Oculys Webinar: “How Long Will I Wait To Be Seen?” Confidently Forecast ED Wait Times With Oculys prEDict - Featuring: Windsor Regional Hospital

This webinar will provide an overview of how Windsor Regional Hospital (WRH) is using predictive analytics to manage public expectations and improve patient satisfaction

About the Webinar

With growing demand for Emergency Department services, managing capacity and patient expectations have become a serious headache for both hospitals and the community. Continuous calls inquiring about ED wait times, ongoing questions directed to volunteers and staff inside the department, and misaligned patient expectations all contribute to irritable visits which negatively impact staff morale and the greater community.

To address this pain, the Windsor Regional Hospital implemented an easy-to-access predictive ED wait time clock called Oculys prEDict that provides transparency between the hospital and the underlying communities they serve. 

Unlike ED wait time clocks which rely upon averages, prEDict uses a proprietary algorithm and predictive analytics to ensure highly accurate wait times can be displayed both in hospital waiting areas and on a public-facing website. 

With the 90%+ accuracy of prEDict, community residents can view wait times, volumes & historic trends which supports strong communication with the community by helping the public manage expectations leading to improved experiences and patient satisfaction. 

You will learn how WRH manages public expectations through:

  • Increasing transparency between community and care staff with easy-to-access ED wait time clock (prEDict) located on hospital website and waiting room

  • Giving the community a sense of knowing. Knowing when they'll be seen, how many people are ahead of them, how long the wait time is, what is the best/worst time to visit the ED, etc.

  • 90% accuracy ensuring the community can expect accurate wait times and care staff can deliver on those promises



  • Improving staff productivity by reducing number of calls inquiring about wait times

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