Rae Woods (00:02): From Advisory Board, we are bringing you a Radio Advisory, your weekly download on how to untangle healthcare's most pressing challenges. My name is Rachel Woods. You can call me Rae. We're not that far into 2024, and if I'm honest, we've already spent a lot of time on this podcast talking about the financial dynamics impacting health systems, and we all know that surgical services are going to be a big part of their economic outlook. (00:30): Here's the thing. If I were to Google right now, what is the future of surgery? I would probably see a bunch of headlines about robots entering the operating room, things that maybe make for a good cable TV show because they're novel, they're flashy, but I'm not sure they're actually going to address the real challenges that surgery leaders are facing today, let alone health system economics writ large. (00:54): So today, I want to talk about what the future of surgery will actually look like. To do that, I brought three Advisory Board experts. Isis Monteiro, Miles Cottier, and Paul Trigonoplos. They're going to talk about what's next in surgery and what it will take to see surgery [inaudible 00:01:11] its margins. Isis, Miles, Paul, welcome to all three of you back on Radio Advisory. Paul Trigonoplos (01:21): Morning. Isis Monteiro (01:21): Thank you so much for having us. Miles Cottier (01:22): Thank you. Good to be back. Rae Woods (01:24): So I want to admit to you from the start. I was up late last night... Our listeners are going to figure out really quickly when we recorded this episode. I was up late last night watching the Grammys, and I'll be honest, I never really watch cable TV anymore, and an advertisement came up for a local hospital system near me. I will not name this organization, but they started talking about why patients consumers should come choose that hospital. (01:49): They were listing off all of these cool things. And I'm not kidding. One of the things they talked about were the cool tech products, the cool innovations that they have as part of their surgery, and that's what I and the general public and the people who made this ad clearly think about when they think about the future of surgery. What would you have said to me if you were sitting on the couch last night with me watching the Grammys when we saw that advertisement come up? Paul Trigonoplos (02:21): I would've asked if they were a center of excellence. Rae Woods (02:23): I don't think they were. They didn't say anything. It wasn't a specific service line, it wasn't a specific specialty, it was just general. And then they moved on to other things. The new campus, the new parking situation, honestly. But seriously, is the future of surgery these new fancy things that we can add into ORs? Paul Trigonoplos (02:46): So I'm not going to sit here and say that robots are not going to be where innovation comes in the future. There's a new robot for a different subspecialty coming out that it seems like every week or every couple of weeks globally. It's not just da Vinci and Hugo anymore. It's worth talking about robots are capable of much, much more. (03:04): They're a lot smaller than they used to be. Da Vinci's new model can do valve replacements in the heart. In 2021, we even saw Hopkins trained a robot to completely autonomously in terms of planning and delivering a surgery, doing four cases where they connected two ends of a pig intestine. Rae Woods (03:24): You're making me think so far that the commercial was right then. Paul Trigonoplos (03:27): I think that robots are going to be here, and they're going to continue to be a part of surgery. I would also push to ask for the vantage point. When you talk to certain surgeons or medical device companies or centers of excellence or you go to a conference, you're going to see a lot about robots. Rae Woods (03:47): Yeah. Paul Trigonoplos (03:47): But for your average hospital and health system, and you can even extend that to just provider in general, at the end of the day, I don't know if this stepwise hardware improvement innovation is going to be where the big focus is, at least in the next five to 10 years. Rae Woods (04:03): Then how would you characterize the future of surgery in the next decade? Paul Trigonoplos (04:08): If you are talking about the health system and you ground the conversation sort of what they're feeling and the problems they're dealing with the future is something much less flashy, and I think it's going to end up being a lot more about software and what the OR feels like and how efficient it is than something like hardware. Rae Woods (04:29): I appreciate this, and I'll be honest, I get a little bit nervous when I see other outlets talk about the future of X, frankly, whether it's something about healthcare or otherwise, because there's always been this temptation to talk about the shiny new thing, right. That's something I've been very mindful of over the last 14 months with the onset of generative AI. So I almost want us to ground this conversation about the future in actual challenges. Challenges of the present. (05:00): And I'll be honest. Over the last few episodes, I know that you all have been listening. We've talked a lot about health system economics. We've talked about the fact that high-profit volumes like surgery play