The 3 best queuing statistics

Queueing systems can be nice (see a more detailed description of those) and enable you to identify and unblock traffic jams during the work day.  But those systems also generate a tremendous amount of data and to not use that information to improve your practice would be a waste of another resource to enable you to simultaneously improve the quality of patient service and your bottom line.

When you track every patient’s movement at every step of the process during a patient day, you can imagine the amount of data available to you.  Please do not print and review daily detailed reports.  That will lead you to errors with anecodotal stories (this one time, on a patient day, we knocked out shorts in 8 minutes) and confusion from the excess of data.

And please do not make the mistake I made early in my history by generating tons of data and reports that no one in his or her right mind would spend time poring over.  Rather, compile the data (or have us compile the data) into useful pieces and focus on the exception to norms or threshholds exceeded.  

With that, here are 3 of the top pieces of data you can generate from your queuing system:

Queuing systems: the vitals

In the last post, I mentioned that I would go deeper into queuing systems in the next writing.  As mentioned earlier, a queuing system basically tracks each patient as they move from point to point during a visit to the office.  In addition to noting which patients are where in the office, you can also see how long the patient has been in that area.

At My Practice Engine, the primary experience we have had with queuing systems is building one from the ground up.  Our patient flow protocols were already in place and our IT team built queuing into our practice management system around those protocols.  

In sum, a queuing system, when used properly, can provide extremely valuable information.  The key phrase there is “when used properly” because if used improperly, it is a waste of hardware and software.  We had one manager simply go in at various times of the day and mark every patient in the office as checked out.  So, at a specific time of day, 15 people all left at once.  I hope they had someone to hold the door for the rush of folks.  

When used properly however, there are a number of ways to use one.  One extremely simple way is to note the time a patient arrived at the office and the time that person left.  Now, that isn’t the hardcore “queuing” or tracking that the term traditionally implies, but can give you useful information.  Here’s how: