 Great now we get to talk about economics and When I gave a lecture in our public health genetics course the constant comment My favorite comment was it was nice to hear from the dark side so here we go and they often save economics for last and In some ways, I think it's because at the end of the day ultimately We all need to make decisions about whether things are a good value or not So I want to tell you a little bit about what's been happening in Caesar, but try to focus a little bit more on what the incredible opportunities are in front of us for future study First I just want to talk a little bit about some terms here We talked about healthcare resource utilization in some ways. That's codename for cost So how much healthcare are people using and we can put a price on that later and figure out what the costs are But some of the main points I think are that just because something is expensive doesn't mean It's not good value just because it's cheap doesn't mean it's cost effective And what we're really looking for in this field is to get the most health benefit that we can for the amount of money that We spend In the field the technical field of health economics. We tend to measure outcomes Using this metric called a quality quality adjusted life here You can think of it as as a year of perfect health and it's a good thing you want more qualities and We calculate something called an incremental cost effectiveness ratio So you might hear me throw around throw around some of those terms But of course payers they care a lot about costs and that's something that we need to pay attention to and that's why We're measuring this healthcare resource utilization a lot of the studies within Caesar Ultimately what we want to do is improve patient outcomes and we want to do that in a cost effective manner Which means the amount of money we're spending is Reasonable compared to other things that we buy in health care or that were cost savings It doesn't necessarily mean that it's cost savings. So To sum it all up when we talk about health economics, we're not just talking about cost and in fact We're more of more often focusing on effectiveness And so I'm really glad that the the session on clinical utility proceeded this one because that really lays the foundation for cost utility Now these slides here just give you Kind of just a sense of what's going on in Caesar in some of the sites and the type of health care Utilization data that that's being collected and you can see that there's you know, there's a lot of different things you can look at and there's a lot of different ways you can categorize these outcomes and It ranges everything from just number of visits what medications people are taking To questions about health insurance and maybe even life insurance And you can see that there's a lot of diversity across the different sites And also there's a lot of different ways Methods for measuring this information Probably in the Caesar consortium leaning a little bit toward patient surveys to find out what kind of resources are being used But also some use of electronic medical records, which can be quite powerful So ultimately what is our goal here? It is to help health care systems and pairs make more informed coverage and reimbursement decisions for clinical sequencing and In order to do that I think we've heard from some of the questions and some of the speakers about challenges they've run into with reimbursement in the Northwest That some decisions that affected us in Seattle were things such as any Gene panel is investigational and therefore will not be covered So I think sometimes pairs are reacting to a lot of change and a lot of uncertainty Sometimes strong marketing push from companies and are coming out with policies Like that and our goal here is really to help them make better decisions And in order to do that we're going to need to collect some data So first I want to talk about just a few of the challenges and then the opportunities that I see for Caesar too The first one and this is really a tough one You know people are always asking what evidence do decision-makers need and then they'll invite the pairs and Pairs will say well, we do like randomized controlled trials and then everyone says oh, they only want randomized controlled trials Well, you know none of that's true. It's a very very hard question It's very difficult to bring someone in and I think Naomi can attest this and say what evidence do we need for a whole Exome sequencing or whole genome sequencing Well, you know, I don't know that's that's a very broad question You can start to ask more specific questions, but then you're asking that person to become an expert in that area So it isn't an important challenge and it's something that I'll come back to a bit and I think Pat will respond to you also I think the other issue really is that there's so many different things you can do with clinical sequencing That you know, there isn't just some generic well is is whole genome sequencing cost-effective well It depends it's like our drugs cost-effective well It depends so you have to be very thoughtful about well What exactly are you talking about doing and what are you going to use it for and then who are you going to use it? But that also presents the challenge that then there's lots of different things that you could be looking at So that's that that's something we'll have to come to terms with And then also obviously I think we need information about all aspects of the delivery of the tests not just the cost of the test and I know that in particular two sites Harvard and Kaiser are collecting very carefully measured quantitative data about How much time is required by their genetics providers and then you know a lot of the Cancer sites are looking at the impact on treatment decisions. So these are the things that I'm that will need to put into the mix I think another issue that really comes up and has been mentioned a couple of times is comparative data or a comparative effectiveness And it's something that I think is really it's quite important It doesn't mean we always have to have it doesn't mean we always have to have randomized control trials But I think that To talk to payers you really need to talk about comparative data. What's your next best? Alternative and what's your opportunity cost? The last lastly, I think we're all where you know sample size is really a key issue Just in general looking at health economics costs health care resource utilization for anything It's very challenging to collect enough data in that area And you know potentially you could quickly find yourself needing studies in the tens of thousands even a hundred thousand people To get definitive health economics answers and you know it for the most part That's not what we do in the field most the time in the field We take data from a randomized controlled trial that's powered for a clinical outcome Maybe a surrogate outcome and then we do our best to estimate the economic outcomes, but this is an important challenge So opportunities for a season are moving forward, and I really think they're tremendous the first one really I think is Doing our best and figuring out ways to have conversations with payers and to get some input from people out there making decisions And and and enable them to tell us Something about what it is we're doing Around the time that we're trying to design and implement these studies and