a very big role in protecting system margins and that those are moving into more and more outpatient settings. So how should we actually diagnose the biggest challenges in surgery? Is it merely just this volume shift, or are there other things we should be paying attention to? Paul Trigonoplos (05:25): I think for the health system especially, it is around the growth and demand and then comparatively the limited supply on ORs, on surgeons, on anesthesiologists compared to it, at least in the next decade. And that's for a few reasons, mostly demographic, and that's happening around the world. (05:46): And we're seeing it really impact, to your point, operations and margin and access right now, which are all very core pillars of any provider organization. And we're seeing it shape out now already in a few ways. First, there's been what we've been calling a decoupling of margin and volume. Rae Woods (06:05): Yeah, yeah. Paul Trigonoplos (06:07): The cost per case around the world is going way, way up, namely inflation and labor costs. We surveyed some US chief strategy officers late last year, and of the people that expected volume increases by the end of 2023, about half of them expected margin decreases, right. Rae Woods (06:25): Even though volumes are coming back, right, we waited a long time for the volume shift in the pandemic to finally come back to two hospitals in particular when we were looking at these high-profit surgeries. And you're saying that even if those volumes are back margins are not? Paul Trigonoplos (06:41): Yeah. I mean, we've got a couple quotes from interviews that I think speak to this. One last year said that, "This is the first time in my 30-year career where beds are full, and I have no margin." Rae Woods (06:53): Wow. Paul Trigonoplos (06:54): And just bringing it back to robots for a second, when I was down in Australia for work in November, we had a session on the future of surgery, and one of the directors of strategy said, "If you ever come across a robot that has proof to help my margin, let me know. But until then, I'm going off the assumption that that's not a solution to that problem." Rae Woods (07:12): Oh, wow. Paul Trigonoplos (07:12): I think that's where a lot of health systems are coming from right now. Isis Monteiro (07:15): Yeah, I think part of the problem as well is that our historical solution set just isn't going far enough anymore. Adding more beds, adding more staff, buying more stuff hasn't led to enough productivity gains to be able to keep pace with this demand growth. (07:33): So even improvement initiatives that have been effective historically, like expanding the scope of practice for surgical staff, pulling forward patient [inaudible 00:07:44] and anesthesia, implementing early discharge strategies and et cetera, those haven't been sufficient. And so health systems have to look to new solutions and an entirely different approach and able to... to be able to address the challenges that we just discussed. Rae Woods (07:59): I really appreciate this take, Isis, because you're saying that, first of all, the problem is not that we don't have the right kind of luring innovations to bring in the next generation of consumers. We actually have a different problem that we need to be solving. We have a margin problem. And you're also saying that the tools that we have at our disposal that we usually use just aren't going to be enough. Paul Trigonoplos (08:21): It's also worth talking about a reality that I think, especially in surgery, takes shape that I don't think we appreciate enough, which is that we are really victims of our own success in many ways. So anytime you make some new innovation that makes something smaller or better or faster, you expand access. Rae Woods (08:41): Yes. Paul Trigonoplos (08:41): You expand the amount of cases you can do. Yes, drugs may take the place of procedures in some cases. I don't know if that's imminent, and I don't know if that's going to be at the scale that we need to solve this supply problem. Rae Woods (08:55): You've mentioned a couple of individual players in the health system. You mentioned the chief strategy officer, for example. I want to channel actually the health system planner in part because I know we've done some surveys here, and we've tried to look at what is the top priority for strategic planners at health systems in 2024. And what came up overwhelmingly is operational efficiency. (09:20): And anyone who's been listening to episodes this year should know that that's not a surprise because our colleague Vidal said that hospitals have basically had to put pedal to the floor and focus relentlessly on being a good operator. My question is, and I'll admit, I don't know that I really know how operational inefficiency actually plays out in surgery. Paul Trigonoplos (09:45): Yeah. I mean, I'm not surprised. Given kind of the margin commentary I had before, I'm not surprised that it shot to the top. Depending on who and where you are, surgery makes up like 30 to 70% of your volumes. It is pretty core to the acute care enterprise. And to answer your question, and this is kind of what we spent most of our time doing last year on interviews, is understanding the status quo of what systems are and are not doing in the way of operational efficiency with