All right. Thank you, Jeremy. So I'm going to make the case that Netson was successful. I'm going to focus on a few different things. I think there's something to be said, which may not be impressive to other people, but for everybody that spent a lot of time working on this, that we just successfully demonstrated a new concept and a new model of care. We actually got this thing up and running. I think probably most importantly, the program, I think, was very successful in improving access to care. The people who used Netson in terms of the patients and the customers, the customers being providers, I think almost as importantly as patients, were people who were in rural areas, very vulnerable, socially vulnerable areas, and underserved areas. I think you can make a strong case, and I think a lot of folks, if you have been involved in telecritical care over time, I think we all know this, that one of the first things you have to try to do is demonstrate that there's some return or value on the investment, and that's hard to do in terms of outcomes, but I think we can make a case that the sort of concept of having backup, of having a safety blanket, has some value in itself and certainly was experienced that way by people during the pandemic. So the load balancing feature, the providing patient care where there wasn't any, and in particular, as I said, supporting clinicians at the bedside during a period that was very stressful and uncertain, I think actually had a very tangible value, even if it's hard to quantify in any kind of outcomes or financial terms. And then I think also very important was that we learned a whole lot of lessons about how to hopefully do this better, faster, more efficiently, and more successfully in the future. So as I said, really the main lesson is that this can be done. And I'm going to go through a couple, I think, important details about our deployments and the activity that Netsan did. So I think first of all, and I'll come back to this, 58% of the sites that went live with the Netsan platform were critical access hospitals. We were active in small communities. If you look at the city population, the median of the total deployment population was 7,364 people. So this is in very rural parts of the country, obviously without much access to higher levels of care. And I'll talk about that a little more in a minute. Just to see this, there were basically COVID hospitalization rates were similar across to regular other places that did not receive Netsan and between different sites here. I'll show a graph that shows this more clearly in a minute. But in terms of the kind of social vulnerability, most of the sites would score by various systems as being very highly socially vulnerable. The median bed capacity for the hospitals that received services was 25. So these are all small places. That's the hospital beds, right? Not the ICU beds. The median ICU beds was zero. The median number of intensivists was zero. And the median number of ICU nurses at these places was zero. So I think you can make this a strong case that we were providing a service that was needed in a place where it wasn't available. A couple other things to point out here, the 60 sites ultimately were active over the two waves that we're talking about here. We provided, we had different teams. This was a competitive selection process for the teams that ultimately provided care. And so there were some different care models involved. And so both sort of proactive and reactive models were used. Total days of coverage in the end was 1,890 coverage days. There were total unique patients, 1,064 patients, and total encounters was 5,653. So I think, you know, if you think about the nation, those numbers are tiny. But I think they do represent a pretty significant intervention. And I think if you extrapolate those and think about scaling, which I'll talk about in a second, then they're meaningful. These are just some pictures of some of the places where NETCEN was deployed. This picture over here of the map is the NETCEN central kind of command center, which was an attempt to kind of graphically show where we were active and working and sort of also link out to some different reports and kind of a command hub. But you can see we were in quite a few different parts of the country, including in some of the outlying territories of the U.S., Puerto Rico and Guam. It's important to point out these patients were critically ill. So just if you look at kind of the acuity scores for the patients, 84% were, you know, scored as high acuity. So these were critically ill. At our other talk the other day, Jerome Lee talked about how a lot of their work has turned out to be a lot of, you know, kind of primary care stuff. But at least for us in NETCEN during COVID, the patients were, in fact, critically ill. This map, this is a heat map just sort of showing the activity level. And Colonel Pamplin already alluded to the fact that, unfortunately, a lot of times we were a little bit behind the wave, and I think that impacted our numbers. But the only point here is that if you look in the middle of this graph, we did have some sort of peak days where we were ready, we were up and running, and the wave was sort of cresting. And so we did end up with fairly large numbers, which I think is just important as kind of an indication of what this could be, again, if we scaled. You know, money really depends on—that's interesting, Dr. Goldman, you showed up in the middle of this slide. Money, you know, is all relative, right? So in some ways, you could argue this is an expensive program. That didn't show up on any of our other views of this, anyway, ghost in the machine. Anyway, that's a plug for, yeah. So, you know, total clinical costs of the healthcare that was delivered by NETCEN was about $7 million, $6.9 million. That theoretically was what could be billed for, but that was sort of the valuation the care provided. And the infrastructure to deliver these services was about $7 million. So the total budget for this, for the care we provided, was about $13.9 million. If you kind of do very simple calculations, that comes out to about $300 an hour for both a nurse and a doctor to provide care. I have two slides just to sort of put this in perspective. If you look at the fiscal year 2024 budget of Health and Human