Overview/Description:

In the first two webinars of this series, we described the fundamental challenges faced by infusion centers across the country, outlined the basic operational factors causing these inefficiencies, and began a deep dive into how leading infusion centers are resolving those inefficiencies.

In this on-demand webinar, we will cover in-depth how data from the EHR can be used by infusion center staff to anticipate and prepare for how each day will unfold. We will also describe how several leading infusion centers are optimizing their scheduling using machine learning and “schedule grooming” techniques to accommodate more patient volume without adding chairs or overloading nurses.

 

Learning Objectives:

After this session, the participants will be able to:

  • Describe how using current data about the day’s schedule to predict how today will run can improve nurse and patient experience as the day unfolds.
  • Explain how “schedule grooming” (for schedulers, nurses, or individual patients) can help shape the future and level-load each day.
  • Describe how machine learning can continuously analyze the “gap” between predicted and actual performance, allowing templates for future days to be tweaked to ensure continuous improvement in operational performance. 

 

   Presented by:

Mohan_LinkedIn_photo
 
   Mohan Giridharadas  
  Founder and CEO
LeanTaaS
 

 
As the founder and CEO of LeanTaaS, Mohan has worked closely with dozens of leading healthcare institutions including Stanford Health Care, UCHealth, UCSF, New-York Presbyterian and more. Mohan holds a B.Tech from IIT Bombay, an MS in Computer Science from Georgia Institute of Technology, and an MBA from Stanford Graduate School of Business. He is on the Faculty of Continuing Education at Stanford University and UC Berkeley Haas School of Business. Mohan has been named by Becker's Hospital Review as one of the top entrepreneurs innovating in Healthcare.

 

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