surgery. (10:14): Most systems do not have real-time visibility into OR supply. They don't have real-time visibility into surgeon capacity across like a footprint. They predict OR blocks that are too short or too long. The inaccuracies mess with each OR schedule each day. They cause overruns and overtime. They either haven't equipped surgeons with the tools they need to speed up the pre-op planning process, which is quite time-consuming. They still resource and staff every single OR they have to the gills just in case- Rae Woods (10:48): Wow. Yeah. Paul Trigonoplos (10:48): ... they need to get certain cases. All these types of things, I mean, there's inefficiencies in all of them. And unpacking what organizations around the world are doing to solve them is kind of where we focused our research on. Miles Cottier (11:03): I wanted to kind of jump off Paul's point and actually give some systems [inaudible 00:11:07] in fact, most systems credit, right, because I think we have seen some systems, most systems take iterative steps to improve operational efficiency. But if you're thinking about things like staffing or less wasteful resourcing or the big one at the moment, right, shifting cases to ambulatory, they are not in isolation- Paul Trigonoplos (11:26): Yes. Miles Cottier (11:26): ... nor are they the wrong thing to do, but we are not very good at scaling them up, right. Increasing efficiency at the scale that we need to actually drive up the ability to meet demand, not just in subspecialties also in surgeons. Rae Woods (11:42): And margin is what we're talking about here, right. We're talking about shoring up the hospital business, right, the surgery business here. So I do want to move from problem to talking about the opportunities talking about the solutions. Help me understand where even are the opportunities to improve efficiency in surgery. Isis Monteiro (12:02): A few themes came up out of our research around the capabilities that health systems are developing to address these capacity and financial pressures, so we see market-leading systems investing in novel solutions to do three things. The first is proactively manage demand and match surgeon and OR supply to meet that demand. (12:24): The second is investing in technologies that enable surgeons to make more accurate treatment decisions earlier in the patient journey. So predictive treatment planning. And the third is tiering their ORs by case complexity or case type. And this is what we mean when we say hyper-efficient operating rooms. Rae Woods (12:44): Okay. I do want to make sure we have time to talk about all three of these. The first one honestly feels the most replicable to me, right. You were talking about patient flow. You were talking about scheduling. How does this currently work when it comes to surgery? Where's the opportunity to actually improve here? Isis Monteiro (13:00): Yeah, so I think to Paul's point earlier is that health systems, again, very limited visibility and to demand an OR and surgeon capacity across their entire system or region, which leads to an uneven distribution of cases across their ORs. And so surgeons can't perform as many cases as they could otherwise. Another thing that you could say is suboptimal is the number of cases that health systems use to determine how long an OR block should be. (13:29): So again, they're using an average of the past 10 to 15 cases to schedule an OR block, and that's not nearly enough data to be as precise as you need to be in order to minimize overruns or reduce idle time. And the last thing on this patient flow bucket is that health systems, again, have very limited ability to predict when appointments are going to be canceled and to proactively intervene to prevent that OR block time from being wasted. So again, each of these three things contributes to long wait times to consultations and to treatments and to idle or unused OR time and to cost as well. Rae Woods (14:08): And I should say the things that you're talking about, they're super technical, but this is the stuff that works. This is the stuff that we know that health systems hospitals need to be focused on right now when it comes to being that hyper-efficient operator. (14:20): And you're reminding me of a lot of the recommendations that we've actually given to health leaders on the ambulatory side that's been quite successful. It's just maybe finally now moving into surgery. Is there an organization that you can point to and an example that you can point to as someone who's really successfully doing this hard work to solve this operational challenge? Miles Cottier (14:44): Like Isis said, when it comes to scheduling, which I think if you talk to most members, that is one of the kind of key bottlenecks, there's a lot of inaccuracy and that leads to overruns, and that in itself leads to things like impacts of flow and costs and staffing, et cetera. (15:00): It comes down to the fact that we're only using data from the average past 10, 15 cases, and that's just not enough. But we found... And like I said, I love this story. We found an organization in Ontario in Canada called Halton. Their head of surgery knew that this problem existed and enlisted the help of his daughter, who conveniently happened to be studying computer science at the time and together- Rae