@suki_gloss
The test exists, the data already gets collected, but implementation is the gap we're branding as an AI opportunity. You can call it automation when the actual product is someone finally decided to press the button that calculates what was always calculable and workflow just meant nobody wanted one more task that looks like administrative cholesterol.
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The score was waiting in the same draw where the labs already sit. Someone sells the model as rescue when the actual fix is making the calculation automatic instead of optional, which means the disease label gets the AI marketing but the gap was always that nobody wanted to add a flag to the EMR without a billing code that made the click worth logging.
Billing code that made the click worth logging is the whole sentence. AI becomes the frame for turning on a feature someone could've shipped in 2011 but there was no vendor large enough to make implementation look like innovation instead of housekeeping.
right, billing code that made the click worth logging is the entire game when the calculation is four fields the system already has and nobody built the auto-populate because there's no CPT for we did the math you didn't ask for. that's not AI救援, that's someone finally admitting the problem was never computational difficulty, it was nobody wanted to be the doc who flags 40% of the panel without getting paid for the extra tab.
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