Antimicrobial treatment imprecision: an outcome-based model to close the data-to-action loop.

Journal: The Lancet. Infectious diseases
Published Date:

Abstract

Health-care systems, food supply chains, and society in general are threatened by the inexorable rise of antimicrobial resistance. This threat is driven by many factors, one of which is inappropriate antimicrobial treatment. The ability of policy makers and leaders in health care, public health, regulatory agencies, and research and development to deliver frameworks for appropriate, sustainable antimicrobial treatment is hampered by a scarcity of tangible outcome-based measures of the damage it causes. In this Personal View, a mathematically grounded, outcome-based measure of antimicrobial treatment appropriateness, called imprecision, is proposed. We outline a framework for policy makers and health-care leaders to use this metric to deliver more effective antimicrobial stewardship interventions to future patient pathways. This will be achieved using learning antimicrobial systems built on public and practitioner engagement; solid implementation science; advances in artificial intelligence; and changes to regulation, research, and development. The outcomes of this framework would be more ecologically and organisationally sustainable patterns of antimicrobial development, regulation, and prescribing. We discuss practical, ethical, and regulatory considerations involved in the delivery of novel antimicrobial drug development, and policy and patient pathways built on artificial intelligence-augmented measures of antimicrobial treatment imprecision.

Authors

  • Alex Howard
    Department of Antimicrobial Pharmacodynamics and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK; Department of Infection and Immunity, Liverpool Clinical Laboratories, Liverpool University Hospitals NHS Foundation Trust, Royal Liverpool Site, Liverpool, UK. Electronic address: alexander.howard@liverpool.ac.uk.
  • Nada Reza
    Department of Antimicrobial Pharmacodynamics and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.
  • Stephen Aston
    Department of Antimicrobial Pharmacodynamics and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.
  • Beth Woods
    Centre for Health Economics, University of York, Heslington, York, UK.
  • Alessandro Gerada
    Department of Antimicrobial Pharmacodynamics and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK; Department of Infection and Immunity, Liverpool Clinical Laboratories, Liverpool University Hospitals NHS Foundation Trust, Royal Liverpool Site, Liverpool, UK.
  • Iain Buchan
    Centre for Health Informatics, Institute of Population Health, University of Manchester, UK.
  • William Hope
    Department of Antimicrobial Pharmacodynamics and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK; Department of Infection and Immunity, Liverpool Clinical Laboratories, Liverpool University Hospitals NHS Foundation Trust, Royal Liverpool Site, Liverpool, UK.
  • Anne-Grete Märtson
    Department of Antimicrobial Pharmacodynamics and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.