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Helping you predict the unpredictable. There's a new normal in radiology and scheduling matters more than ever. GE Healthcare helps your practice stay more efficient by predicting no-shows before they even happen with AI-driven Smart Scheduling.
If you are interested in receiving more information on Smart Scheduling click here to email us directly and we will contact you.
A virus changed everything we knew about scheduling.
Today, unused slots are more disruptive than ever.
You work hard to fill every slot, but some things you can’t control.
No show rates as high as 6.5% or higher are common.1
What if you could predict no-shows before they even happened?
Fully understanding how to best manage exam scheduling in an imaging department or practice is considerable given the wide range of factors contributing to patients missing appointments—creating equipment underutilization, idle staff, and delayed diagnosis. Smart Scheduling is designed to help manage these challenges by utilizing machine learning models leveraging a wide range of factors, both internal and external of the imaging practice, to change the paradigm of scheduling workflows to enable better patient access.
That’s what we call Smart Scheduling
Pinpoint the likelihood of appointment no-shows with advanced data and AI that examine internal and external data factors to deliver probabilities that can help you plan accordingly.
- No show tracking
Receive automated and aggregated alerts throughout the day.
A unique tailored machine learning model for each site.
Save time and effort and increase your conversion rates.
View your daily forecast and schedule history.
- Patient follow-up
Helps support probability driven decision making & actions.
Increase your predictability and have fewer disruptions.
Reduce no-shows by up to 70%2
- Automated data aggregation that helps predict a patient’s tendency to adhere to a particular exam appointment based on historical information and localized patterns up to five days in advance.
- Clear and intuitive dashboard, providing a probability score for each prediction, will allow the scheduler to make an informed decision when scheduling for the most appropriate exam slot.
- Customer Enablement engagements (where available) to drive change management, support setup for success, and help deliver outcomes that matter.
How Chattanooga gained $100,000 through patient no show reduction
- H.B. Harvey MD JD, C Lui MS, J. Ai BS, et al, Journal of the American College of Radiology, Vol14, Iss13, P1303-1309, "Predicting No-Shows in Radiology Using Regression Modeling of Data Available in Electronic Medical Record"
- Results based on single pilot site, results not typical and cannot be guaranteed. GE Healthcare makes no guarantees concerning the impact of the use of Smart Scheduling on customers' facilities