Connectivity for Real-Time Diagnosis to Manage TB, HIV and COVID-19
On May 6, 2020, SystemOne was proud to be part of a Stop TB Partnership Virtual Innovation Spotlight. The Stop TB Partnership, founded in 2001, has a mission to serve every person who is vulnerable to TB, and to ensure that high-quality diagnosis, treatment, and care are available to all who need it. Presenting from SystemOne were Chris Macek, CEO, Brad Cunningham, COO, and Patty Moscibrodzki, Global Health Associate. The transcripted below has been condensed and edited for clarity.
Chris: Good afternoon everyone. My name is Chris Macek, CEO at SystemOne and I'm happy to have the chance to talk to you today about connectivity and how we view it at SystemOne. The title of the talk is Connectivity for Real-Time Diagnosis to Manage TB, HIV and COVID-19.
Chris: I’ll begin with a quick introduction of myself and SystemOne. Then we’ll go to a quick primer on what connectivity is. I'll explain something that we at SystemOne call diagnostic accountability, which is a way to view the health system from the lens of the diagnostic network. And we're going to end with a way to position a country's COVID-19 testing in the same way.
Chris: Okay, I just want to give a little bit of background, on myself and my company. I'm currently the CEO of SystemOne and I'm also one of the founders. We started SystemOne seven years ago. GxAlert was our first platform. Many of you may know or have heard of it being used in your countries. Over those seven years, we've connected about 45 countries with over 3500 labs, most of which use GeneXpert diagnostic instruments, and we have moved about 10 million TB results worldwide and counting. We have a fair bit of experience in low-income countries, a fair bit of experience with a number of different diagnostic devices and diseases, but I'll speak today primarily on our direct TB experience.
Chris: Okay, I want to give a quick overview of how we look at connectivity at SystemOne. The whole field has evolved over the past 5-7 years. This is to show you the way we see it right now; that connectivity is three components, basically three steps. The first step is connecting instruments that are typically in the labs. The second step is to report those diagnostic results from the instruments back to the clinics, to healthcare workers, and patients that have sent off those samples to the labs for testing. And then we have a third step that we call “to confirm or follow up.” That's basically accounting for the fact that the diagnosis was done in the lab, the test result was generated, and that result was reported back to the clinic, and finally, that something was done. I'd also like to give a little bit of context as to why connectivity is so necessary. One of the problems, in fact the basic problem that we're trying at SystemOne to solve with connectivity, is making the data digital, making it electronic, and therefore, most crucially, able to be transmitted almost instantaneously.
Chris: The other thing that we noticed is that typically when people are thinking about fighting TB or ending HIV or now with COVID, they think about it as a medical problem. And one of the things that we find is that most of the people--in the WHO, in the StopTBpartnership, all over the global health scene--most of them are doctors. They come up through the ranks and are trained as doctors and view the problems they face as a medical problem. But when you're trying to treat 10 million people with TB, or a million people in your country or an unknown number with COVID, it is as much of an information problem as it is a medical problem. When you're trying to deal with an infectious disease on a national and global level, if you don't deal with the information problem, you can't deal with the medical problem. Connectivity is one of the ways that we can solve that information problem.
Chris: I want to get into a little bit of the nuts and bolts of what we do at SystemOne. I mentioned three parts of connectivity. The first one was to connect the instruments. It's pretty simple, what we do is we take the instruments, say a GeneXpert in a lab or clinic, and you connect that instrument to the internet so that it can transmit to a server---a GxAlert server or Aspect server--to a place to receive that result, typically at the Ministry of Health in the capital of the country and it's also possible to have the server in the cloud. We can talk about which is more secure on a case-by-case basis, but the basic idea is that as the instruments are operating in real-time, when the test is completed those results can be immediately sent over the Internet to a server. And from there, we can take the next two steps to report and confirm or follow up. Frequently, if this is set up correctly, transmittal of results happens automatically as soon as the test is finished and before the lab tech can even print it out. It has been transmitted through the router or modem over the internet and to the server, and maybe already sent to the clinic or whoever else needs to see that data. esults move as fast as they are done on the machines: instantaneously.
