Understand really the genomics of kidney cancer and now, like immunotherapy, genomics is really what we think is going to alter the way we treat cancers in general. It's all about personalized medicine where what is it about your tumor that's unique, that's going to allow us to treat it differently. I think we are just scraping the surface right now. So Alex is going to help us understand a little bit about the basics and tell us where the field is headed and maybe tell us a little bit more about where we are headed in kidney cancer specifically. So thank you so much again for coming on a Saturday. I know he just told me that he was jeopardized meaning that he has to come in and work extra in the clinic, in the hospital, all I said was I just I'm sorry about that, but I'm glad you're here just to give us a talk and that's all I care about. Thank you, Alex. All righty. Can you guys all hear me? All right, great. Well, Sandy, thank you so much for that warm introduction and thanks for everyone being here. And it's definitely a pleasure to talk on this Saturday afternoon. So I was asked to speak about the genomics of kidney cancer and this is definitely a very large field. But we'll try to break it down into the next four sections. Let's spend a little bit of time talking about each. So I really want to start off with just an overview. What is genomics? What are genes? What are mutations? So as we all know, we have 46 chromosomes in each one of ourselves, half from mom, half from dad. And within these chromosomes, we have genes. And genes are really kind of the building blocks for all cellular processes. And each gene is composed of the A's, C's, T's and G's that we've heard about in biology. And any deviation from the normal sequence here, as we can see, for example, with this red C being different from the normal T, that's what we call a mutation. And this is one form of mutations. There are many other types of mutations that can occur. And these deviations from normal really make abnormally functioning genes and then proteins, which makes cells behave abnormally. And then the process becomes cancerous. So we've known about mutations. We've known about genes for a while. But why is it only recently we're using this in the clinic? And this has really been driven by both sequencing costs as well as sequencing times. So similarly to the development of personalized computing where we went from mainframe to many computers to now personal computers and even cell phones, the same kind of revolutions has occurred in sequencing. So while in the 60s and 70s, we used things called gel-based sequencing techniques, which would take sometimes weeks, if not months, sequence just one gene. This has been replaced initially with Sanger sequencing, which allowed us to sequence for a few thousand dollars a gene maybe in a few weeks and for the first time allowed genomics to enter the clinic to now something called next-generation sequencing, which really has opened up sequencing to the masses. Now sequencing can be done for a few hundred dollars for the cost of reagents and sometimes be done as quickly as just one week. So if we actually look at the cost of sequencing over the last decade or so, we can see that it's dropped faster than Moore's law, which is kind of the prototypical law for the cost and the power of computing over time. And this is truly amazing. So while the first genome took 13 years and over a billion dollars to complete, now we can sequence an entire genome in the span of just a few weeks for a reagent cost of just a few thousand dollars. And with this, there's barely been an explosion of genetic knowledge. And this not has only pervaded all aspects of oncology, but many other disease states as well, including genetic diseases, which we'll spend some time talking about. So I think before we kind of jump into kidney cancer, I think it's really important to spend a little time talking about the two main types of mutations that we may encounter in the clinic. One type is somatic mutations. And these are mutations that are not inherited, so you're not born with these, but you develop over time. So these are kind of the wear and tear mutations. The longer we live, the more toxin we're exposed to, the more of these somatic mutations we develop. And if we develop enough of them in the right cell and in the right order, we can actually go on to develop, for example, the kidney cancer. Again, these are not heritable mutations. So for these mutations, you cannot pass them on to your kids, for example. And the other side of the spectrum, we have germline mutations. So these are mutations we're born with. And these are mutations that we can then pass on to our children. Rare mutations from the germline can predispose us to things like kidney cancer and not only drive the development of kidney cancer, but if present, put our, for example, children at risk for developing similar conditions. So how does this relate to kidney cancer? Well, we know that histologically kidney cancer is not one disease. We might have been familiar, for example, from our clinic visits with clear cell carcinoma of the kidney with the most common histological cause. But there's many more histological subtypes. And we now know that these subtypes are really driven by changes or by different genomics underlying these various forms of kidney cancer. For example, the clear cell carcinoma subtype is really associated strongly with this non-hippo-lindow, the VHL gene. And then we can see the other associations listed here on this slide. But if we dig deeper, the associations are actually much more complex. So this is definitely not a slide I want anyone to memorize. But it really, I think it shows that really, the genetics are very, very complicated. So no two kidney cancers, even in the same histological subtype, are the same. Kidney cancers have many, many mutations. And really, the combination of mutations make each kidney cancer unique. And really, we're beginning to exploit this knowledge to see if we can actually personalize medicine for each individual's kidney cancer. And many of the genes listed on the previous slide are actually seen here in dysregulating the pathways, which the therapies we use in the urology clinic target. So things like avarolimus, things like pazapinib, all of these target the pathways, which are dysregulated by mutations we discussed previously. So how do we tide this explosion of knowledge to actual clinical practice? And I think oncology is really an imperfect art. And this has been changing rapidly. But if we look at various disease states, the response rate for any particular oncology drug on average is actually fairly low. So what we've been doing historically in oncology is something called trial and error medicine. We try disease treatment A. If it doesn't work, we try treatment B, so on and so on. And then until we find something that works, wouldn't be great to actually know that treatment C is the right treatment up from the front and not actually have to go through two therapies, which were ineffective. So because of this, we've seen this explosion of personalized or precision medicine, where we're beginning to reclassify cancers, not based on the histology, but based on their genomic classification. So for example, you could have a lung cancer and a kidney cancer that are more similar because they actually share the same mutations, which may be targetable by some of these agents that we've discussed earlier. And because of this, we've seen kind of other cancer types really benefit from this genomic knowledge. So for example, in colon cancer, if somebody has a KRAS mutation, well, gosh, we know that urban tux will not work and the patient has spared that therapy. Same thing for lung cancer, if somebody has an EGFR mutation, we know for sure that Iresa is gonna be effective and that patient is spared chemotherapy. So this allows us to segregate patients who are likely to be responders or non-responders to particular therapy. And this gets us to, again, what are these mutations? And we can think of mutations largely as being either prognostic. So gosh, if you have this mutation, your cancer is gonna be more aggressive. It's gonna come back a little earlier versus predictive. And that's really the mutation that we care about most. And these are the mutations that say, well, if you have this mutation, for sure drug A will work or drug B won't. And right now in kidney cancer, we're at the prognostic stage. So we know many kidney cancer mutations are prognostic. So for example, if you have a BAP1 mutation, the survival is like this. And if you don't, for example, the survival is like that. But right now we're still struggling to find and identify truly predictive mutations that we can actually use to select the right therapy for the right patient. Because we'll talk a little bit later, that's changing rapidly. So in the clinic, when you're talking to your oncologist, what kind of tests may be discussed and what tests may you benefit from, especially in the metastatic setting? Currently, we're using things called panels. And you can think of a panel as a collection of many genes that we can sequence to basically try to find mutations that may be either prognostic or predictive in a clinical trial setting for your individual cancer. In the future, we think things like exomes. We're actually sequencing all the genes in the tumor. And that's around 20,000 genes may be used. Or even the whole exome, where we sequence all of the abnormal DNA and the cancer and try to derive knowledge from that. Currently, panels are what is being used clinically, but we do see the shift towards exomes happening very slowly. And we think maybe over the next few years, maybe that's the direction we're going to be taking. So how is this currently being used? So I think before we talk about