A crowded waiting room can stress out both front-desk staff and clinicians. And barring obviously emergent presentations, human error can occur when deciding which patient needs attention first. An article just published in Fortune magazine introduces a new machine learning-powered triage system that was created to streamline and assure appropriate triage—with a focus on urgent care. The new system, developed by a company called Epic, analyzes a patient’s electronic medical records and their current vital signs to predict the level and immediacy of care needed, which can inform decisions of whether to treat a patient on site or refer to a higher-acuity setting. The next step in its evaluation will be a pilot program at Stanford University. The questions of cost and potential return-on-investment lie down the road. However,  it’s likely the efficiencies would be greater in hospital-based urgent care, where the cost would be absorbed by fees associated with transferring patients to other settings in-house.

Can Artificial Intelligence Provide Real Value in Triaging Urgent Care Patients?
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