Patient Hours Divided by Chair Hours = the Wrong Utilization Metric Webinar transcript

MARIANNE BISKUP: Hello everyone. Welcome to today’s webinar, titled How To Measure Your Infusion. Centers Utilization. My name’s Marianne Biskup. I’m the Events Manager for LeanTaas, iQueue. I’m going to go over a few housekeeping points, and then we’ll begin today’s webinar. So you can text questions to 6308845493, or you can email us, that addresses is demo@leantaas.com. You’ll also notice– note that you’re all muted, but you can use the Q&A function, that icon is in the right-hand corner of your screen. You can also open a chat window, and communicate with us that way. Following the conclusion of this webinar later today, s we will be sending out a recording of this webinar, so look for that in your email. And now, I’d like to introduce our presenter Chris Koh, Infusion Product Manager. 

CHRIS KOH: Yes, Marianne. And thanks, everyone, for joining. I’ve been with LeanTaas since July 2017, on the iQueue for. Infusion Centers team. So before we get into specific details, let’s have a quick run-through of why you might care about utilization metrics at all. The most obvious reason that all of you are probably familiar with is patient access. You want to know if you’re treating as many patients that you can be treating given the resource constraints you face. Part of fully utilizing your center’s capacity is making sure that you’re not only filling your chairs in a way that doesn’t overload the nurses, but also filling them efficiently. 

For example, if you look at the diagram on the left, you’re filling your chairs, but it’s in a peaky triangular shape where there are many gaps in the schedule, and you’re going over your chair capacity in certain times of day usually in the middle of the day. As you can see in the white here, that’s where the gaps are. This in contrast to the diagram on the right where the gaps in the day are largely filled. And because you are utilizing your chair space efficiently, you aren’t going to have your center share capacity. This also smooths out the workload for your nurses and enables them to care for patients better. In both cases, you’re utilizing your center share capacity but in a very different way with likely different outcomes in each case. The next step– the next thing that we care about is exactly how to calculate the utilization metric that enables you to operate most efficiently. We’ll go over a detailed example in the next few slides. 

Let’s start with the parameters of a hypothetical infusion center, Acme Infusion Center. This center operates under the following basic conditions– there are 18 treatment chairs, the hours of operation are 8:00 AM to 6:00 PM, and there’s six nurses total with the following shifts. Two at 8:00 AM to 4:30, two from 8:30 AM to 5:00, and two from 9:30 to 6:00. There are no lunch breaks go then. The maximum number of patients a nurse can treat at one time is three, which is also known as the nurse ratio, which we’ll talk about a little bit. And the beginning nurse touch time is 30 minutes with negligible end touch time. There are likely some other factors that may come into play, which we’ll discuss later. But for now, let’s use this at the baseline. Calculating the utilization method for the center. Starting point is to take the number of chairs you have and multiply by the number of hours that your center is open. In this particular example, we have 18 chairs in the centers open for 10 hours, which would translate into a patient/hour capacity of 180 hours. 

However, a more accurate measure, in our opinion, is one that accounts for the ramp-up and ramp-down of your nursing shifts, at the beginning, and the end of the day. When you account for these ramps, what you’re left with is the trapezoid shape that you see here. Rather than fill all your chairs right from the opening hour through the end of the day, there is a slow increase in patients being served, being seated as your nurse can come in for their shifts at the beginning of the day. And at the end of the shift, you’ll want to account for the ramp-down as nurses and patients begin to leave for the day. This is probably something that you intuitively account for when managing your infusion operation, but because it can be tougher to properly calculate the exact time cost of the ramp-up and ramp-down, which we’ll get into next. It’s not always fully baked into utilization metrics. Down into how we might arrive at an adjusted utilization metric. 