Woods (15:24): Convenient. Miles Cottier (15:25): Very convenient. Together, they wrote a piece of code, a piece of Python code, whatever that means, and they can scan over, I think it's over 10,000 pass cases for somewhere in the realm of 10 to 15 in different variables. So procedure, comorbidities, et cetera. (15:41): Anything that's going to impact the schedule, they can scan that, and the machine learning algorithm that they created spits out a recommended schedule, right. And health systems have that data, right. They just need some tool to unpack it. And that has helped them reduce overruns by... It's around 20, 25%, which again saves them a lot of money in the region of $800,000, Canadian dollars, over about three years just on nursing overtime alone. Rae Woods (16:09): Oh, wow. Wow. That is such a wholesome story, and it's a good example of looking for creative solutions, asking for support, help partnership, knowing where you've reached the bounds of what you can do and where you need something else to step in. Miles Cottier (16:23): I'll also add for any listeners that are interested, and this is even more wholesome, the algorithm is all completely open-source and free to download. It's all very altruistic. Rae Woods (16:34): No way. They came up with the solution, and they're giving it away for free. Miles Cottier (16:39): We can include it in the show notes. Rae Woods (16:41): Wow. I know I just mentioned that we have to look at these very kind of technical operational solutions, but what this story reminds me of, Miles, as wholesome as it is, that we can still do these kind of cool, new age, sexy innovations for these very operational problems. (16:57): And, of course, here I'm talking about AI. So right, you just gave a code example, a machine learning example. Are there other kinds of organizations that are using the next generation of artificial intelligence to help solve some of these very practical problems? Isis Monteiro (17:13): Yeah. So I can share the case example from Brazil. I love sharing case studies from my home country. So Albert Einstein created a machine learning algorithm that can predict the likelihood that a surgical procedure is going to be canceled and kind of important context setting. But in their context, surgeons can book their own or times, so they would often book their or to hold the space even if they didn't have a patient to operate on. (17:39): And so this would lead to a lot of last-minute appointment cancellations if they didn't have someone to complete the procedure on. And so, the algorithm that they created is mostly based on nonclinical variables. So who's the surgeon, how long before the surgery, was it scheduled, and what day of the week is the appointment scheduled for? Things like that. (17:59): And for each appointment that has a high likelihood of cancellation, they have an intervention team that can proactively step in and connect to the patient and surgeons who preserve that original appointment. And in the event that they're not able to prevent the cancellation, then they're able to slot in a patient from their waitlist. And by implementing this algorithm and other patient flow improvement initiatives, they were able to increase their OR use time by 10%. Rae Woods (18:29): Oh, wow. Wow. And I like that you're flagging kind of things that are different in the surgery space than what we would see in things like primary care, by the way. So, for example, we see perhaps not as sophisticated examples of folks using these nonclinical variables to determine if an appointment is going to be a no-show. We see lots of double bookings there. That's been something that's been really effective in the ambulatory space. I like that you said that the concern here is perhaps not always the patient. Isis Monteiro (18:56): Yes. Rae Woods (18:56): It's the surgeon. Isis Monteiro (18:58): Yeah. Miles Cottier (18:59): As we were talking about cost earlier this came to mind. We did some relatively rudimentary number crunching because I had no idea how much it cost for a surgeon to cancel on the same day as the surgery. And I'm generalizing based on geographies and different surgical areas and stuff, but it's around about 5,000 US dollars per cancellation on the same day. So €2,500 [inaudible 00:19:25]- Rae Woods (19:24): Okay, now you're showing off, Miles. Miles Cottier (19:27): ... Australian dollars. Conversions are good. I know, I know. They're all probably horrendously wrong now. Rae Woods (19:32): Yeah. Miles Cottier (19:33): But that's just factoring in the lost OR time, right. That doesn't factor in staffing. That doesn't factor in resourcing. That shows you how much of a boon it is if you can get ahead of those cancellations. Rae Woods (21:24): I have a thought that I almost hesitate to say out loud while we're literally recording, but what you just described are the obvious dollars that are on the line that no one can afford to lose. (21:37): And this is where I hesitate to admit this, but the two examples that you just gave, they seem like easy solutions. They seem like things that we would describe as, I hate this phrase, but low-hanging fruit, right. The things that everyone can do. My question then is, what is stopping the average health system from doing these things? Aside, perhaps not having