 How many patients in queue for x-ray, casting, in lobby ◦ Predict demand per quarter-hour, per building  Order in EHR from last appointment  Whether the last appointment was a surgery  With logic per surgeon  Was cast applied at last visit  Using predictive analytics to determine which patients are likely to no-show ◦ Give those patients special encouragement to show/cancel ◦ Automated daily e-mails recommending next day add-ons by provider (linked to potential no-shows pts)
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