Chris: In some cases, there's internet available to clinics, and machines are available in a hospital. However, typically, that's not the case where we end up installing some kind of modem with a sim card and we put a kind of VPN modem as opposed to a little $20 thumb drive. This is because this modem is hard ruggedized for the climates that we work in: dusty, hot, and humid places. By using a SIM card, we can also control the data limit. Because if you provide internet to a remote area, you have to make sure people aren't using it for Facebook and YouTube. You also need to limit which sites they can go to. Again, this is to secure the data, make sure it's only going to the places you want it to go. We typically put a hardened router in there. It's about 200 US dollars. It's expensive, but it comes up automatically with power if there's a power outage. You can remote into it from afar to troubleshoot and fix/support. Usually, we recommend the global sim but it's also possible to use a local sim. We often have an external antenna so that we ensure that there is a signal. And even in sites where there's only a weak 2G connection, we're still usually able to connect an instrument and get that data moving to our server.
Chris: Once you connect an instrument like that, it's kind of like turning on the lights. Connectivity basically provides transparency into the diagnostic network. And it shows us two kinds of data from the machines that transmitted it. The first is clinical data. So obviously, we get the results of the test, and often with that, there's a sample ID, a patient ID, something that identifies that results to the patient. Additionally, we often get other associated application data. In many countries, there are no unique IDs so we'll have the name of the patient, sometimes their address, sometimes their cell phone, sometimes we get the clinic where they received the treatment, sometimes the reason for the test.
Chris: The other thing we get is operational data, so we can see information about the machine; things like utilization, a number of tests run per day, and the number of days running per week or month. We can see service or repair issues of the machines and we can coordinate that. We can look at the cartridge inventory supply. We know that each test, for instance, takes one GeneXpert cartridge. So we know the total number of cartridges in each lab, we can just subtract one test and see what the supply is and when labs will be running out. We can also look at the errors and the performance of machines, and how they're doing. If the machine starts throwing errors every 10, 15, 20 percent of the time, there is a definite service and repair issue that needs to be addressed.
Chris: So I mentioned those three things: connect, report, and confirm or follow up. So if we had Aspect as our central platform in a country, the first thing we would do is connect those labs using those routers or modems we just talked about. We can connect a number of different instruments and this can be for different assay types. So EID or TB , we are starting to use the ultra cartridges and XDR cartridges. We also connect to different second-line testing, some Abbott’s and Roche’s for viral load, really for anything, any kind of diagnostic or test. After that, you connect that device and get the results to a central location, you need to report that data out. So some mechanism, whether it be our dedicated mobile app, SMS or email to get the results back out to the healthcare workers, back out to the clinics, back out to the patients.
Chris: One of the things that we look at when we work in a country is the turnaround time. We've seen turnaround times in GeneXpert labs, like upwards of a week, two weeks, sometimes even longer. HIV viral load central labs can take up to two months to get a test result. And again, in most of the countries, we see that there's very little visibility in getting those results back. There's some 10 to 20 percent that never ever make it back to the clinic for whatever reason. And a lot of times, there is a lot of unknown about what happened from the clinic side once they sent a sample out to be tested. You don't know when that result will get back. When we connect diagnostic machines in labs, we can send test results directly, in real-time, to clinics via SMS, email, or mobile apps. We can also send directly into different kinds of systems like LIMS systems, EMR, EHR, and DHIS2.
Chris: We'll talk more in detail about how we do confirmation of the treatment or follow up. So we get the results from labs then we send it to clinics or to electronic systems, and get a signal back that these individuals have been placed on treatment. And then based on that, we can look at what percentage of the test results, from the point of view of the diagnostic network, that actually had actions. So for instance, with a high viral load result, has there been adherence counselling or second or third-line drugs, for TB, if it's a positive TB test, has the patient started a treatment? If it's a RIF-resistant test, are they on appropriate treatment? These are the kinds of things you can look at and measure, either at the national level, state or provincial level, district level, individual labs or individual clinics with Aspect. Stratified by children and adults, men and women, different groups. Again, depending on what you have in your patient data.
I mentioned reporting and we originally were using SMS and email to report the results back to clinics and we can still do that. But we have since developed an Android app we call Aspect Reporter. This allows us to automatically send the results in a more structured and standardized form. When a person in a clinic receives a diagnostic result, they can verify the clinical response and indicate what treatment the patient started on and/or eventually stopped. This enables a sort of confirmation or accountability of treatment.The app is designed to be secure, can be used online or offline for intermittent internet availability and that makes it easy to distribute and can be found in Google and App Store.