a daughter that happens to be in computer science. Paul Trigonoplos (22:05): We've given the speech version of this to folks from 10 countries, including the US. I've never heard any response to those stories other than, "Why don't we do this already?" Rae Woods (22:16): Wow. Paul Trigonoplos (22:18): I don't know what the reason is other than maybe it's just so new, and no one ever said that it's a solution that everyone should consider. Rae Woods (22:28): I mean, it also requires... in the scheduling example that we just gave, it requires changing something that I'll just say is incredibly sacred to physicians, let alone surgeons, which are their schedules, right, for example. And that, for a long time, has been a bit of a third rail for organizations. Miles Cottier (22:47): I would also say that the end number for a lot of these kinds of tools is pretty low. These are emerging technologies. So there's a reticence from a lot of health systems to copy without there being a huge wealth of evidence that these things work every time for each organization. And most of them, the ones that we discussed already are built. Rae Woods (23:08): Yes. Miles Cottier (23:09): So you can't necessarily directly copy it verbatim. Rae Woods (23:12): Unless they're giving it away for free, like the example that we're apparently going to add to the show notes. But I do think there's a larger point here about when we're going to be doing any of these changes to the operations of any kind of clinical pathway, we have to, of course, be thinking about what that means in terms of our own kind of business economics. (23:33): We need to think about it in terms of the patient. We also need to think about it in terms of the doctor, and no solution is going to actually be successful if it makes physician's lives harder as opposed to easier. So how are we thinking about the kind of workflow side here? Isis Monteiro (23:47): When we're talking about clinician resistance? I think it isn't about fear of the technology itself, which we might assume or scapegoat. It's a lack of trust and change leadership. Rae Woods (24:00): 100%. It's not actually about the technology. We like to blame the technology, but it's never that, actually. Not in my experience. Isis Monteiro (24:08): Absolutely. So it's more of reaction to how previous rollouts have gone than to the new technology or process itself. So as with anything else, we really have to engage clinicians in the process of developing and implementing these tools to ensure that they are making clinicians' jobs easier and enhancing patient-facing care. Miles Cottier (24:28): The other thing I'm going to add, I think again, these are all pretty new tools, right. So the incentives don't necessarily exist to drive up adoption to the level that we want. So when we've been speaking to health systems, we've been speaking about maybe how you can build in some of those softer elements, like those softer incentives or penalties, right. So you can get some uptake without making everyone angry in the process. (24:50): And what I think a lot of, especially when it comes to AI and machine learning tools, the successful rollouts usually leave the final decision with the surgeon. So if you've got a load of students or residents shadowing you while you're doing your surgeries or you know that, "Oh, my patient today is going to take a lot longer than the surgery scheduling tool suggests," you still have the authority to change the schedule, right. You have the power to change the schedule- Isis Monteiro (25:17): Yes. Miles Cottier (25:17): ... if you want to. And I think that's key to making something like this stick, especially initially. Rae Woods (25:22): Yeah, I couldn't agree more. We've talked a lot about scheduling. It's clearly very, very important. What about the treatment planning part? Isis Monteiro (25:30): We have come across several examples of AI-enabled pre-op planning software that can create customized plans based on individual patient anatomy taken from CT scans or 2D imaging. And this type of software is mostly used for ortho procedures. (25:47): And we're also seeing examples of extended reality or 3D pre-op planning and intra-op software programs for cardio procedures. And these create a hologram of the heart, which can allow interventionists to be really precise with device placements. So pretty futuristic stuff happening on the treatment planning side. Rae Woods (26:08): So there is still cool, sexy stuff happening. It's not just managing schedules. Are there examples on the efficient operating room side? Paul Trigonoplos (26:19): Yeah. I mean, ASCs around the world are generally where you look for what an efficient or looks like. That being said, it's one thing to partner with a management company and have them sort of Lean Six Sigma your OR. Most health system owned and operated, even if their ambulatory ORs, I would say, are not that efficient. They run them like their inpatient ORs. We worked on a case study with an organization in Canada that developed the province's first ASC. In a lot of the ways, it looks like an ASC you'd see in the US, but I think they did a few things that go even further. (26:55): They tiered their cases by complexity, so they have different tiers of complexity, and they adjust the tool allocation