that, it's good to look at how we use sequencing in the past. So before when we can only sequence one gene at a time, what we would do is we'd sequence gene A if it was normal. There's no mutation and we'd do gene B, C, D and E and so on and so on. And this would frequently take months if not longer to get done, because you would do this in a sequential manner. With panel testing, because you're sequencing a collection of genes at the same time, this can be done much quicker in the order of just sometimes a week or two. Where we can sequence up to hundreds of genes and get meaningful results back that can then inform clinical decision making. So right now, what's happening is that we're beginning to integrate genomic information into clinical decision making, both for prognosis. And we're hoping more and more for predictive purposes. So just like we would do a biopsy and interpret it or do a CT or an X-ray interpret that to use that to guide clinical decisions, we're now using genomics more and more primarily for the purpose of clinical trial enrollment. But we're hoping in the future for actually treatment selection. And this is becoming an integral part of many of our clinics. So how does genomic information really allow us to better select trials? Again, the old paradigm would be looking for individual mutations. So there's a trial that was enrolling based on mutation in gene A. You would test for that gene. If that was not present, you would test for a different gene. And frequently that led to really long delays in enrolling patients on clinical trials as you would kind of go again through this sequential process. Now with these next generation sequencing panels, we can test for many, many mutations. And assuming we find an individual mutation in each patient's tumor, we can actually then stratify patients to the right clinical trial in a much more efficient and a timely manner. So what trials do we have open at Stanford, which may be of interest to the folks in this room? Well, we do have the MATCH trial, and this is an NCI sponsored study, which again is using next generation panel sequencing to find mutations which may be actionable for folks who failed standard line therapy. We have some other trials, which again are based on a similar premise. So just focusing on the NCI MATCH trial, again, this is a trial that's multi-institutional, open all across the country, open for many cancer types, including kidney cancer. Where if folks run out of standard therapy options, the tumor can be sequenced. And the sequencing now is allowed to be done through companies like Foundation Medicine and some of the other sequencing providers, including Stanford's sequencing panel. And if any actionable mutations are identified, then a drug can be selected and then prescribed for that particular mutation. And again, this is just shown here schematically. And really the interesting thing is that even though we're looking at all of these genes and all of these drugs, many of these targets are the same ones that are abnormal frequently in kidney cancer. So definitely there's a lot of overlap of this trial's targets with what we know is frequently abnormal in kidney cancer. Furthermore, there's additional clinical trials open in the US looking at even more rare mutations. So we're beginning to realize that, again, cancers are so different, even kidney cancers that, for example, very rare mutations, if we find those, can be targetable. And I think that's really a reason to kind of look frequently when standard therapy options become unavailable. For example, n-track fusions are a very hot topic in oncology right now. So if this n-track fusion is present in a cancer, there's two trials open which have response rates over 50% in other cancer types. And these are currently enrolling kidney cancer patients. Also activating that mutations are now implicated in certain hereditary forms of kidney cancers and there's trials open for that. And even at Stanford, we have a trial for folks with these are homologous recombination deficiency mutations, which again also can occur in kidney cancer, the ability to get this specific drug, which is a PARP inhibitor that specifically targets this pathway. So again, many options there and really the only way to know if you would qualify for one of these options is to look. So I think talking about genetic testing with your oncologist, when standard therapies stop working, if that ever happens, it's really an important thing we encourage all our patients to do. So now let's switch focus to germline mutations again. So these are hereditary mutations which may be implicated in development of kidney cancer in certain individuals. So what I tell my patients is that even though cancer is genetic, so we know every cancer has certain mutations, only 10% of it is inherited. And that works out very well actually for kidney cancer, where it's around 10 to 12% of kidney cancers have some kind of hereditary predisposition. So these are some of the syndromes that we look for in clinic, especially if there's some concerning features, either a strong family history of cancer or some other rare forms of birth defects. Again, this is not something I want you to memorize, but just be aware that we look for this very closely in our patients. What I do want you to think about is kind of what are the indications for genetic testing. So again, this is for germline genetic testing, seeing if you have an inherited version of one of these mutations. And what we currently are saying is that if you have an early onset kidney cancer, less than 45 of the age of diagnosis, if you have multiple primary cancers in one person. So if you have, for example, two different kidney cancers, or kidney cancer and a thyroid cancer, which was diagnosed separately, again, that may be an indication for genetic testing. If you've had two, more than two family members with kidney cancer, which are immediate family members, again, consider talking about germline testing with your doctor. Or if you have more than three family members with one of them having kidney cancer, that could be you or somebody else, and any other cancer, again, that would be an indication for testing. And then we'll talk a little bit more about this, but if you have family members with kidney and some other rare tumors, again, that may be an indication for genetic testing. So I always, you know, we are always asking, you know, what's the point of knowing if I have one of these rare mutations that I may be able to pass on? You know, how does that really change my management? And wouldn't just not cause me, you know, more anxiety to know. And I think for a while that was a valid argument, but I think now we're knowing that the more information we have, the better treatment decisions we can make and the better guidelines and screening recommendations we can make. A lot of these hereditary mutations are associated with other cancer types. So if we know about that, we can consider earlier screening for other cancers. And for many of these mutations, if your children are at risk or other close relatives, they can then be easily screened and they can take appropriate precautions to catch any type of tumor that they may be at risk for earlier. Before, for example, it becomes something of a problem that requires more intensive therapy. So I always put up the slide as well. And these are the red flags that you may have something that's genetic driving your kidney cancer or somebody's kidney cancer in your family. So if any of these terms are familiar to you, you know, you may want to discuss with your doctor possible genetic screening. Again, a lot of these are very rare conditions that have run very closely with hereditary forms of kidney cancer. Yes and no. So OMA means growth. So Lyoma would be a growth of a smooth muscle. So again, I think what you're referring to here is if you have family members with other type of cancers or if you have more than one type of cancer, those would be indications. But these are usually, these terms are part of rare genetic syndromes that run with kidney cancer. Yeah, it's part of a very rare genetic syndrome that can predispose to kidney cancer. So again, we can maybe save a few questions for the end, but just cause we have a few more slides. Yes. So based on current guidelines, so you have a kidney cancer and your son has a different cancer. So technically it's hard to say, but the risk is lower. But if you had another family member with another cancer, then the risk would be a little bit higher. So again, that these guidelines kind of help us decide who should we screen. And then future directions. I think this is kind of the really exciting things that are going on with genomics of kidney cancer. I think we might have mentioned this earlier today, but liquid biopsies are really something that's taking the oncology field by storm. We've focused a lot of attention previously in looking for actual cancer cells floating around in the blood. Sometimes we could find those, but sometimes we can. And we've realized that instead of looking for cancer cells, let's gosh look for cancer DNA that's in the blood.  