 Okay. Well, welcome back, everybody, and we have Mark Williams slides up to introduce the eMERGE presentation on EMR integration and genomic medicine implementation. Mark, it's yours. Thank you, Dan. At this point, batting seventh in the lineup, I think we're going to experience what Yogi Berra described as deja vu all over again. I won't read the title of our group because it would take my ten minutes. I was supposed to say we were asked to cover a lot of different subjects, so what you're going to see is a very highly selected group of activities that have been ongoing. So the EMR integration group, which I co-chair with Justin Stern, has been primarily focused, as you've heard, on pharmacogenomic representation and clinical decision support. And this is a list of the different variants that are being returned across the sites. Before, so I'm not going to go through it. But we also, as you've heard, do have some non-PGX initiatives that, again, I'll just project here briefly, and you can take a look at the different things that are being done. And all of these are, to one degree or another, using the electronic health record as a way to provide appropriate notification and support to clinicians to utilize the information. One of the things that we referenced earlier was the EMRGE infobutton project. And there are two objectives to this, and I think Casey Overby, who is leading this project along with Luke Rasmussen for their slides, objective one is to develop a new information resource based on EMRGE 2 and PGX scenarios. So infobutons are a way to use the context of where a provider is in the electronic health record to essentially pre-ask the question that the provider is likely to have. And then, with one click, allow access to a resource that specifically addresses that question. So, and there's been formative research on this that looks at the ontology of clinical questions, and you can map this pretty well. So for PGX, it's actually pretty easy, because if you're in a drug order entry system and you click on a drug to order, then we can pretty well decide the questions that you're going to have about that project and a medication. And specifically, if we're interested in pharmacogenomics, we can present the relevant information about pharmacogenomics very quickly. So this talks about the different parts of this objective that we're involved in. This is ongoing. So we've completed a collection of scenarios and have designed a template where we're trying to do is to use a standardized format for this information sheet that can be used across the site. We're in the process of having our content developers complete the eMERGE template, and then we're going to be using that to engage end users and evaluate the resource. The second objective is actually then to implement infobutons within the electronic health records. Again, you can see the status of this at the present time. One of the reasons that infobutons are a good target is that they are required by meaningful use to be included, and there's an infobuton standard that exists. And so if we can actually develop infobutons at work, this is a way that we could implement this information within any certified electronic health record. And we've been collaborating with the University of Utah, particularly Ken Kawamoto and his group, who leads the open infobuton system. So this is something that's ongoing, and we hope that this will be the first example of something that comes out of eMERGE in the electronic health record space that could be truly generalizable with little, if any, local customization. But it remains to be seen. And Ken just messaged me. It's actually a Guillermet Delphiol who's leading open infobuton. And so sorry about that, Guillermet, even though he's not on the phone. The challenges, we've heard this one, implementation of research informatics into the clinical EHR system is really hard. I decided to illustrate this by taking a photograph. I was taking it at the end of a recent meeting here at Geisinger where I presented some of our implementation ideas to the clinical informatics group. There were no serious injuries or fatalities, but it was a close thing. One successful implementation equals one successful implementation, even at the same site. I think there's been a certain amount of tension and frustration that's been experienced given that a lot of other eMERGE activities are moving forward much faster than the glacial pace that EHRI is moving forward. We are working now on looking at some network outcomes related to EHR integration, but almost all of these are process outcomes. Even though we all know we would like to have clinical outcomes that we can look at, and there are some sites that have developed some ability to look at clinical outcomes. So we heard this from Justin earlier, the Clayton aphorism, each system is built three times. First time to see can it be built, the second time to determine how it should be built, and the third to actually build it. So our status using the Clayton-Steron algorithm here is that we really, most of what we're doing here in phase two relates to Clayton first stage with some hope of learning enough to proceed with stage two and maybe at some individual sites to actually proceed into stage two. And I think the Predict program at Vanderbilt is an example of EHR implementation that is actually into stage three. But we don't have anything system-wide at eMERGE that we can point to at that level of maturity. As has been referenced previously, the EHRI group works closely with two other eMERGE workgroups, the return of results and CERC, which we've already heard from. There's also an informatics group associated with the clinical sequencing exploratory research efforts, which are funded through the NHGRI as well. And we have had joint meetings between our two informatics groups and have agreed to produce a white paper on where in the EHR this information should appear. So future direction and opportunities, we think there's a research agenda around actionable clinical decision support. So what are the optimum ways to centralize and distribute standardized evidence-based clinical decision support? I referenced the clinical decision support consortium earlier. This is work that they had done through their ARC-funded grant. To put it in perspective, and I don't think Blackford would get horribly angry with me if I said this, but they had six years of funding with literally a who's who of the top clinical informatics groups in the country. And at the end of that, they had one clinical decision support rule that could have been said to meet that first bullet. So this is really challenging, but again, they've decided to sign up for a second go-around. And as mentioned, they are very interested in engaging with us. We've had some communication with them at a previous workgroup session at an e-merge meeting, and we will look to do more of that going forward. We also want to determine how accurate, and there are different ways to define accuracy, which I'm not going to go into now, but how accurate does clinical decision support work across genomic medicine use cases? In other words, are there certain standardized ways of doing clinical decision support that are more robust and are less likely to need customization? Because when we talk about implementation, there are really two issues that need to be measured. One is fidelity. Does it work the same at site B as it did at site A? And how much difference is there? And then customizability, which is how much customization does it take at site B to make it work like at site A? And those are critical issues to study. And then ultimately, we would want to move beyond process outcomes to relevant clinical outcomes for selected genomic medicine use cases. We want to be able to study the ability to extract real-time patient-level data from transactional electronic health records to fire clinical decision support for selected genomic medicine use cases. So the common example that we've been using with PGX is you want to go to order a medication. You want to order Simvastatin. You click on the Simvastatin. The system recognizes that a pharmacogenomic test has been done. It looks for the result. And if the Star-5 allele of SLCO1B1 is presented, then the clinician would be notified in some way that perhaps a statin other than Simvastatin should be used because of the risk of statin-related muscle injury. But what we'd really like to move to is much more complex clinical context issues. An example that I use is it is now routine and pediatrics to screen for autism between 18 months and two years. If, for some reason or another, we had a whole genome or a whole exome on a patient and they did that screening test and it was screen positive for suspected autism, one could shortcut the diagnostic odyssey by immediately generating a query of all autism-related genes to say is there a known deleterious mutation in one of these genes that could potentially confirm the diagnosis and the specific cause of autism in an individual. So again, that's just sort of one example of a much more complex clinical context where you'd want something lurking the electronic health record to be able to fire and answer questions that clinicians may not know even need to be asked. And then ultimately to study how electronic health records, personal health records that are tethered to EHRs and patient portals can be used to enhance education of patients and providers and measure the comparative effectiveness of different approaches. And I think as we talked about in the prior discussion, it maybe extends beyond just education to who is best able to manage the results. There's been a sidebar conversation about the dangers of, you know, the consequences, if you will, of giving information to patients. But the patient is the only person that's the constant in the health care delivery system. So if we do a genome here at Geisinger on a patient and they go to see somebody at CHOP, they won't have that genome to utilize. Whereas the patient, if they had the genome, could potentially use it in some way, shape, or form. That remains to be studied. And that's the end of my presentation. So I'll turn control back over to Brandy.