Introduction: We report a pathfinder study of AI/knowledge engineering methods to rapidly formalise COVID-19 guidelines into an executable model of decision making and care pathways. The knowledge source for the study was material published by BMJ Best Practice in March 2020.
Methods: The PROforma guideline modelling language and OpenClinical.net authoring and publishing platform were used to create a data model for care of COVID-19 patients together with executable models of rules, decisions and plans that interpret patient data and give personalised care advice.
Results: PROforma and OpenClinical.net proved to be an effective combination for rapidly creating the COVID-19 model; the Pathfinder 1 demonstrator is available for assessment at https://www.openclinical.net/index.php?id=746.
Conclusions: This is believed to be the first use of AI/knowledge engineering methods for disseminating best-practice in COVID-19 care. It demonstrates a novel and promising approach to the rapid translation of clinical guidelines into point of care services, and a foundation for rapid learning systems in many areas of healthcare.
Keywords: COVID‐19; artificial intelligence; rapid learning systems.
© 2020 The Authors. Learning Health Systems published by Wiley Periodicals LLC on behalf of the University of Michigan.