And by detecting this DNA in the blood, we can tell not only what mutations are found in the candy cancer without necessarily having to re-biopsy it, but we can actually track how much kidney cancer there is. And if kidney cancer is present or not, for example, after a curative resection. So this allows us to do something called monitoring or liquid biopsies to monitor certain cancers over time. Again, this is now purely done on a research basis, but we're thinking that in the future, this may become part of clinical practice. So for example, here you can see that this patient's cancer was treated after surgery, all of this abnormal DNA was gone. And then after surgery, it started going up and it was going up even before there was any clinical or radiological evidence of relapse. And this uptrend in this abnormal DNA then predicted relapse over a year before radiological relapse. So again, these are some exciting kind of developments in the field that really allows for ultra sensitive monitoring of possible residual disease. Again, currently doing this on a research basis only, but again, this is something you're interested in. We are starting to collect plasma from our patients to allow some of these tests to be done on a research basis. These are some of the companies that are currently doing cell-free DNA testing, which are actually commercially available. Again, we don't necessarily recommend using these tests for monitoring of disease, but they may be used sometimes if for example, a biopsy is too hard to do. We can sometimes use one of these tests to see if there's any new mutations present in the blood that may be actionable. Lastly, immune therapy, and I think we've spent some time today talking about some of the really exciting developments in immune therapy for kidney cancer, but really even beyond currently approved drugs we're looking for ways to predict who's gonna respond to immune therapy and who's not. And some of the approaches are actually looking for something called neoantigens. And we know that all of our cells have proteins which are on the surface.  So why doesn't our immune system pick that up? And again, this really ties down back to genomics and mutations. So how can we find which mutations really produce these neoantigens or these abnormal proteins that are gonna be more likely to be picked up by the immune system and generate a response to this immune therapy? So again, these are studies in process. And we think hopefully in the future we can be able to use some of these techniques to really kind of even personalize immune therapy to each individual's tumor. So I think that kind of closes my talk. And really the way I want folks to think about genomics is that in a way it really ties patients together because as we know more about the individual mutations in the various cancers, really we're seeing communities build around some of these mutations just like there's now communities in building around cancer types. So I think definitely if you meet criteria for some of this testing, talk to your oncologist and I'll be available for questions after as well. Thank you. My own personal experience is that unless you push for it, even at a stage four, they're not going to sequence your particular cancer unless there's some special situation. Would you recommend that everyone who gets to stage four have their cancer sequence? There's information to be found there. But that doesn't seem to be the current practice. I think if current therapies are not no longer effective for stage four cancer, I do recommend everyone have their cancer sequence. I think sequencing the cancer very early, for example, right at diagnosis of stage four cancer may be less meaningful. And really I think the time would be actually at progression beyond standard therapies because you can really look at that time for all the mutations that are present at that time point. So if you sequence too early, you may actually be missing some of the new mutations that have developed over time. So the genomic costs are getting cheaper and cheaper but we've been seeing that for a long time and even that curve seemed to have flattened your chart ended in 2014. So when is it going to be inexpensive enough that it's commonly available to a lot of patients as part of the standard healthcare system and cancer treatment? Because despite that speed it seemed it hasn't gotten to where we thought it would be in 2017. Yeah, I think a lot of this also has to do with reimbursement. So I think even though some of these technologies are available reimbursement patterns have been spotty for a lot of these tests. And for example, the GARN test, I mean this is a liquid biopsy test that just like a month ago received reimbursement for the first time in a subset of lung cancer patients. Because reimbursement's really lagged, we found it hard to get some of these tests to patients. So I think again that's something we currently work with, payers and insurers with about but really reimbursement really drives adoption for these tests. Follow me. Yes. I would just add one more comment is that, I mean if you do a test we think that you need to have an actionable item, right? There should be something that we can act upon that test and prior to the match trial being available it's really been a challenge if we do a sequencing and we find a rare mutation that only happens in breast cancer for instance. I mean getting that drug available to the patient has been extremely challenging for insurance companies don't want to pay for something that hasn't been proven that hasn't been approved. So it's really been, it was a challenge till the match trial really came along where if we find something we could at least then offer an appropriate treatment. All right, thank you.


I was good the next day. They cut right now Aaron's back and he's talking up another Unknown guy Kofusi yeah Bronson Kofusi Bob Damofsky the People's writer asked an incredible question to lead off Wow


This is the session on DHS2 and PEPFAR, and let's get started. If other people wander in, they can join us in progress. We have three presentations in this session. As you may know, DHS2 is used in a PEPFAR, there's a main global instance that collects all kinds of data that's called datum, but DHS2 apparently is used in many other ways in PEPFAR, and the papers we're going to hear today, none of them are actually talking about data going into datum directly, so we're going to hear some other ways that DHS2 is used in PEPFAR. The presentations will be by Lombay, who's going to talk about the safe system from USAID by Kayla, who's going to talk from FHI 360, who's going to talk about an epic DHS2 system, and from Vlad and Alicia from ICF, who are going to talk about digital health inventory and how that's being used in DHS2. First, we'll have a remote presentation. I'm sorry that Lombay couldn't be here in person, but some visa problems presented that, but he will present it virtually, so Lombay, you can go ahead and share your screen and start when ready. Okay, thank you very much Jim, so let me just share my screen until let me know if you see it. Looks good. All right, that's good, good. Yeah, so my name is Lombay, I'm the data management and strategic information advisor for the USSF project, which is a project under JSI, which is Johnson or Inc., and being implemented in Zambia in three regions of Zambia. So the abstract title focuses on the use of customized apps in improving data collection and monitoring, as well as reporting into the into datum, which is the PEPA system that we're reporting into on a quarterly basis, semi-annual and on an annual basis. Yeah, so just a brief overview of the USSF project. So the USSF project is implemented, it's been implemented in three regions in Zambia. As you can see by the map there, they are shaded regions that are north-west in Kuba Bay and central province, and then find that they, if you look at the main mandate of the project is to reduce mortality, morbidity, and transmission when proven nutrition outcomes and family plan integrations in the three regions. And the project life is initially a five-year project, which comes to an end this year, but we have an extension that's going up to 2024. And that's a period of implementation. And at the moment, we are supporting 302 health facilities, which are in 24 districts in the three regions. Then of the 302 facilities, we do have the strategic information assistance, who we call, we can refer to also as data associates. So these are people that handle the data facilities, as well as the rest of the clean and other community health providers in these three regions. And then if you look at one of the mandates that we have amongst our objectives is the 95-95, which is a UN-edged objective, where we are looking at 95 percent of our people to know their status out of those, 95 percent should be put on treatment, should be initiated. And then out of that, the 95 percent should be very suppressed. So we work within the same UN-edged objectives. And then at the facility itself, we just don't focus on one component. We look at different other aspects there, like cervical cancer. We do look at family planning. We also look at the pediatric cascades. And also support some of the community activities such as index testing, of which everything, when you put it up together, we need to call back to the 395s on testing initiation, as well as suppression rates. So because of that, that's why we find that we do all indicators referenced by the MR. As you're all aware, most of us in the house who are familiar with PEPFAR, PEPFAR does release the modern evaluation and reporting reference guide every year, somewhere by September, October, somewhere there. So this time around, we have a vision 2.6, which already is September of 2021. So we actually use the same indicators that in the MR, that's the data that is collected from the health facilities by the teams, the MRD team, as well as the clinical team. And then we do have some other custom indicators as well that are collected on different intervals. So we do have indicators that are collected on a daily basis. We have some indicators collected on a weekly basis. We have some on a monthly basis, quarterly basis, and the semi-annual basis. So depending on what reporting needs we want to find that we do collect these indicators on those different defined periods. So as you've seen by the header, it's written GHIS2 echo platform.  