You can see here that we’ve marked the parts of the rectangle that are not actually available to you as realistic capacity do the ramp up and ramp down at the beginning and end of the day. These are marked in yellow here. You can see that we’ve broken the day into half hour chunks. If you look at the period from 8:00 to 8:30, recall that Acme only has two nurses starting at 8:00, so you won’t be able to seat more than two patients a day. And assuming the 30-minute beginning touch time, the next time slot that the patient can realistically start is 8:30, so there are 16 chairs not being used in that half hour. And if you multiply that by 30 minutes, that’s eight hours total. We would deduct this from the total number of hours available. You can see that we ran a similar exercise over the course of the rest of the day until mid-morning. And the total ramp-up costs the left-hand side of this trapezoidal shape is 19 hours. That’s 8 plus 6 plus 4 plus 1. 

Note that this assumes that we’re filling the morning appointment slots with longer appointments and that patients are taking up the chairs for the entire period. Looking at the ramp-down at the end of the day, the considerations at that time are slightly different. One of the key variables that would be a nurse ratio that we talked about earlier or how many patients are comfortable with their nurse handling simultaneously at the end of the day. If you have a nurse ratio of three, for example, which we have assumed in this case, the ramp down starts when the first nurses leave at 4:30. Acme has four nurses remaining from 4:30 to 5:00, so the realistic capacity that you could handle at that time is 4 times 3 or 12. So you see this purple bar goes up to 12 chairs, and the yellow part is the part that accounts for the nurses leaving. Similarly, when the next wave nurse shifts end, there’s another step down where the two closing nurses can handle a total of 6 patients or 2 times 3. 

As with the ramp up, there are other things that you should– you can consider when it comes to the ramp down that might impact the speed of the ramp-down at the end of the day. But in this example, we’re losing 6 times 30 minutes or three hours the chair capacity from 4:30 to 5:00, and another 12 hours from 5:00 to 6:00 for a total of 15 hours. When we add the 15 hours at the end of the day to the 19 hours at the beginning of the day, we get a total of 34 hours for the sides of the trapezoid, which we deduct from the original rectangular estimate of 180 for an adjusted denominator of 146. If we assume that a center-treated patients were at 108 hours. In a particular day, we would get an adjusted utilization percentage of 74% or 108 divided by 146, compared to the 60% if we use 180 hours as the denominator. 

The takeaway from this difference in calculation of your utilization metric should hopefully be pretty clear at this point. If you plan for 180 patient hours, but realistically can only take 146 patient hours. Once you account for the size of the trapezoid, you will run out of chairs and overburden your nurses. Even if you plan for 150 to 260 patient hours in this case, that may be too many to keep your operation running smoothly. So it’s important to account for the size of the trapezoid to gauge your true capacity and allow for some buffer against that capacity if you can. We mentioned earlier that there are some other factors that might impact the slope and shape of the trapezoid. One other factor that might influence the shape is pharmacy availability both at the beginning and the end of your day. 

If only certain types of appointments can be done in the beginning or end of day because pharmacy is not available, then the shape of your chair utilization may vary slightly from a clean trapezoid. May have a slower ramp up right at the beginning with a steeper ramp-up after an hour as shown with the red lines in this example. CDC, the slower ramp from 8:00 to 9:00, and then a steeper ramp from 9:00 to 10:00. The same holds true at the end of the day. Another factor that’s possible is that one or more is able to turn the chairs in the morning more than one time with some small gaps in the base of the trapezoid. For example, if a nurse has one 1-hour appointment at 8:00 o’clock, and another appointment at 9:15, there’s a small gap between 9:00 and 9:15. And that would cause the filling of the chairs in the morning to be slightly slower. We could also use empirical appointment data to interpolate what your average ramp up speed and ramp down speed is over time, rather than attempt to calculate a theoretical ramp-up speed. This can help smooth out the impact of outliers that may have occurred on any single day. 

