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Dan Housman: Hi everyone. I’m here with Jeff Weisinger from PointClickCare and we’re here today talking about COVID-19 and PointClickCare’s Real World Data capabilities. Let’s start by asking Jeff a little bit about his role at PointClickCare. I know he leads the RWE Lighthouse initiative and he can tell us a bit about how that came about.

Jeff Wessinger: Thanks, Dan. Great to be here. Yeah, my name is Jeff Wessinger and I’m with PointClickCare. As Dan said, I lead the Lighthouse initiative, which is an initiative to take the EHR data from our database focused on long term healthcare and make that data available to life sciences companies, for the purpose of Real World Evidence research. PointClickCare has historically been an EMR business, but oddly enough, in the 25 years that they’ve been running, had not considered the idea of taking their business beyond providers in hospital systems and their customers to life sciences. Over the last couple of years, we’ve developed a strategy to get the appropriate BAAs in place with our customers to do right by them. And then to put this dataset together, curated so that it would be relevant for research. My role is to head up that commercial endeavor for PCC.

Dan: So maybe we’ll step back and can you give us a feel for what PointClickCare is and what clinicians use it for?

Jeff: As you know PointClickCare is a privately-owned Canadian company. They got into the SaaS software game very early and they created both a SaaS offering and an associated pricing model that work very well for long term healthcare. So if you know anything about industry and skilled nursing homes, specifically, most of what they buy is on a per resident day basis. And so, to align with that buying model, PointClickCare created a pricing option for their software on a per resident day basis, meaning that for pennies per resident day, they equipped themselves with everything they needed from a software perspective. Effectively it becomes the ERP for their facility. Everything from billing, trust management, and care management. In short, everything that the facility needs in order to operate and take care of their patients. In the last 25 years, by providing this kind of value, they’ve managed to capture about 70% plus of the skilled nursing facility market, 60% of the assisted living market and have recently entered into the home care market which is an emerging market. There are not many players there yet, but they intend to be a leader in that space as well. So as I said, because of that robust dataset, and the types of patients that are in it, the idea to create a novel offering from the EMR patient data is where Lighthouse comes in. And we feel that that data fills a critical gap between the ambulatory care EMRs and the acute care EMRs that hasn’t been served in the market before. So now we can track these patients longitudinally across a longer continuum. This is where PCC intends to enter this patient data space.

Dan: As we all know, COVID-19 is probably the dominant issue of our times. Tell us more about what’s in the dataset you have around COVID-19 and why it might be enriched in a different way than other datasets?

Jeff: Well it’s a completely unique dataset to what you would see in acute care or ambulatory care. As it relates to COVID, you might consider that long term care is the epicenter, at least in the US for this disease and if it’s not the epicenter, it’s definitely been disproportionately impacted versus the general population. So we have a very high risk population in general, and then we have a high density environment. From a comorbidities perspective we have an average of eight comorbidities for any of these patients. So you see it’s definitely no coincidence that we’ve had a significant impact. The database as of a couple of days ago had 135,000 patients that have been diagnosed with COVID-19. And we have at least one case in each of the 4,300+ facilities that we serve so far. So a very high percentage, which is not good, obviously, from an industry or facility perspective, but tends to be very good for anybody that’s looking to research this type of patient. We are working closely with a number of organizations to do specific research in this important area and hopefully we can do some good.

Dan: So did I catch it correctly? You said 135 or 135,000.

Jeff: 135,000 patients and 4,300 facilities that have at least one patient.

Dan: Oh, that’s quite a lot of data. What sort of unique information is available in that dataset?

Jeff: Well as most of the EMRs we have a very detailed and extensive set of patient records. The unique part about long term care databases is that we have longer stays than would generally be there for acute care. So you see, we have therapy and treatment information that includes very detailed care plans, some that aren’t necessarily “go for surgery”, but “over a longer period of time, this is how we’re going to care for the patient”. Now this includes not just medication administration, but other daily activities that care professionals would undertake, and it’s very specific and an outline for them; they very much follow a plan for each patient. So we have that. In addition to this we have very detailed outcomes, at very small intervals, almost down to the shift level, which means that you can measure vitals over time smaller than days. You can measure incidents that happen with these residents. Other specific assessments, like a typical one in long term care is an “activities for daily living score”, that measures the ability for the resident to conduct their own daily activities like ambulating, using the bathroom or being able to dress themselves. These kinds of scores are typical. Other detailed assessments like cognitive screeners and other screening tools are all available as well. We tend to have a very detailed level of therapy data and a much more detailed level of outcomes that can be measured. And again, because of the long term nature of the stays you can study patients on a longer scale longitudinally than typically available.

