Webinar Transcript: How Seattle Cancer Care Alliance is transforming infusion operations using predictive analytics
At our winter 2021 Transform event, Emily McCambridge Kowalski, Patient Access Operations Manager at Seattle Cancer Care Alliance, and Armand Indra, Product Implementation and Customer Success Manager at LeanTaaS, discussed how SCCA used iQueue to optimize daily infusion operations, to the benefit of patients and staff alike. Visit the Transform Infusion track page to hear the full talk.
Moderator: It is my pleasure to introduce today’s speaker, Emily McCambridge Kowalski, Patient Access Operations Manager at Seattle Cancer Care Alliance. Emily received her Master’s degree in Healthcare Administration from Colorado State University in 2017. Emily oversees the infusion scheduling, and works closely with the access staff and nursing team to support the infusion and clinical trials operations.
We also have Armand Indra, Product Implementation and Customer Success Manager at LeanTaaS. Armand has worked with multiple leading healthcare institutions by using iQueue to optimize infusion center operations. Previously, Armand was a healthcare consultant and holds a BS in human biology from the University of Southern California. With that, thank you so much for being here. And Emily, I’ll now turn the floor over to you.
Kowalski: So just a little bit about Seattle Cancer Care Alliance. We’re the clinical arm of a partnership between Fred Hutch Research Center, the University of Washington Medical Center, and Seattle Children’s Hospital. We serve a diverse patient population and have a heavy focus on clinical trials, which include conducting Phase One through Four clinical trials on our main campus. Our main clinic is located in South Lake Union in downtown Seattle on a shared campus with Fred Hutch Research Center, but we also have a presence at several community sites in the surrounding area.
Indra: Thanks Emily, for walking us through a little bit about SCCA. A little bit about LeanTaaS and iQueue: we currently have three products, you can see them down here. One is iQueue for Operating Rooms, number two is iQueue for Inpatient Beds, and the third product is iQueue for Infusion Centers. Across our three products, these are our achievements. We’re in over 450+ leading hospitals, 13 of the top 20 health systems, and in over 120 health systems total, across 42 states in the US. For this presentation we will focus on the iQueue for Infusion Centers product and some of the results Emily has had on her site.
Kowalski: So just a bit of a summary of where we were pre-COVID, during COVID and our current state. As I’m sure it probably was for you, COVID was hugely impactful on our operations and our patient volumes. We planned for a patient surge, but instead experienced decreased volumes during the COVID in Summer 2020. The last few months we’ve returned to pre-COVID volumes with our completed appointments and inpatient hours increasing while our wait times have remained flat.
One of our biggest pain points pre-COVID was our nursing assignment process. It was entirely manual, handwritten by pencil the afternoon before each day, taking a charge nurse on average four hours to complete. The changes and cancellations were not easily caught and patients had to be erased and redistributed with morning sick calls, taking additional time from the morning charge nurse. In March 2020, right at the start of COVID, we implemented the nurse allocation feature in iQueue instead of writing each patient by hand. iQueue automatically distributed patients across the available nurses. The charge nurse then looks at speciality skills and distribution of higher acuity treatments such, as first doses. Overall this resulted in a change of three to three and a half hours of reduction in nursing time each day that we then reallocate to other areas. Our Real Time Data Feed automatically captures add-ons and cancellations, and sick calls can be easily redistributed by either rerunning the allocation or just dragging patients around.
During the peak of COVID, we also experienced additional challenges with the need to extend our operating hours and opening additional services such as our Acute Clinical Evaluation Unit, which was tasked with helping decant patients from the ER and the hospital. Our infusion team also supported the implementation of a hotline for patient questions around COVID. We continue to operate a COVID Testing Center for our patients and our staff through all of these changes. We were not given any additional staffing and also had to cope with more stringent sick call policies that were meant to keep our patients and staff safe. We also had to adjust to new dynamics with some of our administrative staff moving off site. One of the adjustments we made during this time to help us be more equitable with the work, and agile with our staffing, was to adjust our use of the nurse allocation feature by dividing nurses into pods.
Due to differing scheduling practices, our schedule is s broken down into hematology/BMT patients and general oncology patients, but by pulling these two resources together with the nurse allocation, we were able to mix transfusions and hydrations more evenly with our heavier chemo regimens across the units without needing to change our scheduling practice. Nurses that used to be in the general oncologies, solid tumor side, are no longer left with an assignment filled with chemo regimens, which also come with a large amount of chemo verifications and have a more even mix of transfusions and hydrations. It also ended up in a more even workload for our support staff in both areas as well.