So echo, we were just looking at the bouncing back of the way it is, the name is echo, the bouncing back of sound. So we looked at it and thought of having a creative name where instead of bouncing sounds, we are bouncing back data. So when data is collected from the facility, using GHIS2 aggregated, analysed, it's bounced back to the different providers who are at health facilities and as well as the other technical team who are clinical. And everyone else who have an input in the data and we all now have to speak the same language. That's how we came up with a term echo to go our system. And then looking at the pay for EMIR, all pay for supported IPs in the country and just use the EMIR. That's why we also adopted the EMIR for our reporting on the different indicators. So give you a brief background as well on where we were before migrating to GHIS2 and how we used to do the reporting. So before then, we were using an offline system, you can call it. It's where data was being collected from the Excel template from the facility level. And then that Excel template is submitted to the district for aggregation. Then the same tool, a different tool now is submitted to the province for aggregation into one file. And then that file was put into Microsoft Access. So we were using Microsoft Access as a transactional database. So I think that's used right there at the province. And then we know the cleaning is done. And then the province is happy and comfortable with their data that was now sent to the national office, where aggregation was done into SKL7, which we're using as a data warehouse at the time. And then depending on the different reports that we have, we have the daily report, weekly, monthly, quarterly, I know those reports. So finally, to have all these different templates and all these different transactions of databases as well, which would be sent back and forth to the regions and the national office. And then also later on aggregated into one into SKL7. And then finally, when time came for reporting itself, which is the Quota report as one of the reporting periods itself, paper, we'll go back to SKL7 and put this data on some queries, put the data into an Excel CSV file, which was later imported into Datting. But before that, what we had done using the Datteam UIDs and the Datteam codes that we got from the exchange platform, we actually mapped those codes into our SKL7 database. So it would be easy for us to actually get the import file that we can use for reporting into Datteam. So we find that during this whole process of having the back and forth access, SQLSaver, get a Datteam file, finally to have these all back and forth, which was time consuming. Finally, by the time you're getting a report from one of the regions, which is about 700 kilometers from the national office, per adventure, there's no proper internet connectivity at the time. You find that that file can actually be shared. Even if you try to share it through Google Drive, would have those challenges. And then the process of cleaning through all this from Excel to access and SQLSaver was also proving to be a challenge at the time. And then every time the mail is released by September, we have to go back and update the new codes if the indicator has been dropped and find that that entire process of closing out some indicators opening up other indicators, changing the frequency of reporting and all that, you find that during that whole process, you find that you will lose out on time and have some errors in there, the mappings won't be correct, and some validations also miss out at the time of doing the Datteam validation, Datteam validation and the import. And when all that is done, the report has to be generated in money. So when you run the query for miss here, we have this reporting in Excel, and then you start filtering out what we don't need to come up with an import file that is needed for Datteam. And you find that at the time of doing that report, the entire process was only have a short window from the time we finished our data collection, which ends somewhere by the 10th of every month. And then in the end you have only have about two weeks to do the cleaning, the cleaning and all the aggregation and everything else before we put into Datteam. That's if you're doing the Kotter Report. So we're forced to wait more, extra hours, we're forced to touch and bring the mean that oil for us to make sure the data is clean, because we do have a lot of better elements that would what we collect as a project. Right now for us to go to DHS to improve them, because we still maintain most of them, we've got over 600 that elements that would collect on a monthly basis. So find that as you are running through all those validations using our SQL server and the access, time will be lost. It was quite a little bit intensive. So at the time of reporting, when you're done with the actual reporting, you now have to take a breather and take a few days off before you can report and get back to work. So with that, DHS2 was then introduced to us in JSI. It was there running with other projects, but as a project, we now thought of migrating to DHS2 and we thought of how are we going to improve our data collection, the aggregation as well as the importing tool into Datteam. So we came up with our DHS2 instance, as I mentioned earlier. So this little diagram here is able to show us a few, let me see if we can get the laser to just point a few things here. So right now the way it is, at the facility level, so we do have this data entry person with the strategic information assistance who does collect the data from the registers and the different THR systems at the health facility and they enter directly to Datteam. Sorry, they enter directly into Echo, which is our DHS2. Then at the same time they enter in that, we know we appreciate the good features that DHS2 has. The M&D team mostly at the district level and the provincial level are able to see the data and they can quickly give feedback and they can easily run validations from there, provide feedback to the facility and the team in the facility can also now they can go back, correct the data and clean it right there. Such that at the time when they're done with their cleaning they confuse them, see some visualizers and reports to see how the data is sitting and then we have some other now key stakeholders, technical team can also look at the data and see what's happening. So at the time everything is happening in collection, everyone is involved from the facility all the way to the national office. Everyone wants to see how the data is, run the validations and all that. So what we did to make our lives easy, we mapped all our validations may make the Datteam validations for most of the indicators, especially the ones that are paper indicators, they mapped the Datteam validation so it's easy for us as we run the validation against the Datteam and important to Datteam find that it makes life easy. So how did we achieve this as a project? This is where I have this section here where we're showing the managed data for Datteam app. So this is an app that we have developed and embedded into GHS2, we call it the managed for Datteam app. So how we came about setting up the app, we got the UIDs, example for the organization units, we got all the quotes from Datteam as provided by the Datteam exchange team. We got all the org units, IDs and we got all the data elements, UIDs as well and we got all the category, option, combos, the way Datteam has actually, the way they are set up in Datteam, then we use those ones to map to our GHS2 UIDs. So the indicator in Datteam, example, two excursions is the people that are currently on ARIT is mapped the same way in our echo as the people grant on ARIT. So we get the UID from there and we get the UID from Datteam and then we reference those two. So that's how we managed to work around the managed for Datteam app. So to achieve this, we are using, right now we're using vision 2.36 and all the data is actually stored in the data store. We don't have any external storage of data, so everything is from the data store and we're using the Python scripts to help us do the mapping from and the mapping between the Datteam UIDs and the Datteam codes as well as the echo UIDs and the codes. So found that after introducing this app, I can attest to this, the work that is to take one week for us to prepare the quota report, the quota three, quota three has got very few indicators to take us about a week class and for that we're able to do that in like two to three days, maximum three days. That's if we're just taking our time, we're just waking maybe six hours in a day also, but if we try to push further or at least with nine hours in a day, we find that we're able to achieve that in two days and finish the entire quota three report for certain reporting periods for semi-annual annual, that's what we tend to do about four days. So the period has just taken two weeks, it now takes us about a week or so, five days, we are done with the reporting because life has been made easy, so all we do is just click the button and then see the mapping is done right in the background and though the validations are already configured in our DHIs to based on Datteam, we pull out the data and it will generate the CSV file that we now use to validate against Datteam and which I reported the data into Datteam. So it's one of the things that has helped us, the app customization, which has actually made life easy for us to map the category, the category combos and every time there's a change in the MERA now, if I know it's easy for us, we just go in, just change from the front end and then the indicator will be mapped differently and also the manage for data, the app actually allows for data quality checks, web monitoring validations through the app itself, so we have about three intervals of validations, the form validations, we