Part 3 in a 3-part Series on Stable Discharge Rates.  

Last time, we talked about how you can predict your future census. Today, we’re going to talk about some of the ways you can use that data to help manage your practice.  

Let’s say you happen to have more than a few providers working with longer (Length of Stay) LOS, and when you look at the predicted census for the next day, it looks like the census is going to balloon.   

This would mean overloading your providers and jeopardizing patient care. You can now preemptively activate another provider to bring in extra help for the next day. Instead of scrambling first thing in the morning when people may not be available, you can get it set up the prior day.  

In addition, you can get people the extra resources they need from case management and other allied health professionals to maximize their ability to discharge. You can leverage your new predictive analytics to help the hospital manage flow and help maximize the chances of keeping beds open – facilitating throughput from the ED (so fewer patients are boarding) and ensuring that there are beds available, so surgeries don’t need to be cancelled.  

Or maybe you can predict that census is going to be very light tomorrow. You could give people time off and save labor costs by not bringing in per diems. You could even use it as an opportunity for a meeting or a lunch when everyone should be more able to attend. A relaxed day for everyone can be great for morale and help with burnout. 

Or, if you really want to be clever, you can adjust how you schedule. Instead of just picking a random assortment of providers to work on any given day, you can make sure that you have a mix of high LOS and low LOS docs to make sure that census doesn’t get too out of control. This can help smooth out the variability in the census which is good for everyone for planning purposes. 

You can even provide feedback to your providers regarding their LOS. Not every short LOS is good, and not every long LOS is bad. But people who are outliers from the mean of the group are potential opportunities for education and behavior change when needed. It may be difficult for people to change the way that they practice, but over time perhaps they can – now that they know it’s being measured and are motivated to change.    

Once you have the data, there are lots of ways to use it to effectively manage your program. Maybe it’s time to start collecting that data.

What’s next?  

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