For the current state: the physical space continues to be a constraint for us, and with our volumes ticking back to pre-COVID volumes, capacity management has been a main focus. We worked with our team at LeanTaaS to explore possibilities for alleviating some of the load. One of the main areas of opportunity was level loading patients to Tuesdays, which are historically a low volume day for us across all of our units.
In addition to level loading some of our visits to Tuesdays, we also recently implemented different scripting to align with best practices for scheduling. Historically our schedulers have asked patients what time they would prefer to come in and if that time was not available, they just add them to a waitlist. It’s frequently the case that the time they want is not available. So in the current state, we are offering patients a choice of different available appointments, with the hope that one of those times will work for them and then we can avoid the waitlist process entirely.
After the scripting change, we saw an increased the utilization of Tuesdays, and we also took our waitlist from a high of over 500 patients within a three month period to a low of under 100.
Indra: Thanks Emily for walking us through SCCA, as well as some of the results you’ve seen with iQueue. On this slide, I’ll walk through a little bit more about iQueue, a little bit what we saw before iQueue, and what we see after iQueue’s been deployed. Then the third piece is some of the successes at SCCA specifically.
So before iQueue, what we typically find are three main problems that infusion centers face. One being long wait times: patients wait for a long time for infusion appointments. Number two being this midday peak, you see this triangular shape right here where the chair utilization starts out low and ends low, but there’s the midday peak where they might go above chair capacity and just feel really busy between that 10am and 2pm time. The third problem we see is burnout, because these two other problems kind of snowball, so staff starts to feel extremely burned out or they’re not able to take any lunch break.
So these three problems, long wait times, midday peaks, and staff burnout are what we typically see at infusion centers. Now the question is, how do we solve that? We solve that by walking through these optimization algorithms. You see three gear icons, which symbolize three main things. Those three optimization algorithms come in the form of the optimize phase, the operate phase, and the learn phase.
In the optimize phase we essentially deploy this optimizing scheduling template that level loads the day while respecting the unique constraints faced by the infusion center. The second place that we go into is this operating phase, where we use forward-looking analytics to anticipate how days, today and the future, will unfold, to solve problems before they happen. The third phase we go into is the learning phase, where we monitor the actual versus expected performance to pinpoint improvement opportunities and update templates as operation evolves.
So once the optimization algorithm is deployed and the center is using iQueue, we typically see improvement in those three main problems I mentioned, which was long wait time, a better midday peak, and staff burnout. So the way we kind of pictured that In this slide, it’s kind of like Tetris blocks, right? Then to fit them together and be more compact and a little more level loaded where you get this trapezoid shape.
With SCCA specifically, what we found when they continued to use iQueue, you can see in the current state they are getting value in three main areas. The first is improved patient access, and as Emily discussed, we were able to decrease the waitlist by 80% from 500 to 100. The second piece is balanced workload across the week. With SCCA specifically we were able to see Tuesdays being better utilized while Mondays going a little lighter, and that leads to the third thing, we just improved utilization of resources. By having the days be pretty level loaded, your resources are being better used. So those were the three main problems, and then the three things that iQueue has has helped with SCCA
Kowalski: One great aspect of our partnership with LeanTaaS is our participation in the Customer Advisory Board. We meet every other month to give feedback and gain insights into new features and previews of things that are coming. And it also gives us an opportunity to share what our current pain points are and see what’s in the works to help us improve our operations going forward.
Future goals: we hope to continue to leverage iQueue to provide insights for us, especially with our linked and unlinked appointments for patients, so patients that are not seeing their provider the same day, trying to push those into all of our hours of operation We are also trying to open a new building in early 2023. We are continuing to grow our patient population, so we will have different challenges related to capacity management. For that, we also have to manage short term staffing challenges with staff members that are either getting COVID or exposed to COVID and needing to quarantine for long periods of time.
Overall our motto at SCCA is “Better Together”, and that definitely applies to our partnership with LeanTaaS and iQueue. You can open up now to any questions.
Moderator: Thank you so much Emily and Armand for this great presentation. We’d love to take some questions at this time. If you have any questions, please chat them into the Q&A box now.
Our first question looks like it’s for you, Emily. How did you convince patients and schedulers about the new scheduling best practices?
Kowalski: This one was as far as changes go pretty easy to rollout. We just went back to some scripting that we had originally tried to roll out in 2017, but now with our continued waitlist and the challenges related to that, it is an exhausting process for both our patients and our schedulers, so everybody was pretty on board with coming up with a way to reduce that. Overall after implementation, we have very minimal pushback from patients. They hardly noticed the change and for the most part were happy with the times that they were offered and avoiding the waitlist entirely.