can the actual data quality and then we can run the validations as well from the app and eventually run the validations into Datteam and then we will then report the data into, we will report it into the Datteam Dev instance and the file of the instance to Datteam support for Datteam on plot. So what are some of the things that we have picked up that we can call the results and the results and conclusions is that using DHAs to an eco-entranded and to health facilities has actually made life easy for us when it comes to aggregation, analysis and reporting, that's like at facility level and all and then on or not end when it comes to Datteam reporting, find that life has been made easy because before then we were, we would assemble a team of about 30 from Mitridge and 30, 40, bring them in one place, I start doing my new data entry, though they have to burn me that all work one, two weeks to do the entries but now we don't have to bring anyone in one central place, all I have to do is wherever they are, they do their normal entry on the monthly basis, then we just run the app and the data is aggregated within a few minutes, we'll have the data already in Datteam. So found that the time has been reduced for about 50 to 60 percent when it comes to running these preparing the Datteam reports from 10 days to about 5 days somewhere there, all that has been reduced has by using the app and then the app also helps us to generate the reports that we need depending on the frequency that we're reporting on and then it also helps us to just submit an error-free report over and then definitely what we can appreciate about the app is we try to also to make it easy to help us report on data outside Datteam such as the high-frequency reporting to get it as a HA farm. Sorry to interrupt, it's been more than 15 minutes, are you able to wrap up in a couple of sentences? Sure, not a problem, this is the last slide. All right, so we can say efficiency has improved the data quality, has actually improved our data quality, that's the use of the app. And yeah, like I said, this was my last slide. So yeah, so that's what I can say about the apps in that it has really improved our work and it does make work easy for us as a project. And thank you. I didn't realize it was 15 minutes. Thank you. Next up we have Kayla who will talk to us about Epic System that FHI 360 has developed. Okay, while they're setting up the presentation, maybe I can just start by saying, Lone Bay, please send us your app. We definitely want to use it. It would definitely help our project as well. All right, that's good to give. Yeah, we can chat to all of us. Okay, great. So my name is Kayla Stankvitz, I'm a technical advisor in health informatics and data science at FHI 360. And today I'm going to be talking about our experience using DHIS2 in the Epic project, which works in 65 countries. So honestly, you can take all the background from the previous presentation and just apply it to many, many, many countries. And it actually works well as background to our project as well. Okay, but just briefly, we are a five-year PEPFAR project supporting HIV and also COVID-19. And we're focused on key populations. So these are populations that are at higher risk of HIV.  We also work in some generalized epidemic countries where we just support the general population. We support the full range of HIV services from testing, prevention, and treatment in over 30 countries. And more recently, we've started supporting COVID-19 vaccination and oxygen systems in over 40 countries. So that's where the 65 countries come in. We work in some countries in both HIV and COVID. So the reporting burden for our epic supported sites is quite high. Many sites originally collected data on paper, and then they'd have to count up those numbers on a regular basis and report to Ministry of Health databases. They have to report monthly to our project database, which I'll talk a little bit about later. And then they would report quarterly to data. So there was a very high data entry burden for our staff. And through Epic, we've tried to improve the data reporting and utilization of the sites that we work with. And DHIS2 has been a really integral part of that process. So we use DHIS2 tracker in, I think, 20 of our HIV countries now. And as I mentioned, as I mentioned, both our project database and our funder's database are also based in DHIS2 aggregate. For DHIS2 tracker, we actually developed a metadata package that's available on our website that can be used for tracking all of the services that I mentioned here, or sorry, here from testing prevention to treatment. I've given multiple hour long talks on that system. So I can't cover it in an hour or sorry, I can't cover it in 10 minutes, but I'm very happy to chat with anyone about that if anyone's interested. So this is what our aggregate DHIS2 system looks like for the project. It's called InfoLink. If anyone is familiar with datum, this looks a lot like datum. But what we do is we further disaggregate all of our data by population type. So if you think about datums reporting, I think maybe some people in the room know how burdensome it is to report quarterly to datum. We have further disaggregated our data and we're reporting it monthly instead of quarterly. So this is a really, really big data entry burden for our teams, but enables us to have really good data that we can act on. And I just want to, this is mostly focused on HIV, but I want to briefly mention that maintaining a DHIS2 aggregate system at the project level has enabled us to very, very quickly adapt when we got COVID-19 bias. So we were able to very quickly use this platform to collect COVID data as well. So as I mentioned, the reporting burden into InfoLink monthly is quite high. So we've actually used a tracker to aggregate data migration process to translate the data from our 20 tracker countries into the aggregate data format to report into InfoLink. I think if you're particularly interested in tracker to aggregate, you're probably not in this room because there's a session about this going on right now. But I'm happy to talk about this process that we use as well. And I'm really excited to hear that this is being integrated into DHIS2 going forward. So the main thing I want to talk about is how we actually automate our reporting in the project and how this has enabled us to improve data quality and consistency of our reporting to our funder. So we do this using Power BI. So the challenge was that each of our countries that work in HIV, which as of right now, that's 34 countries, has to submit quarterly reporting slides to PEPFAR. They have to generate these on a quarterly basis. And the quality of these slides kind of varied across countries. Some countries had a lot of capacity to generate graphs and visuals. Some had lower capacity. But there was also nothing preventing them from entering different data than what they were reporting to InfoLink. So they could report to InfoLink and say that they tested a thousand people and then they could write in their quarterly reporting slides that they tested 800. And there was nothing to automatically flag that as an issue. So what we did was we actually automated the reporting process via DHIS2 and Power BI. So we utilized the DHIS2 API to create what is technically a Power BI dashboard. But we export that dashboard to PowerPoint and it automatically generates about 100 quarterly reporting slides for each of our countries. So there are multiple benefits to this process. One of them being that we have one source for all data. So now any if you want to use the automatically generated slides you have to enter your data into InfoLink and you have to enter it correctly. So it actually motivates people to enter their data on a more timely basis and to correct their data entry. It also really reduces the reporting burden so people don't have to manually create their slides every quarter. And it has increased the quality and consistency of visuals across the project. So this is just an example of what that dashboard looks like. So when one of our teams logs in they have to enter information such as the country they want to report for, the quarter they're reporting for, in which population types they want to highlight in the slides. And then the system actually automatically generates 100 slides. So it's as easy. So all the slides will show here along the left and it's as easy as expressing export to PowerPoint to get your slides in a PowerPoint format. This is an example of a slide that's actually not showing any data. It's just a title page for the PowerPoint presentation. But here are some examples of what some of our slides look like. So this is an example of the cumulative cascade showing our performance towards targets. So we can see for some key paper indicators what percentage of our targets we've hit and see a consistent graph across all of our countries in each of our QPR or quarterly reporting slide decks. Here's just another example of a slide that again shows the graphs that are automatically generated. So lessons learned, DHIS2 has been a really effective platform for increasing timely access to data in our project. We work across a lot of countries and DHIS2 has enabled us to get data from all of those countries in a timely manner and share it with the stakeholders that need that information. It's also enabled us to rapidly deploy information systems in during the COVID-19 pandemic. The DHIS2 tracker to aggregate integration process is possible, but it's I haven't had a lot of time to talk about it today, but it hasn't been very simple for us to maintain mainly because some of the things that the first presenter talked about, our funder updates our reporting requirements every year. So every year we have to go into 20 different DHIS2 instances and update all that