Services, there's $20 billion in mandatory funding to increase preparedness for pandemics and other biological threats, $1 billion to BARDA, almost $1 billion to the Strategic National Stockpile, $400 million in flexible funding for ASPR to invest in capabilities that enable rapid response to future threats, and some vaccine programs. So I don't begrudge any of those other line items their money. I think most of us who are working in this area feel very strongly that all this stuff should be funded. So the point is not to say that they should get less, but I think in context, this whole Netson project starts to look quite cheap. The other thing to think about is to compare it to the existing NDMS model. So it's estimated that to deploy a national disaster medical system boots-on-the-ground team, so a medical response team that goes to the point of care, costs around $250,000 to as much as $1 million per week. And so if you think about that, that's around $1,500 an hour for each site, whereas we're talking about $300 an hour for Netson. If you even just covered the 36 critical care access hospitals that we covered with Netson, that would be about $53,000 per hour. If you extrapolate that to the over 1,300 critical access hospitals that exist in the U.S., obviously that's billions of dollars. So I think it's important to think about what if we could scale up. So Netson treated about nine patients per site over an average of 61 days per site. So that's pretty tiny little numbers, right, 0.15 patients per day per site. But with the bandwidth that we had available, we could have actually covered most of the critical access hospitals because we had enough people in place to do this. And at that scale, that would be about 200 patients a day. It's estimated that that would potentially increase the kind of bed capacity, ICU bed capacity of the U.S. around 2%, which is not significant. Even as a limited pilot for a short amount of time, we were able to monitor 30 patients at home who didn't end up requiring admission. Only five of those patients ultimately ended up coming into the hospital, and three of them went back home after less than 48 hours. So again, these are tiny little numbers and don't intend to pretend that that's an outcome, but I think it just shows you the potential. So the pilot itself, you could argue, was expensive, but expanded care at scale would not be. And we think we had a signal, at least, that we could reduce transfers, reduce admissions, and multiply the workforce. Very similar to the arguments that have been made for the general power of telecritical care. So again, I said, if NETSAN was available to all critical access hospitals in the U.S., you could theoretically provide a 2% increase in critical care beds. And the NDMS model, while, again, I'm not arguing for replacement. I think that's obviously a crucial and important service. But if you had a telecritical care wing or deployment model, you could reach places that are functionally or technically not really reachable by our current system. So what that means is that I think we have a significant opportunity to improve access to care and provide more equitable care, and I think we can show a little bit that we already did that. So the CDC has measures of social vulnerability that you can look at. They have an interactive map on the CDC ATSDR site. And basically, every county in the U.S. is scored for the level of social vulnerability, and that includes things like economic status, housing costs, education levels, age, disability rates, all kinds of stuff, right? So it's a pretty broad measure of how counties are situated in terms of the overall level of resources and the social and health vulnerabilities and stresses in those communities. If you look at the map, you can see that especially the South, and I think a lot of this is also rural, is more vulnerable. So for all sites that NETSAN took care of, the median SVI was—SVI is basically just a scaled score. It's probably just sort of a ranked percentile, but the SVI was around .4694. So that in their scale system is around middle, you know, moderate vulnerability. But if you look at—because of the way NETSAN played out, we deployed to some states, specifically Vermont, Minnesota, and Wisconsin, which actually overall as states have very low social vulnerability indexes, so good for them, but I think a little bit—probably a combination of factors that are, you know, that have to do with demographics and state budgets and priorities and all kinds of things. But in any case, if you remove those three states, then the SVI for the NETSAN deployments was .6646, which is moderate to high vulnerability, and 15 of our deployments, so, you know, almost half were in highly vulnerable areas, including a few that scored in the—literally the highest social vulnerability that you can have in the U.S. So again, these locations, I think, are very hard to reach, and I think we were able to reach some places that otherwise wouldn't have been able to have these services at all. So then the last thing to say is I think we learned a lot of lessons that hopefully can be applied, and, you know, it's obviously—if I spend lessons learned as a reason we were successful, that's maybe a little bit, whatever, disingenuous. But I think that this was of great value to us going forward. So just—some of you may have heard this if you were at my talk the other day, but one of the deployments that we did was the state of Vermont reached out to NETSAN through the Regional Disaster Health Response System. Vermont is in Region 1, which is the New England area, and they asked for help from the Regional Disaster Health Response System. And Region 1 had already been working with us on some of our NETSAN projects and planning, and so they said, hey, well, why don't you guys request help from NETSAN? They had the full support of the Vermont Department of Health and the Vermont Health and Hospital Administration to go ahead with kind of a statewide on-demand deployment. And so we really felt like this was an optimal scenario. You know, Vermont is a small state, relatively small population, relatively small number of hospitals. We had the program up and ready to go, and we had, you know, as much as you could, coordinated buy-in from state and local leadership, including, you know, some of the