Dan: You’ve been working with some groups like Mayo Clinic and CDC. Tell me more about what groups are already trying to do with the anonymized data.

Jeff: Yes, many of groups have approached us for this data, specifically for COVID patients. A study by the Mayo Clinic is looking to understanding post ICU outcomes e.g. after they leave the hospital, what type of outcomes are they dealing with (post-COVID and being in that intensive environment). So this is a big study that we’re helping with. The CDC and then more broadly, CMS and HHS are, are looking to understand disease progression. They’re looking at mortality rates within nursing homes and are really looking to understand, in general, how it’s impacting these homes and how they might create guidelines to better aid these organizations down the road, and maybe even apply some legislation based on that research. So we are providing data to those organizations. Other Life Sciences organizations have also inquired and some are already using the data set with the COVID diagnosis as an extra parameter. Our goal is to help as many of these organizations as we can to better understand this disease and how to deal with it.

Dan: And what have you seen out there that is exciting in terms of Real World studies and research around COVID-19 beyond what you’re already doing?

Jeff: The obvious one is if you look at what pharma companies want to do with their existing therapies. The have products already in line and available in the market: what impact are they having on the disease? So if there are patients that are already on either your vaccine or your therapy, maybe it’s not indicated, obviously for COVID, but to see if there are any correlations. So if you do have a correlation or a better mortality rate, like we saw, potentially with the BCG vaccine or hydroxychloroquine, where those are two examples of some that have been studied extensively, but really anybody that has a drug that’s out there that we can look at and see if we get a change in outcomes that’s significant. You know, from the baseline. I think that’s the interesting and the most obvious use case that we’re seeing.

Dan: I’m curious, do you have a way to determine mortality? Or is that a tricky variable? Because I know that’s hard in a lot of datasets.

Jeff: We have it and I think in terms of providing it, we can certainly provide it to government organizations like HHS and CDC. I know we can provide it in aggregate form and specifically for studies like this, that’s how it would be provided. We definitely have the attribute. But depending on expert opinion we may not be able to provide it longitudinally at a specific patient level.

Dan: Great. You’ve been planning on this for a while and what else do you envision groups doing with the PointClickCare data beyond what you’ve seen so far?

Jeff: I think because of the demographic you can look at diseases that disproportionately impact this population as areas that we would look at. At the top of the list is neurologic disorders like Parkinson’s or Alzheimer’s, or more broadly, dementia in general. I think those are areas that we have a very robust set of patients for that could help with that research. So that one seems obvious but we are not limited to those. There’s also cardiology, respiratory, diabetes, immunology, and even some rare diseases that impact this population. I think these would be areas that we definitely see interest in and that we have customers using it for. The second thing is, because we’re not just a data set, PointClickCare is first of all, foremost an EHR.

So prospective studies, and the ability to use our custom assessments and forms for putting out screening tools and putting out specific care plans by disease. I think that’s an area where pharma companies can create their own datasets, right? So they can at once give back by providing the screener, the therapy, description and what makes the most sense and then also get back the data from that specific assessment which will help them enhance in the future. We’re already doing that with a couple of customers like Acadia with their PDP screening tool, and we look forward to doing that with many other pharma companies in the future. And then lastly where we’re just starting to look at are opportunities for clinical trial recruitment. Obviously there’s a complicating factor in terms of privacy and notifying the patient that there’s a clinical trial, but I think we have some really good ideas about how we can do that notification and still respect that. And I think there’s a tremendous opportunity to get patients involved early on with some of the new research that’s happening. These are three areas that we look forward to participating in moving forward.

Dan: Great. Well, Jeff, it’s been excellent having you on. Now we’re looking forward here at Graticule to partnering with PointClickCare. I think there’s lots opportunity especially in the short term for COVID, but also in the long term these sound like great concepts, so thank you for taking the time with us today.

Jeff: All right. Thanks for having me.

Dan: Catch you soon. Bye.