mapping. So we're looking for better ways to kind of facilitate that. And finally, DHIS2 and Power BI combined have greatly improved our ability to use our data, but we acknowledge that Power BI isn't a good solution for every country. As a large international NGO, it works very well for us, but as we transition some of these systems to local ownership, we're really interested in similar open source solutions. So if anyone has any experience with that, please feel free to reach out to me. Great, thank you. Thank you, Kayla. The final presentation will be from Vlad and Alicia, who are working with ICF on digital health inventory. Okay. All right. So hello everyone. So my name is Alicia Smith, and my colleague and I will be presenting on a new initiative by a project called the Digital Health Inventory. As Kayla has gone through Epic a while ago, that's one of PEPFAR funded project. And this is one thing that PEPFAR that will need to be invented in the future once we have this tool available. So just a quick background of the why we're doing this tool. So one of the challenges or what PEPFAR is seeking to do is align digital health strategies. And they need to do that in order to have better health outcomes. And they can't do that because of, you know, data needs to continue to evolve. You know, with the pandemic, you see that we needed data for COVID just to see how we were responding. There's different data formats and systems in their reporting countries. We've heard about interoperability issues, data use issues in a lot of the sessions that we had today. There's another problem with standardizing of indicators on reporting. As any person who is lending you money or giving you money, you need to be accountable for how you're spending our money. So, you know, there's a high demand for accountability. There's high degree of fragmentation. We realized that there are a lot of donors who are investing in the same digital systems. And it would be good if we'd have better coordination across these donors. And one of the things that we have heard on numerous occasions is we need to have granular data. That's the best way for us to have proper secondary use of data. And for persons who work in the purpose space, you've heard Mark, use this phrase a lot. We need to collect data once and use multiple times. So I've adopted. I'm not sure what's happening here. Okay. I'm not sure what's happening here, but what we did was we looked at the principles of donor alignment and kind of copied some of the ideas or the ideology from that. And what we want to say is for what donor wants is they want to collaborate and align their investments to the national digital health strategies. They want to prioritize their national planning to just incorporate digital goods. A lot of the work that preferred does is focusing on digital goods or global goods. We want to be able to determine and quantify long-term costs of any investments that we're investing in. We want to track investments just without the progress, the learning opportunities, successes of these investments. And we want to be able to strengthen donor technical skills as we just understand how each donor is investing into these tools. So what donor will invest in, we'll invest in things that are creating and just focusing on the national digital health strategies, policies and regulator frameworks. We're also looking at systems at an appropriate, okay. There we go. So when the slides are real, we can review this slide, but it's on the principles of donor alignment. So what donor will invest in, again, anything that focuses on the creation and evolution of the country's national health strategies, policies and regulatory framework. We're also looking at systems that are on the projectory and progress of continuing their health maturity level, looking at sustainable country capacity, focusing on government implementation, global good adaptation, and also digital health global goods that are sustainable, scalable, accessible, and again, the big word, incomparable, just to ensure that we're meeting those country priorities. And one of the things that we don't really focus mostly on is just the stakeholder sharing of information and ensuring that as a global community, we're doing peer learning across these multiple systems that we're investing in. And that's one of the reasons, those are multiple reasons why PEPFAR is launching the digital health inventory tool. We're referring to it as DHR, not to be confused with DHR, it's two, right? Just a short inversion. So this is a new data stream that has been outlined in the country operation plan in the FY22. And what DHR aims to do is just help PEPFAR understand how these investments start to, you know, put their money in, how they can, the collecting data, so these digital health can help us inform planning, align investments across donors, lower burden, and increase the usability of national digital health inventories and also just identify ways that we can scale tools and just improve healthcare delivery. And again, going back, we're seeking to have better health outcomes. And one of the things that we've done so far with this tool is we've developed it, and we have already piloted and have collaborated with several stakeholders, namely there's an IWG that we're working with. We're also working with public health gates, foundation, global fund, and then we have extensive feedback and, you know, collaboration with multiple implementing partners, namely from Uganda, Vietnam, and Zimbabwe. So quickly, my colleague is just going to run through how we implement this in DHRs too, and I just did the background. Thank you, Alicia. And I recognize we have very little time left, so we'll just go through this quickly. And I'm not going to have a lot of technical detail, unfortunately, because it will take a lot more time. So I'll just do an overview of how are we doing this? So we are doing DHRs too. We are using DHRs too. And so, you know, PEPR has data which basically is used for collecting most of the data streams that PEPR collects, be it that MRS, SIMS, or anything else. So all the users have accounts. They know how to use the platform. So creating a new platform for new data stream would be just not a good idea. So we were trying to figure out how to fit DHI with its complex qualitative questions into DHRs too. Obviously, aggregate data format does not fit. Event and tracker didn't exactly meet our needs either, because our questions were too complex and the requirements of how to display the forms was a bit complicated and convoluted as well. So we decided to go with a platform as a DHRs too, where we would create a React application using the DHRs to library. However, we would use AWS serverless platform on the back end for storing the data and processing the requests coming through this application. We still take advantage of DHRs too for user authentication, user authorizations. We use the data store where we keep some of the information that is possible to store in the data store, and then the rest of it is in AWS, easily accessible. The system team working on PEPR systems, BAO mainly, has been very helpful putting together the tool set that allows this sort of throughput and connectivity to the AWS. So what this custom app does is basically just log in into DHRs too, and then you have this app, but it provides you with sort of alternate form that you wouldn't be able to get through native DHRs to data types. We have custom data entry field types, where we have the checkboxes where you can select multiple with other, where you can extend it with additional text associated with the other. There's radio buttons, and there's this dynamic questions, where if you select a particular answer that additional sub questions will appear. And then we do on the flag logic validation, where we flag everything as you type, as opposed to, you know, in data entry app, you would have to run the validation as you finish the data entry. So what we've done is piloted this to three countries, and these three countries provided over 80 entries. We've had follow-up focus groups with the three countries, and we've gathered feedback from them. Based on their feedback, we've implemented the bug fixes, we enhanced the workflow, and revised and expanded some questions to address the needs. And then based on that feedback, we've had version 1.1, and we're launching it actually on July 1st. It will be launched to 23 priority countries in PEPFAR, but then PEPFAR obviously has, I believe, over 70 countries, and the rest of the countries are optional, where if they want to report it, they can, and it's just that the priority countries are required. Now, of course, collecting data is one thing, but then how you use this data, you know, I think Jason Pickering likes to start with the back where, you know, you start with analysis question first, like, what do you do with this data? Because asking for the data is easy. So it'll allow us to facilitate alignment of the donor data and investments. We'll be able to do the national inventories and landscape analysis of what's out there because so far PEPFAR has not done anything like this where they would ask questions like what are the systems that we've invested in, identify scalable tools to improve healthcare delivery and improve the efficiency of programming and reduce the redundancy of the digital interventions. You know, it'll let us articulate the required digital functionality and synthesize evidence and research, and then it'll allow us to provide a regularly updated and broadly accessible landscape analysis. And that is it. Thank you very much. Thank you, everyone. That's the end of the time for the session. If some of the presenters might be able to stick around for a minute or two, I know I'm supposed to be somewhere else in 430, but thank you all for coming.