Moderator: Great, thank you. Armand, this next question is for you. This attendee says, “I represent an infusion center of only 15 chairs, will I see value from deploying iQueue?”
Indra: That’s a great question. The short answer is yes, you will see value. Usually you’ll see it in this in the form of improved wait times, utilization level loading, allowing nurses to be able to take lunches We’ve seen some of these successes specifically with SCCA.
Moderator: Great, and a follow-up question for you, Armand. Is iQueue able to work with any EHR or EMR system?
Indra: We can work with any EHR or EMR system. It can be Epic or Cerner, those are the biggest ones we’ve seen, but we’re pretty flexible with any systems.
Moderator: Thanks for that clarity. Emily, how do you deal with last minute add on appointments on Tuesdays?
Kowalski: So on a daily basis, our cancellations and no shows outpace our add-ons. For the most part we are just repurposing patients that have canceled and filling add-ons into those spaces. We also do maintain a list of patients looking for earlier times, so we can be more flexible about moving patients into those spots and creating add-on space later in the day that we may have more time to get a request for.
Moderator: Wonderful, thank you. Armand, do the schedulers schedule appointments into iQueue or do they need to do it in the scheduling system?
Armand: Great question. So schedulers will continue with their regular practice, which is scheduling into scheduling systems. There shouldn’t be major changes to their workflow, iQueue just provides additional insights to your team on the best way to schedule appointments.
Moderator: That makes sense. Emily, another question for you. This attendee says, “My center has a really high number of no-shows on a daily basis. How do we plan for that so we’re not constantly overstaffed?”
Kowalski: So we do our staffing to our scheduled volume for our nurse ratio, so that has its challenges, either if you have a lot of no shows or add-ons. But from the no-show perspective, really we try to be flexible with where the nurses are working for the day, schedule them across units so they can go help out somewhere else if we have a high rate of patients not showing up for up for one area, or just utilize them in a different capacity than patient care they can be providing breaks to other nurses or helping in other ways
Moderator: Great, thank you, and sort of a follow up question, but this one is for Armand. How does iQueue handle changes to the schedule, such as cancellations and reschedules and no -shows?
Indra: iQueue basically uses our learning algorithm to pick up insights and data. Essentially from your data trends, we can see and account for those cancellations, reschedules and no shows when we can create this optimized template, which is the best kind of the optimized template, how iQueue recommends staff should schedule appointments.
Moderator: Thanks for that. We have another question for Emily. This attendee says “We have had many of our staff out sick. How do you handle nurses calling in sick on the same day?”
Kowalski: So that’s one area where the nurse allocation tool has been really helpful for us. It gives us an insight into the multiple units that we have and where we have some capacity to redistribute those patients. It also makes the physical act of redistributing the patients much easier by being able to drag them up and run that reallocation in iQueue, to get those patients fairly distributed with the nurses who remain for the day.
Moderator: Great, thanks Emily. Looks like we have another question here for Armand. This attendee asked, “How long is the implementation process with iQueue?”
Indra: Great question. Generally it’s a light lift for the IT team on the customer side, so we can move as fast or as slow as you guys want or need. Specifically, if you have challenges on any deadlines or issues or other projects that your team’s working on, we can adapt to your timeline. From our side we’ve seen it move as fast as about five weeks and on the opposite end it’d be a little bit longer based off your staff’s constraints.
Moderator: One more question here. It looks like it’s for you, Armand. This attendee is asking, “What else can I see in Queue?”
Indra: In iQueue, our product is formed of two things. One is our template. It provides this optimized template of the recommendations for how you should book for the week. The second piece is the web app, and there’s two major things you’ll see in it. One piece is kind of the forward-looking analytics. Just like the weather, you’ll get insights into the future for how your weeks or even day will unfold. That way you can basically adjust or go in for a quick huddle to know and accommodate for those days. The second piece you’ll also see is those retroactive analytics in the web app. So they dig into answering questions, like why does my day look bad, what can I do to improve, as well as giving you the raw data, like how are my patient loads, what were my cancellations, wait times, etc. Those are the kind of things you can see in Queue, in the web app and the templates.
Moderator: Armand, thank you so much. Unfortunately That is all the time we have for today. But I want to thank Emily and Armand for taking the time to chat with us and I also want to thank LeanTaaS for sponsoring the event. Have a great day.