and the nurse FTE count based on the tiers. So in the lowest tier, you don't even get a scrub nurse. The surgeon has to pick up a scalpel. It's finding efficiencies that way. We've seen them gain a lot of improvement. I think they've cut... In their lowest tier, they cut 56% of their costs per case. The big thing they did that was interesting, they started with an inpatient suite of tools, right, what they had in the inpatient OR about 120 tools. They got it down to 20- Rae Woods (27:37): Wow. Paul Trigonoplos (27:37): ... in their outpatient ORs. And it took two years of pilots to basically convince doctors like, "You can still operate on a lot of cases without all of these extra tools." They reduced their tool count by 80, 85%. They went to their med device companies and said, "We're no longer going to buy your kits, your surgery kits, because every screw, every plate is up for grabs-" Rae Woods (27:59): Wow. Paul Trigonoplos (27:59): "... or negotiation." Miles Cottier (28:00): Yep. Paul Trigonoplos (28:00): "We can't afford to just have these things collecting dust and not use them anymore." And that's also a trend that we're seeing around the world now too. Rae Woods (28:08): And big change. Paul Trigonoplos (28:09): Yeah, a little bit of an emboldened stance. But I mean, it just shows this is the margin pressure- Rae Woods (28:15): Yes. Paul Trigonoplos (28:16): ... we're under. Miles Cottier (28:17): Mm-hmm. Rae Woods (28:17): The four of us have spent a lot of this conversation actually talking about what real people listening to this episode should do next. We've talked about a lot of the practical guidance that we want our listeners to take. Before we close this episode, I want to ask the opposite question. What should be at the bottom of leaders to-do list? What should they not do when it comes to the future of surgery? Paul Trigonoplos (28:38): With one that maybe seems simple, but it's probably pretty hard to do in real life, is to just don't go into this type of work and expect to be able to solve it within a couple of months. I think all the case studies we talked about and all of the other ones we didn't even get to that are in our future of surgery work, they all took years, right. The time it takes to get docs to buy into some new change without everyone off is a meaningfully long. And that's actually the hard work. Rae Woods (29:10): Mm-hmm. Paul Trigonoplos (29:11): Capital H. I don't think the hard work is coming up with the ideas or finding the tech in Googling online. It's understanding how do we do this and enfranchise- Rae Woods (29:21): Yes. Paul Trigonoplos (29:23): ... our partners. Miles Cottier (29:23): Yeah. I'd say as well, if you can do that, I'd say that's going to open the door for you too for them to run at the solutions. But I would say don't run at the solution straight away. I would start with the... The fundamental question is, what work do we need to improve? What is the problem that we want to solve? Or where are the- Rae Woods (29:44): Yes. Miles Cottier (29:44): ... issues in our system that we want to solve, right? Not what amazing technology can we find that's going to solve it? If we can do that, then we can start to chase the technology that's going to help us answer those problems or those decisions. So really it's chase problems, not solutions. That is probably the thing to do. Rae Woods (30:02): And gets us back to the very first thing we said. We already said, don't chase the fancy robot. Don't also chase the fancy new software. Isis Monteiro (30:09): Absolutely. And it's also... To that point, it's also not just go build an ASC if, to Pauls earlier point, it's just going to replicate the same inefficiencies as the inpatient pathway. We have to be really intentional about where and how we invest our resources and, again, create skin in the game for surgeons in these investments as well. Rae Woods (30:30): Well, Isis, Miles, Paul, thanks so much for coming on Radio Advisory. Isis Monteiro (30:35): Thank you so much for having us. Miles Cottier (30:36): Thank you very much. Yeah. Paul Trigonoplos (30:36): Thanks, Rae. Miles Cottier (30:36): It's been great. Rae Woods (30:43): Look, it's easy to think about the future of healthcare or the future of surgery specifically as the next cool innovation, the next kind of sexy, shiny object to go chase, the next tool. And yes, I will admit that we spent a lot of this conversation talking about operations. Dare I even call it minutia. (31:03): But I want to be clear. We're actually still talking about innovation. We're talking about software innovation, innovations that, to Miles point, solves real problems. And that's what the future of surgery and the future of healthcare really needs. And remember, as always, we are here to help. (31:45): If you like Radio Advisory, please share it with your networks, subscribe wherever you get your podcasts, and leave a rating and a review. Radio Advisory is a production of Advisory Board. (31:55): This episode was produced by me, Rae Woods, as well as Abby Burns, Kristin Myers, and Atticus Raasch. The episode was edited by Katy Anderson, with technical support provided by Dan Tayag, Chris Phelps, and Joe Shrum. Additional support was provided by Carson Sisk, Leanne Elston, and Erin Collins. We'll see you next week.