city and in the territory on west there's just one way to handle the killers in the spoilers and that's with the u.s. Marshall and the smell of gun smoke gun smoke starring William Conrad the story of the violence that moved west with young America the story of a man who moved with it Matt Dillon United States Marshall Chester and I had left Dodge about nine that morning it was a good day clear with a snap in the air the horses felt it too and they wanted to move fast not in the loop that we were holding them to Chester took a couple of deep breaths and liked what he smelled is a fine day Mr. Dillon a fine day I had some government papers to take over to Bill Holton with the post office in Pierceville place about 40 miles west of Dodge Chester and I figured we'd stop overnight and right back the next day we followed the trail along the Arkansas and stayed with it as it left the river at Cimarron and cut across the prairie looks like a big wagon paint up ahead there at the crossing Mr. Dillon yeah sure looks like a chester Chester was right but thus cloud we'd seen became 30 and more wagons taking the Cimarron crossing it was a shortcut of the Santa Fe Trail leading on southwest toward Ratone Pass we passed them and our trail swung back to the Arkansas again we rested what are the horses a couple of times and by afternoon we could see the warehouse the store and the post office a few of the other buildings of the town it wasn't a big place Pierceville maybe 50 people regularly living there funny peculiar yeah I just don't rightly know sir just funny it's peculiar you mean nobody around yes so that's what I was thinking that's what I thought Mr. Dillon what do you figure them horses are doing down there it ain't right they should wander around like that without it Mr. Dillon they got their saddles on too the horses were down the street and as they heard us their heads jerked up and they wheeled about and trotted off away and around out of sight and we stopped they listened there was nothing to hear an empty place nothing to see but there was a feeling in the town you couldn't figure what we walked the horses over to Bill Houghton's post office maybe everybody in town is sick mr. Dillon no or maybe dead no couldn't be that no crows and their buzzards mr.  Dillon I swear it gives me the will he was I never seen anything like it not a living soul in Chester did you hear something I'm not sure just wait a minute they're kid crying I didn't we ought to try the storm mr. Dillon huh hey uh all right keep your eyes open Chester yes we'll take a look in the saloon first the saloon was about 200 feet back up toward the end of town but we didn't get that far they stepped out behind us as we passed the livery stable and we never had a chance to draw get your hands up hi we did and I felt my guns lifted away and then we got a look at what had crawled into Pierceville there were three of them and they were killers man gets to know the look in the eye of a killer if you're lucky you see it in time now we weren't lucky that day it's the law bril yeah are you from mr dodge dodge that's Dylan no it sure is you Dylan Marshall Dylan from Doug yeah you want to try that again we will won't fret yourself about that Dylan you move in taking the warehouse bril yeah besides better to get rid of them if you asked me I don't think so not right now they might be able to help I've always wanted a U.S. Marshall to help me isn't well take away his gun you watch him he'd be on his belly begging to help they took us to the warehouse and we found out what had happened to the folks who lived in Pierceville they were all in there the kids the six months old baby the women and the men inside there were six more heart-faced men leaning against the wall near the door where guns held lazily in their hands they'd taken over the whole town and for some reason they were holding it the one of you shut up to keep that kid quiet you want me to do it for you mr Dylan be quiet can you again which one of you shot my kid brother you hear what I'm saying which one maybe you know this fellow just walked in here of this pal he's a U.S. Marshall out of dodge his name is Dylan I'm gonna make him countable for what you make up to do the man does a kill on his countable ain't that so much that's so okay one of these folks killed my kid brother nonetheless he talks up there's going to be a lot of killing around here you get that you talk to him Dylan you explain the law I'm a fair man I'm going to give you a couple of minutes don't nobody try nothing because we'll be right outside don't try nothing hey Chester there's Bill Holton over there come on hi Matt how are you Bill could be worse I guess Mr Holton your fakes what'd they do to you I was the first one they worked on will you tell us what's happened Bill well they rode in early this morning whole outfit I figured them for trouble when I saw them straight off I knew a couple of them held me knocked me around others grabbed three women kind of a hostage I guess Brill he's the leader he cleaned out the safe what about the killer three or four of our boys came up saw what was happening started in shooting and these snakes hauled the women folk over the post office door and kept them in front for shields hear boys stop shooting them yeah sure drop the guns where they stood Brill's kid brother was already dead then Brill kind of went crazy swore he'd kill the women burn the town in the outfit rounded up a couple more women after that everybody else none of us wanted to see the women hurt I guess we gave up too easy on account of his brother he calls it murder you heard they've kept you locked up in here ever since yeah yeah he says he'll take us out two at a time and shoot us if we don't tell do you know who it was no no like I say three or four fellas were shooting even they don't know which one of them it was listen Marsha I'm Dave Maxon I got a place outside of town but listen we gotta do something quick yeah yeah sure take it easy but my wife that's her over there she's she's got the baby we come in this morning to get something at the store you gotta do all right Mr. Maxim I just take it easy will you look just 30 of us the man with we we could rush him and some of us had to kill now listen we gotta get to the Marsha I'm thinking all of us are get killed and that's not the way we gotta do something yeah I know well this baby she came what's it gonna be delin step over here well what do you say I don't know seems to me you came here and broke the law it's the chance your brother took when he got killed that was murder he was shot in the back maybe he got turned around looking for somebody to kill himself it was murder I'm gonna stand here arguing with you mister who did it you think I'm bluffing I tell you I ain't bluffing if I have to wipe out this whole stinking town I'm gonna do it that doesn't get your brother back you and the habit of killing women and kids you shut up Santa's cargo start with two of them take them outside crazy you do this and they won't even hang you you'll be torn to pieces you won't be around and see it all right go on get them outside well anybody got anything to say anybody gonna say who killed my brother I'll tell you something yellow anybody else still need to look the two men out and we stood there some of us looking at the body of Maxon with his wife sobbing over others staring at the closed door it happened so quickly there wasn't time to think to figure anything there wasn't any way to shut out the sound of what happened outside I gotta do something no Bill don't you will return for the second act of gun smoke in just a moment but first a skid can be tragic if the road is wetter icy a faulty windshield wiper that's a nuisance in a shower can be your nemesis in a snowstorm