Abstract
While artificial intelligence (AI) models have been developed to support coronary revascularization decision-making, health economic evaluation of such models has been rare. We conducted a retrospective health economic simulation modeling study using real-world data from 25,942 adult patients with obstructive coronary artery disease in Alberta, Canada to evaluate the economic value of an AI-enabled coronary revascularization decision support system. Clinicians deciding among medical therapy only, percutaneous coronary intervention, and coronary artery bypass grafting were simulated to be provided with AI predictions of 3- and 5-year major adverse cardiovascular events and all-cause mortality. At a willingness-to-pay of $50,000 per quality adjusted life year (QALY), as many as 72.4% of all actual treatment decisions shifted to a different health economically optimized treatment, resulting in an average cost saving of $22,960 and a QALY gain equivalent to up to $22,439 per patient. Even in a conservative scenario where clinicians’ AI adoption was assumed to be limited, 53.2% of the actual decisions shifted, resulting in an average QALY gain equivalent to up to $32,214 per patient. AI can potentially optimize the health system level economic value of treatment decisions in the form of reduced costs stemming from fewer future complications and improved patient outcomes.
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Data availability
The patient data used in this study contains real patient information and cannot be shared without permission from the data custodians, Alberta Health Services and Alberta Health. The simulated data may be shared upon reasonable request.
Code availability
Our source code for the health economic simulation may be shared upon reasonable request.
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Acknowledgements
This study was supported by a Project Grant from the Canadian Institutes of Health Research (PJT 178027) and an AICE-Concepts Grant from Alberta Innovates (212200473). The funders had no role in the design, execution, and analysis of this study.
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T.M. designed and executed the health economic simulation, produced all results, and wrote the manuscript. A.P. conceived of the study and provided feedback on the study design. E.B. prepared the patient data and Revaz AI predictions for the simulation model. B.H., C.J.M., R.W., and B.T. provided clinical input. C.L.F.S. and J.L. provided technical input related to AI and clinical decision support. J.L. provided feedback on the study design, wrote the manuscript, and oversaw the project. All authors critically revised the manuscript.
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A.P. and J.L. are co-founders and major shareholders of Symbiotic AI, Inc. B.H. and C.J.M. are minor shareholders of Symbiotic AI, Inc. All other authors have no conflict of interest to declare.
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Mullie, T., Puri, A., Bogner, E. et al. Health economic simulation modeling of an AI-enabled clinical decision support system for coronary revascularization. npj Digit. Med. (2026). https://doi.org/10.1038/s41746-026-02430-x
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DOI: https://doi.org/10.1038/s41746-026-02430-x