Chris: I want to talk in the last couple of minutes of my presentation about what I think the real value of connectivity is: Dealing with the problem of loss to followup. This is pre-treatment loss to follow up that I’m talking about. Here are a couple of studies that were done over the past 10 years in a few different countries. They looked at a number of people that had a confirmed diagnosis, but never made it to treatment. Maybe in your country, there were 50,000 GeneXpert confirmed TB cases. But, in that same period, maybe there are only 35,000 people on the treatment list. This is a typical differential and a problem that varies by country, but we’ve seen that all countries seem to have some significant share of this loss to followup. And again, because many of these countries have no unique patient ID there's no way for a computer to reconcile data easily. So one of the things connectivity allows is a way to tackle this problem, to look through the lens of the diagnostic network. It's sort of like, over on the left here, I can see from the diagnostic lab network, how many people are being positively diagnosed, and this could be for TB, high viral load, this could be COVID, whatever it is, and we can see those people who, after getting diagnosed, still have to make it over to the treatment side. This is the is loss to followup group. It’s almost like they have to make it over this bridge, this link from the lab to the clinic, and how do you ensure this link happens? Typically, 10, 20, 30 percent of people are sort of falling off of the bridge here, through the cracks, as loss to followup. One of the things that's possible by looking at this problem from the diagnostic network which we call diagnostic accountability is we can keep track of all of the people that were diagnosed and confirm that they had some appropriate followup. The way our system does that is we allow the country to define how they want to confirm follow-up because there are different criteria for what they consider as confirmed. In some countries, it might be if the result arrives at the clinic and the DOTS officer confirms receipt.
Chris: Another country, they might want to indicate that not only has the clinic received the result, but there is also confirmation of treatment. They may want to know when they started the treatment, or what the treatment was, and we can make those kinds of options available at the clinic level when we're showing them the results. I mentioned that it's very difficult, perhaps impossible to reconcile these two databases due to the lack of unique patient ID’s. That's true at a national level and at a computing level. However, it's not really true at the local level. At a local clinic, maybe they only see 10, 15, 20, 100 patients a week. Just using the name- if I sent a test result out last week or two weeks ago, and I get a result back and it has the name and I look at my register and I see the age or whatever confirms it, a local DOTS officer can figure out whose test results I'm referring to. So when we give those local officers these results, let them be the ones to identify the person referred to in the results because of that human connection between diagnosis, the lab result and the patient on treatment. There's sort of a bridge that can connect those two. It allows us to make that connection and measurement of loss to followup. And so we know all of the positive diagnoses that have been confirmed and followed-up and we also know the ones that haven't been. Then we can keep prompting in our app for the contact worker to continue to follow up until they confirm everybody knows the appropriate diagnosis and action taken. This could go for COVID. This could go for high viral loads, pretty much anything.
Chris: Okay, I'm gonna pause there. I know there are probably some questions about that and I want to leave a lot of time for some questions and discussion. I'm going to turn it over to Patty at this point to talk a little bit about what we've done to extend our products for COVID testing.
Patty: Thanks, Chris. So, the question right now with the current COVID-19 pandemic is how to leverage these existing technologies that we have to support the continued essential testing for people affected with TB or HIV and other diseases and maximize the ability to jointly test for COVID-19. SystemOne has developed a compatible module to collect COVID-19 testing data. Both on our platform dashboard and our mobile application, and it is compatible with Cepheid's GeneXperts cartridges, as well as other rapid-point tests for COVID, including Abbottm2000 and others.