the summoned substance of our message being take extra care when you're driving under winter conditions make sure your cars prepared for winter and then drive it with twice your usual caution now for the second act of gun smoke except for Maxon's wife and another woman whose husband had died there there was a quiet now in the warehouse the killers didn't come back in again maybe for what they've done they didn't have the nerve right then takes nerve to look at the faces of the ones who are left I found out that there've been 12 of them who've written in now with the one who was gone over 11 I talked to the boys who had done the shooting at the gang two of them were willing to give up but two others weren't and I didn't blame them we waited Chester Bill Houghton and me in a corner trying to make a plan an hour went by an early evening chill found its way into the warehouse I think they'll do it again two more of us now for a while maybe that kind will get liquored up first it makes them brave I still think that maybe now's a chance to get outside mr. Della yeah it might be what scares me though is they'll start with the women and kids yeah there's always a chance somebody'll ride in maybe see what's happening it's in for help like us some sizes that take too long mr. Dylan let me try it I don't want to hear no more of these women doing that just let me thank Chester they're coming back but all right come on quick there's two of them you can see through the crack yeah it's the ones that got our guns Braille listen with them Chester get on the other side of the door yes you mr. Bill behind me right now when they come in grab them time now look I want everybody to keep real quiet do you understand yeah all right now wait until they're inside you think that this might be around the bank I don't know we'll take the chance whoever gets hold of them don't let him yell let me have a drink what do you think what in there how should I know we shouldn't hang around too long figure we ought to start riding you know Brill it was a kid he thought a lot of yeah yeah hey hey there's one woman in there though did you see her torn oh no with the old man the pretty one that little oh yeah yeah maybe we get her out here and the others will talk might be I ain't saying it will make them talk but a lot of men in there are soft about women what about Brill nah he don't care he wants to find out who killed the kid maybe maybe we can get him to talk sure it might be fun miss now I'm none of you over there come on we won't hurt you we want to talk to you outside come on he said come here she don't want to cover me will you I'll go get her oh this one's got two all right which one of you here can handle a gun right don't leave yes sir here we'll split up the cartridges just to get over by the crack there and keep a lookout yes one of the kids following eggs behind those empty crates a good see if you can find anything else yeah well three of us now nine of them with guns yeah except that we know that and they don't don't leave you're gonna have to stay here Chester and I'll try to get some more guns now you got a good chance to knock out a couple more of them if they come in shoot to kill them you understand I understand wait a minute man I'm coming with you no listen I used to throw an expert a good I get close enough to one of them boys I can split them I'm coming with you it's our only chance you start shooting and the whole bunch will be on your neck this is quieter okay let's go you see anybody Chester oh sure he must be up the saloon all right then open the door now if we hear any shots back here don't we will come running take it easy now we got outside and made a run over to some dugouts up the street we could hear the killers still drinking their courage back they're just been the three of us against them we might have taken a chance but well the women and kids in the warehouse we couldn't do that we'd have to pick them off if we could one by one the first shot we fired there was gonna be trouble out to the left of the warehouse in the evening shade I saw the bodies of the two men they shot down a dog was moving around whimpering a couple of minutes went by and then we started around the back and made our way up behind the saloon if we get in by the back door Mr. Dillon you think we get surprised we can't take the chance Chester not with only two guns they get us and you know what'll happen yes one of them is coming out look yeah it's the fellow shot Dave Max he's heading this way you think he's oh Bill yeah I think you can get him from here a little closer maybe not from here he's got two guns on him we need him stay in line with the post we'll cover you okay I saw Houghton's big fist tighten around the axe handle they moved out and down the alley in line with the post my killer never looked up he just stood there head down swaying a bit and their Houghton stopped his arm raised up back and the axe caught a gleam of light and must have thrown it into the killer's eye he had just time to look up and see the thing before it caught him square I haven't done that for a long time I only throw trees and boards I never did it to me before I never killed a man like that Chester got the other gun yes all right here here Bill take this all right we got four now that ought to fix us now look I don't like what we're going to do but it's the safest way we go in there shooting get them fast in the leg anywhere try not to kill but don't give them a chance to shoot back yes sure man you okay Bill you want to wait a minute drink up we're going back now and see if they change their minds all right with me thinking Marshall Dylan out this time and that deputy yeah too many marshals around this country anyway that's enough keep your hands where they are bro all right Chester take their guns yes sir I'm arresting you for murder bro arrest them with you killed my brother got him in the back my brother they murdered him you know something if I wasn't a marshall I do the same thing to you right now it's too bad I can't I hope it hurts when they hang you bro and it was over and I got a feeling like it never happened that there hadn't been time for it to happen but the dead men's women knew that it wasn't a dream the next day a half a dozen of the fellows Chester and myself took the odd laws back to dodge most of them had been hit back in the saloon one died and simmer on before we could get him to the dock but not Brill he was alive when he went to Hayes city with the rest of the boys I was there when they tried him and I was there when they hanged him gunsmoak under the direction of Norman Mcdonnell stars William Conrad as Matt Dylan US Marshall tonight's story was specially written for gunsmoak by Anthony Ellis with music composed and conducted by Rex Corey featured in the cast were Lawrence Dobkin Vic Perrin Bob Sweeney John Daner Lou Krugman Michael Ann Barrett and Ted Bliss parley bear is Chester gunsmoak is heard by our troops overseas through the facilities of the armed forces radio service join us again next week as Matt Dylan US Marshall fights to bring law and order out of the wild violence of the west in gunsmoak tomorrow night CBS radio raises the curtain on a new dramatic treat the theater of stars on the network that brings you Lionel Barrymore Sunday night playhouse and thrilling stories of escape tomorrow night for the premiere performance over most of the same CBS radio stations here lovely Joan Fontaine in the Guardsman it's a sprightly peppery adaptation of Franz Bonard's great french comedy a romantic experience you will certainly enjoy remember theater of stars tomorrow night premiere performance on CBS radio this is Roy Rowan speaking America now listens to 105 million radio sets and listens most to the CBS radio network