IT infrastructure development, implementation science-led clinical studies, and health economic modelling. The Wellcome-funded SEDRI-LIMS open-source microbiology laboratory information management system (LIMS) will be enhanced with additional analytics and interoperability capabilities. Processes around implementation of SEDRI-LIMS and subsequent clinical data utilisation will be characterised in healthcare facilities in Cambodia, Malawi, and Nigeria and facility-level clinical impacts collected via ACORN-lite AMR surveillance, prescribing / pharmacy data, and AMU point-prevalence surveys. We will develop budget impact models and return on investment projections for SEDRI-LIMS implementation and also model the economic impacts of improved AMR data utilisation and economic contribution of AMC to future AMR outcomes.