identify our outcomes It is very challenging I think we need to be somewhat indication specific and It's important to talk about types of evidence rather than getting obsessed with what exact level of evidence is needed In order for you to say yes to this technology. That's just it's very hard to do and it doesn't happen in other areas in health care The other is that You know, I think Katrina showed you that the heterogeneity of clinical indications and approaches across Caesar Which I I agree has been a great strength because we've been able to learn a lot from that But there's also kind of pools of similar indications or uses of clinical sequencing And I think we need to figure out how to how to best align Projects in those sub areas so that we can pool data within those areas Obviously thinking I think you know the three major categories would be diagnosis treatment and screening and then particularly within Screening there's this subset of incidental findings Which could be viewed as opportunistic screening and that's something that could apply across all sites and we've already Started efforts to do that. I think maybe tomorrow Jonathan Berg is going to be presenting Some information about the incidental findings across the entire Caesar Consortium and then lastly I really enjoyed The discussion about the families and getting involved with them I think actually from a health economics perspective I think what happens within families will be one of the single most important drivers for the value of precision medicine And I think it's something we really need to give a lot of thought to and then this other discussion about engagement with patients Was great because think about engaging families. It's not easy either right got to figure out approaches to do that In terms of data collection, I think that just briefly mentioning study design again Trying to be comparative. We're feasible trying to have studies that are actually powered on some kind of outcome Okay, we're not always going to power on survival But we should have some kind of clinical outcome that these studies are powered to as feasible I think we've seen a very nice, you know laid out Robert laid out five trials that have been done and are ongoing right now and those are all small kind of phase one I think it's time to think about moving to phase two in terms of in terms of the kinds of studies that we're doing and moving You know finding our initial signals and trying to confirm those and using a lot of the tools that we're developing here in this study In this consortium and some of those tools Really, I think relate to data collection. I think again this it's patient and family-centered cost issue the cost of You know the diet the the odyssey of trying to find a diagnosis for a patient I don't think has been well docked enough what Documentation has gone into that. I think that there also needs to be some communication with payers about what does that really mean and You know, what's their level of engagement and willing to pay? To end the diagnostic odyssey we could probably make a more efficient use of EMRs within Caesar I think that's something we need to think about and then I think this last point Not to get too technical, but as I said, we're never gonna have studies I think that are powered for economic outcomes I think we need to start thinking about developing patient reported health economic outcomes where we can ask patients What actions did you take because of your test result? Now there's some obvious limitations with that, but I think that potentially we could develop some tools that would really Enable us to find the signal and the noise there with the health care resource utilization And then lastly, I'll just mention this general area of policy models. These are quantitative policy models cost-effectiveness models These are calm. These are used throughout health care to try to get a better understanding of the boundaries of the benefits and harms costs and ultimately the economic value of interventions and and even when you don't have a lot of data that can be quite useful and You know one study by Carlos Gallego was mentioned looking at inherited colorectal cancer risk These model, you know, there's been some work within the Caesar one to develop some of these models But they're just sitting there kind of waiting for more data And I think that not only further development of these models But generating data and Caesar to inform those models and then having that interaction and conversation with payers will be quite fruitful So just in summary, I think there's for the for the consortium. I think there's some great opportunities Just to go over the go over that my key points again pair and decision-maker input. I think will be Really important but challenging Developing validating and implementing some common economic measures across the consortium and not just Caesar But also emerge and ignite for instance the the working groups are starting to have conversations across those consortia So I think there's great opportunity there and then again the data pooling within indications and More broadly as feasible and then lastly some of these kind of policy frameworks to in a way fill the gaps Well, we're not going to be able to have these huge randomized trials for for every indication so that's it and If we want to take questions or allow Pat to respond If there's one or two specific questions, and then we'll have the more general discussion So Dave that was really nice. I was just wondering Do you have any thoughts about the prior discussion with regard to diagnosis one obvious economic brooch would be you know Money saved by ending the diagnostic odyssey, but is that really the only way to address that? I think most of us as practitioners take it as almost axiomatic that making a diagnosis as a benefit You know insurers don't pay much attention to what we've considered to be axiomatic Yeah, yeah, I think there's that there's the oh we'll save money because we're not searching anymore But that inherent value that it has to individuals that's real And there are methods that people have used and are actually are using within Caesar to put a monetary value on On that for patients the challenge is kind of as a society as a health care systems Is that something we pay for or not? And I think there's some really nice work that could be done there that you know Is a broader social issue even more than economic Build on that comment for a second one of the Corresponding struggles that has gone on for a long time as many people in the room probably come from academic medical centers One of the challenges academic medical centers have is in any way demonstrating that they have better quality than other centers Because if you look at many of the kind of standard things delivering mammograms to everyone actually it doesn't necessarily look better And so there's a corresponding effort going on now to try to ask the question. Can we actually look at the? Quality that may come from a better diagnostic Center than a non Than a center that has less let's say tools or ability to do that So it'd be interesting to see if that can end up informing this discussion also because it's kind of a corresponding Effort which really relates to why do people come and look for that diagnosis at a tertiary center Okay, great. So then Patricia is going to give her comments and then we'll have a general discussion