hospital—each hospital basically involved. So we deployed, and unfortunately, the thing that we learned was that it still took us forever. The fastest that we were able to deploy in one of those hospitals was seven days, and the median time from their request to deployment was 27 days. So, you know, Colonel Pamplin alluded to this, but basically the surge was sort of subsiding by the time we got up and running, so we kind of missed our window. And I think there's a couple things to be said about this. The first is that it's kind of hard to sort out exactly why we were so slow. I think it varied a little bit by hospital. Some of the hospitals just hadn't really gone through this emergency credentialing process before. Some of them, even though everybody said yes, did still have some concerns about sort of making sure that the liability issues were taken care of, that, you know, even though we're happy with this idea and theory to really move forward and green light, it took a few days. So the lesson, I think, there is that these things work, and they can—you know, our fastest deployment in all of Netsan was two hours, right? So we had a request, and we're up and running within two hours at one site. And so obviously that's not realistic, but that's possible. And I think the lesson is that if these systems are in place and somebody's invested in them ahead of time and knows they're there and knows how to use them, we could deploy in a remarkably quick amount of time. So, you know, I think going back to this, I think, you know, how do you demonstrate that this was valuable? I think, you know, we were ready fast. We did—we were able to live up to some of the kind of promises, right? We had patients online quickly. We had clinicians ready. We had a lot of support from clinicians right away. We did log thousands of video messages and communications. We did fill in some gaps. We had one case where we actually diagnosed pneumothorax virtually when nobody else was around and were able to provide service. We did cover nights and weekends and provide some kind of documented, you know, burnout reduction for some of these places. We monitored places at home—I mean patients at home, sorry. We reduced hospital admissions in that cohort that I already talked about. And we actually had one situation where Netson stayed live when the local hospital's IT system went out and went down. So those are obviously anecdotal, but I think they're real potential benefits. We did get a little bit faster as we went, so this just compares from sort of earlier on in the time frame to later. Our days from request to go live did go down, even though it never went to where we wanted it. And I think, you know, probably as important as anything is that we laid a foundation that has continued, I think, to generate benefit. We built a real strong community of people around the country, so there's been, you know, consistent support from thought leaders and experts and practitioners of telecritical care who have continued to show up. They're still showing up and asking us kind of how they can help and what's next for this program. And this has led to some specific spinoff programs. There's been an effort to do some ECMO regionalization in Texas using some network Netson platform ideas. There have been real-world deployments in Ukraine by SCCM-supported projects that kind of, at least the teams, assembled during the Netson effort. And I think we've established a clear model for multidisciplinary telepresence. So there's efforts going on in burn care and sort of remote palliative care and monitoring vaccine clinics and all kinds of other things. And I think all of us have recognized that it's, if we develop the platform, it's got a wide range of uses well beyond critical care. We did learn a little bit about successful and unsuccessful deployments. So successful deployments are the most successful if there's an identified need that's recognized by everybody. If you have effective leadership that really engages the key stakeholders in the places you're trying to reach, you have to have IT support. This stuff, even though we have a sort of ready-to-go system, it still requires quite a bit of work and people who understand things like networks and IT security. Privileging and credentialing obviously really require, are much easier if you have an experienced team that knows what they're doing and has gone through this before. We recognize that in some cases there were kind of misaligned ideas about what we were offering or what was available. And so you have to try to sort of figure out how to make sure that your service you can provide is aligned with what people are hoping for. There were a couple cases where the administrative apparatus of a hospital or health system said yes and the clinicians kind of said no. So it really, you really need buy-in from all levels. And then I think there's some areas of uncertainty that we didn't answer that still are worth some thinking about. One is we deployed both proactive and reactive models. One of the models used kind of a nurse navigator to start out and route and triage. The other model was direct to expert and we don't have enough data to say much that's meaningful about which one of those was better, but it's an interesting thing. Still a lot of things about liability, about indemnification of providers, about how orders will be placed and who's sort of responsible for care are unexamined or still open to a lot of discussion. And then kind of we lived basically thrived on volunteerism during COVID and I think that's actually also what's happened for example in the Ukraine deployment is that people are willing to put their time and effort into things when they think it's important. But obviously that's probably not a sustainable all hazards kind of approach and so we still have a lot of uncertainty about how compensation for this care can happen. I'll just leave you with this. You can just read these, but I think we had quite a few users of the service who thanked us for it and described the benefits we provided and obviously it's hard to put a number on any one of these things, but I do think we made a difference for a lot of people. Thank you.

telecritical care

rural healthcare

COVID-19 support

critical care access

cost-effective healthcare

telehealth initiatives