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:
Waiting room wait times
As mentioned in a recent post, patients do not like to sit around waiting for the appointment to start. You can, of course, track wait times at various other points of the process, but nothing annoys patients as much as sitting in the waiting room. At least with other parts of the appointment, the process has started. If the patient is on deck, at least he or she has moved on from the waiting room and is in the treatment process. If you are in the waiting room, you might as well be sitting in your living room plowing through the show on your DVR.
Here, set a goal or a threshold. Say, 10 minutes and look at the averages for each day. Glance at the report –which should only display the days over the threshold or highlight those days—and then understand why those days ran over. Maybe there were some extenuating circumstances like a challenging patient or the doctor having to deal with a situation during the work day. If you see the numbers continuing to run above your threshold, understand exactly what is causing the delays – disorganization, your system, etc.—and fix it.
Clinician times
During the work day, it is difficult to evaluate the performance of your team. The management of the practice – doctor, manager, clinical supervisor—are usually busy focusing on patient care and addressing problems that come up during the day. Queuing can give you a tool to help you to better understand what is going on with the clinical side of the operation. If a clinician is struggling with a particular type of appointment or patient, this information can help you identify a problem area and work with the clinician on solving the problem. Over time, you may find that most people cluster into a certain area while others pop out and require further attention.
Here’s a real world example of using this data: in one of our practices in Texas, we examined the time at a clinician’s chair over a period of months. On a consistent basis, one clinician spent an average of 8 minutes more than everyone else per appointment with a patient in the chair. Like a car tapping the brakes in heavy traffic, that slows down the entire operation. Since the report only generated exceptions instead of massive amounts of data, we quickly found this outlier and looked deeper into the situation. The clinical supervisor took time to more closely observe this person and see what might be causing these weak numbers. As it turned out, her treatment was excellent, but this person was extremely social. Almost every patient visit turned into a social occasion to talk about the last 6 weeks. Very nice, but not terribly efficient on a 125 patient day. To maximize her skills, she was transitioned into more of a marketing role and as I understand, she continues to thrive in that role today.
Appointment times/schedules
On a somewhat broader level, you can take a look at how long each appointment takes. Here’s one way to use it. Let’s say your long appointments are scheduled for 40 minutes, but when you add up the time spent by patients in treatment for a long appointment*, the average consistently comes to 45 minutes. Here, you have a couple of decisions to make. First, you need to determine whether or not this is a problem for your practice. Maybe your treatment style and your preferred systems result in a 45 minute long appointment. In that case, you simple need to make accommodations in your schedule for a 45 minute long versus a 40 minute one.
If you decide that 45 minutes is too long, then you need to look deeper into the numbers. Pick out a couple of outliers among individual long appointments (like a 56 minute long appointment) and try to determine where things may be going off the rails. If that doesn’t reveal anything, take the time to look at a few of that appointment type in real time to determine exactly what is going on.
*Like any other statistic, please do not be misled by the results from a small sample size. Performance for a week or even a month may represent too small of a group of patients (even in a large practice) to accurately know how things are going in the practice. A couple of herculean or dawdling days can throw off averages and lead you to believe there’s a problem when there isn’t and vice versa. I find that a 90 day moving average gives you the best feel for actual performance.
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