You would also take into account any other factors that might also impact ramp-up that you might not necessarily think about ahead of time or anticipate. So we spend some time going over how to calculate an adjusted utilization metric to make sure that you’re coming up with a reasonable plan for the number of patient hours you can fit into your center on any given day. A good rule of thumb is at the edges of the trapezoid typically take about 20% of your rectangular capacity out. An example used it was in that ballpark with the adjustment reducing the denominator by 34 from 180 down to 140 sticks. Now, let’s go over some other ways you might want to measure your center’s utilization in conjunction with the utilization metric, which can be tracked in the iQueue for infusion centers application. These include patient hours and volumes, picture utilization and percentage of days you run out of chairs, scheduled versus actual utilization, and ability to absorb add-ons, and other adverse events. Each of these metrics measures the utilization of your center in different ways that could impact the way you choose to plan your operation. 

Let’s start with patient hours and volumes. Patient hours and volumes are both important measures of patient access. Bodies by themselves are good initial indicator of patient access on their own but do not account for the length and complexity of treatments, and those are best gauge when taken together with patient hours. In this example, we are displaying, for instance, you can see that there is a spike in appointments on Feb 22, but dramatic like an unmanageable number of patients or a very busy day. However, when looking at the patient hours, which is this yellow dots here, we see that the number of patient hours on Feb 22 is similar to the number of patient hours on Feb 3 and Feb 6. Suggesting that there will be a similar load on the chairs, this could be because the length of appointments were skewed toward shorter appointments on that day, or the appointments ran shorter than they were scheduled for in Feb 22 compared to other days, which potentially could have helped offset the fact that volumes are high. Could also be useful to look at these metrics together over time to identify trends. 

At a high level, high volume days could put a strain on your nursing capacity. And high patient hour days could lead to patients having to wait for chair space to open up. By looking at both of these metrics consistently over time, you can identify whether each of these resources is being properly, properly utilized, or one of them is being consistently over underutilized. In a perfect world, nursing and check capacity are in sync in a level low today where both are available to patients when they arrive. One other thing to note is that changes in patient hours could also reflect the gaps in your appointment scheduling where there is some space between appointments as we were describing earlier. So patient hours seem relatively low to the volumes that you’re seeing could be a sign of less than optimal scheduling in patterns. Next, we’ll take a look at peak chair utilization. Even if you know that you’ve seen 108 patient hours and 30 patients for a day, you might also want to know whether there are any bottlenecks during the day that were substantial enough to cause you to run out of chair space. 

This is related to utilization metric in that the way that your patients flow into chair ramps up will have a significant impact on whether you will run out of chairs. You ramp up too slowly relative to what is possible or patients arrive systematically late on a particular day that could result in a cluster of patients arrival arriving simultaneously, which runs the risk of both causing you to run out of chairs, and for your nurses to be overloaded. This can lead to a cascading effect where it gets progressively worse to the point where you run out of chairs and patients are experiencing. For this chart, the horizontal line represents your check capacity. In this case, 30. and the points represent your peak chair utilization by day. The center ran out of chairs on Feb 3, 6, 8, and 22. 

Not coincidentally, as you may recall, these were also some of the higher patient hour days that we were showing in the previous chart, though there are frequently other factors that come into play as well that can cause you to run out of chair space. In addition to knowing if you run out of chairs on a single day, you might also care about how often you’re running out of chairs over time. Indicated here as the percentage of days over max capacity, which in this case is 19%. We also include how long an average year over max capacity when you are over max capacity, in this case, 45 minutes. Since being over capacity for 10 minutes on a given day has a much different impact on patient experience than if you’re over capacity for say two hours or even longer than that. 

Another important metric is your schedule versus your actual utilization. Actual utilization is what patients and nurses feel on a day to day basis, so most utilization metrics correctly focus on actual utilization. However, scheduled utilization is also important since it can help measure whether you’re putting your nursing team in infusion operation in a position to succeed in the first place. The metric we are showing in this slide is median chair utilization, which represents how your actual chair utilization played out over a period of time. Looking at this over a period of time is useful because it helps smooth out the impact of any individual day, and helps you spot trends in your schedule versus your actual utilization. In this example, you can see that the center’s actual utilization marked in pink typically starts to run above its scheduled utilization, marked in blue, around 10:00 AM pretty consistently for the remainder of the day, which is usually caused by same day add-ons outnumbering same day cancelations or appointments running long systematically, relative to what you expected them to run. 

