Health economic simulation modeling of an AI-enabled clinical decision support system for coronary revascularization

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The study evaluated an AI-driven decision support tool for coronary revascularization using data from 25,942 patients in Alberta, Canada.
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AI predictions influenced treatment decisions, shifting 72.4% of actual decisions to more economically optimized options.
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The average cost savings per patient were $22,960, with a QALY gain of up to $22,439 at a willingness-to-pay of $50,000 per QALY.
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Even with limited AI adoption, 53.2% of decisions shifted, resulting in a QALY gain of up to $32,214 per patient.
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The findings suggest AI can enhance economic value in healthcare by reducing costs and improving patient outcomes.

Npj Digital Medicine

by Tom Mullie, Arjun Puri, Emma Bogner, Bryan Har, Colm J. Murphy, Robert C. Welsh, Benjamin Tyrrell, Christopher L. F. Sun, Joon Lee
February 16, 2026

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