Patty: We share the valid concerns of potential diversion of resources from TB testing to the current urgent COVID-19 testing. So, SystemOne data scientists undertook an analysis to understand current utilization rates of GeneXperts connected to GxAlert or Aspect to see what this increased requirement for testing will mean for a lot of countries. For this analysis, in particular, we used data from 618 GeneXperts across eight countries. This analysis is also up on the website in case people are interested in looking a little bit further into these graphs. But the assumption that we used was that a laboratory can run about three tests per module per day, over 21 working days. We calculated that an instrument's yearly utilization rate given that the number of tests run per year and then divided by the theoretical maximum number of tests an instrument could achieve in a year. Given that the findings showed that only 10% of this sample of instruments are reaching utilization rates of above 80%. This means that over 75% of instruments are performing at below 50% utilization rates, which is encouraging in the sense that we do have the capacity for the COVID-19 testing that will be increasing over the coming months. But it is a matter of utilizing this kind of operational data in order to be able to plan for this increased testing and this switch in terms of encompassing COVID-19. Another analysis that SystemOne data experts did was an analysis that was focused on whether these GeneXperts machines were COVID ready. What that really means is that the new GeneXpert Cepheid test for COVID-19 only operates on a GeneXpert software version 4.7b or later. This is something to note because to upgrade to later versions in order to be compatible with these new COVID-19 tests, it requires some careful planning in terms of time, costs, and human resources, etc. We did an analysis of 18 countries and about 594 GeneXperts. The findings were encouraging because many countries have upgraded and are ready for this influx of testing once the cartridges reach them. But however, there still are 12.6% of sites that require this upgrade. This and the other information about both analyses are up on our website, and we encourage all of you right now listening, if this is interesting, and if you require an analysis, SystemOne data analysts would gladly be able to do an analysis for your country to determine whether you are ready for COVID-19 testing.
A Q&A session followed SystemOne’s presentation:
QUESTIONS & ANSWERS SUMMARY[1]
Utilization rate measures the result of several intersecting factors in the TB diagnostic network (e.g., algorithms, specimen transportation, HRH, distribution, PSM, etc.). How much attention should countries give to this measure, particularly as we move towards the last mile of TB detection?
We recognize utilization rates are a result of several different factors that cannot be accounted for with one measure. However, utilization rates may be useful to explore and identify these compounding issues that labs face. For example, is the utilization rate low because of staffing issues whereby people are not trained to use the machines or is it a sample transport issue or are labs not properly stocked with cartridges? Enabling transparency through access to data can bring attention to where resources are needed and fix these problems. The utilization rates demonstrated during the presentation were intended to showcase the ability for countries to identify existing capacity to multiplex COVID-19 testing on existing machines to save countries from purchasing additional instruments. By understanding current utilization rates within a country, there is a significant opportunity to use current diagnostic investment to absorb testing for COVID-19 without the need for additional investment in any new diagnostic systems and without sacrificing any ongoing TB testing.
2. How long does it take for Cepheid to upgrade software to 4.7 or higher and what are the costs and local requirements? Does it require a personal agent in the facility?
Although this is a question better answered by a Cepheid representative, it is our impression that that upgrade itself only takes about 1 hour but requires stopping instruments from running to enable the upgrade process. For countries that have a technical representative they may assist with the process in-country. However, for countries where a representative is not present, Cepheid may assist remotely by sending a CD to help with the process. The local costs and requirements may vary however it is recommended that all existing data be backed up prior to the upgrade to ensure no loss of information during the process.
3. Aspect will meet a growing need. From your experience from around the world, are you able to say how well multiplexing is working and in particular, if there are any issues with maybe the lowering of the priority to test TB?
We see several countries beginning to use the GeneXpert device in labs to test for COVID-19 and we expect this number to grow. Understanding the capacity and utilization rates can enable this process and ensure continuity of TB testing while expanding to urgent COVID-19 testing.
4. Can you give us more information on the countries and data which are ready to run
COVID-19 testing? What is the cost for moving from GxAlert to Aspect?
Please contact SystemOne @ info@systemone.id should you be interested in upgrading to Aspect or GxAlert’s COVID modules. We will also provide a free COVID-19 “readiness” of your GeneXpert fleet.
5. Connectivity tools are more and more used and implemented, but one of the bottlenecks to the expansion is the cost. Are there any plans to decrease it?
A disease surveillance system requires maintenance. GxAlert, for GeneXpert connectivity, is the largest provider globally at present having connected over 10M results from 3,500 GeneXpert instruments and 43 countries. We currently provide over 75,000 real-time notifications for new TB case notifications each month. A number of countries have independently published evidence of impact of the system. We have explored various pricing models to ensure the best price for our customers while still maintaining the quality of our products.
Because of the increasing use of GeneXpert fleets for diseases beyond TB, we are planning to move all countries onto “per test” pricing. This will enable the countries to leverage the capital investment of their fleet, while allowing the disease-oriented funding streams prevalent in global health to only pay for “their tests”.
[1] 1 Note: The questions were submitted from participants who attended the Virtual Innovation Spotlight and the answers were provided by SystemOne.
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