This has important ramifications for scheduling. If you were to book up to check capacity or even near it on an individual day, this tendency for actual utilization to rise above schedule utilization could cause you to go above your chair capacity. The best thing to do in these situations is to allow yourself some buffer where you’re not scheduling up to your chair capacity throughout the day, but perhaps to a future below capacity. The opposite scenario where actual capacity is under scheduled capacity is typically easier to deal with, but can also inform your decision making when it comes to scheduling. If you consistently using fewer chairs than anticipated, then you can be fairly comfortable scheduling right up to your chair capacity. And in some extreme case is [AUDIO OUT].. 

That can monitor your available capacity relative to your max capacity, which can give you a sense of how well you might be able to respond to unexpected add-ons or adverse reactions from patients. In the diagram we are showing here patients flow, reflect the dotted line which is an optimized level loaded day would have some room to absorb patients throughout the day with this max of about 18 chairs relative to its 19-chair capacity. The solid line. However, would be in a much more precarious position, which is that orange line when it comes to being able to take an add on because it’s a ready schedule to go over capacity for much of the day, particularly in the morning. This is another good reason why you might want to give yourself some buffer chairs when you’re in a position to do so. 

Having buffer gives you the flexibility to respond to unexpected– disruptins the operation for the rest of the day. In summary, when developing a utilization metric it is important to try to account for the variables that might impact your operation at the beginning and end of days. It can also be useful to use that metric in conjunction with other utilization metrics that can help you monitor engage your center’s overall utilization trends. With that, I’ll turn it back over to Marianne for questions. 

MARIANNE BISKUP: And yeah, we have a few questions already. But I want to remind you, if you’d like to ask a question, use the Q&A box, which is in the upper right hand corner of the screen because we really love engaging with all of you. 

First question, does iQueue factor in each center’s parameters or is it by the institutions pledge system. I am from a system wide network, but each of our centers operates in very different ways. 

CHRIS KOH: Yes, iQueue actually does factor in each center’s specific operational inputs like what we were showing on slide 4 for Acme. We take these inputs along with your historical data. We generate these level loaded templates, and we try to help optimize your utilization and unlock capacity. 

MARIANNE BISKUP:. Another question, do nurse lunches have an impact on my utilization metric? 

CHRIS KOH: That’s a good question. Counterintuitively, actually they do not impact the calculation as a metric if you plan them properly. So you can actually schedule your appointments around your nurse lunch schedule, so that the touch times required when a nurse is on lunch can be handled by a backup nurse or is not required at all, so the patient just might be sitting in a chair while the nurse is going to lunch. If you don’t plan for properly, it can, indeed, lead to some capacity leakages, so it’s definitely something you do want to plan for, and that’s something we do account for with the iQueue system. 

MARIANNE BISKUP:. And looks like this is our last question do nurse handoffs, at the end of the day, have an impact on my utilization calculation. 

CHRIS KOH: Yeah, that’s another good one. It can actually have an impact. It could lead you to have overloading of the remaining nurses at the end of the day where nurses taking on more patients than was originally expected. And that could lead to the ramp down not being as deep as you’d like. And so what that means for your utilization metric is that you would wind up using a denominator that needs to be slightly larger than it is. And so that would mean that you’re actually overestimating your utilization a little bit in those cases. 

MARIANNE BISKUP: OK, it looks like that’s it for questions. I want to thank everyone for viewing our presentation today, and a big thanks to Chris for presenting the webinar. Keep an eye on your inbox, we’ll be sending out a link to the recording of this session. And want to remind you, even though the webinars concluding we still more than happy to field questions. You can text us 6308845493, or you can always email us demo@leantaas.com. I know we’re all tired of seeing surveys pop up our screens, but please take a few seconds it’s a very short survey. That a complete the survey that will pop up, it helps us fine tune our webinars so that we continue to provide content and value to you. Again, thanks for tuning into the webinar, and have a great day. Thank you.