PATH's Chief AI Officer Bilal Mateen reveals how a computer vision tool that digitizes lab documents cut processing time from 90 days to 1 day in Kenya, yet vendors keep pitching clinical decision support systems instead of these operational solutions that actually move the needle. After 30 years between FDA approval of breast cancer AI diagnostics and the first randomized control trial proving patient benefit, Mateen argues we've been measuring the wrong things: diagnostic accuracy instead of downstream health outcomes. His team's Kenya pilot with Penda Health demonstrated cash-releasing ROI through an LLM co-pilot that prevented inappropriate prescriptions, saving patients and insurers $50,000 in unnecessary antibiotics and steroids. What looks like lost revenue to the clinic represents system-wide healthcare savings.
Topics discussed:

The 90-day to 1-day document digitization transformation in Kenya
Research showing only 1 in 20 improved diagnostic tests benefit patients
Cash-releasing versus non-cash-releasing efficiency gains framework
The 30-year gap between FDA approval and proven patient outcomes
Why digital infrastructure investment beats diagnostic AI development
Hidden costs of scaling pilots across entire health systems
How inappropriate prescription prevention creates system-wide savings
Why operational AI beats clinical decision support in resource-constrained settings

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