 For some of the standard reports about demographics like age and gender and location We made some significant performance. This was a very slow analysis Two weeks ago. We made it a lot faster So, but anyway, can you go to help? I want to see what the date is of your who net go to help So help you want to see the data from No, no, no, no stop on the screen. It says help at the top menu help Okay about About yes, I just want to see what the date is So this is from April 22nd. Okay, good. We've made some improvements Everything works the same, but we made it go a lot faster recently. Can you click on okay? Okay Click on okay to close the screen with the data analysis No data analysis analysis quick analysis the second option Just want to see what options we have here. I think that I sent you some report macro files. I can resend those let's I'm going to go to Um good. Well, why don't we start by this click on exit? I'd like because of the performance improvements I'd like to put in the new software. So click No, not edit exit perfect close that an Exit leave who net completely Okay, I want to update your who net. So let's go to the who net website from Google or I'm sorry. What is that? So I'm going to search the Google mom in the who net website or I don't know you just go to who net org There's no need to search just go to who net org go down a little bit down a little more Okay, stop right there. Can you see the online installer? No too far go back towards the top We simply want to update the software Further up This one further up Further up stop stop. You see it says download No, yeah, yes, okay, you see it Good do the online installer the online installer is faster. It's a smaller file. So click on that Yeah, it's downloading. It's great now that we're doing that. I'm going to just send you an email right now. Um, The lollum and I'm going to put in some macro files. Let's see drive who net macros Yeah, I'm going to zip those Send to zip I think that should do it good. So I'll now email that file to you zip, okay and Macro Report files that I will um these save these two of the macros and Send okay, great. I'm now going back to look at your computer As it finished downloading it Just keep I know it's still downloading Okay, uh Good, I can't see the size. Oh, is it halfway done or less than half? Okay, great So you see my email. Okay, so yes, yes Yeah, copy and paste that into your macros folder So the way how to do it I'm going to copy all the items within the folder Yeah, that's well, okay. No, no, okay. Let's do it a different way close this right now close this Go back to your downloads folder Yeah, this one This is a document perfect perfect cut and paste that cut and paste that into your who net macros folder so cut You go to go to my computer or you'll go to the Windows Explorer and go to the C drive Yeah, who I call And macros correct gate now paste past Yes, now right-click and extract here here extract here Yeah, and then I wanted to so this is also part of the teaching so basically Let's start off at the top This is a series of macros and we discussed those briefly Previously you see that it says can you make the the I want to see the name the name is incomplete Can you make the name column a little bit wider? Just We can see the full names of the file great perfect So as you can see here these macros have different purposes Percent susceptible gram-negative percent susceptible gram-positive I should alerts for quality I should alerts for important species and resistance percent resistance for stephorius and we have especially you see all There's several called isolate listing Summary I think the list that no I think it's just better as a list Yeah, I think that's good. Okay. I'm good. So you see several of them are called isolate listing summary Those analysis were very slow. They are now very fast so you have We can't see the full now can you just change it back to a normal list? Okay, yeah view list because then we can see the full name Okay, so you see it's organism by location organism by sex No, that's details So you at the top of the screen click on view the top menu click on view view View at the top of the menu. Yes and click on Just just titles or list list choose list One good perfect perfect. The list is good. So here you can see the full names You see organism by age group organism by lab organism by location type organism by month organism by sex So it's all of these different ways of summarizing the data good and I sent those to you as a big zip file and that's called macros and reports and you unzipped it here This is useful that if you've made some nice macros at the national level You can easily share these with the people in the country. You just send them the macros you send them the reports They put them into the macros folder and then they are ready to utilize So each of these macros and in the letters MCR and each analysis does something specific for example Can you double-click on the one? Oh, it doesn't matter. You see the one called organism by month Isolate listing summary organism by month Yeah, these one just double-click on that Okay, more applications More apps and whip notepad just put notepad is fine notepad So you see these macro files are very simple and very short It says please this is the name of the macro use the laboratory test It's the analysis is isolate listing summary organism by specimen date by month all Organisms so you can see that the macro is just simply a summary of one of the Hoonan analyses Normally, you don't need to see this but I want to show it to you because it is very simple You know sometimes just easier to edit these behind the screen behind the scenes so close this This is what a macro looks like Okay, and I'll ask you one question. Sure. Go ahead. Yes Yeah What is the language of this Hoonan? I don't understand by the way Can we start from the scratch because I'm actually new for macros especially specific to Hoonan So you are actually telling us You know, I Don't know how can I explain for you? No, I already Question is you want to understand the syntax like what to type here? Yeah, exactly great And the answer is you don't need to know there's I mean, I'll tell you a little bit, but who net made this automatically That's a good thing to do. I'll okay. I'll show you in a few minutes. Has your who not downloaded yet? Yeah, it's finished. Yeah. Okay, so let's let's run it. Let's let's let's update your who not The main reason I'm updating your who not is because the new one is going to be a lot faster But it requires the internet access, right? Well, so it needs the internet access to download it, but you've already done that Right, so just double-click. Yeah, just click on the who that set up Okay, maybe wait me one minute Yeah, okay, so it's not finished yet. Is that correct? Yeah, now it's finished. I see I see. Thank you Great now that it's go ahead and do that and we've been making a lot of changes and improvements recently We've spent a lot of time modernizing the structure and improving the speed So it's kind of a useful for you for once in a while, you know regularly just you know you can ask us what new features there are but just check the website and you'll tell you the date and Sometimes the new features are not useful are not relevant for you. Sometimes they are But there are benefits to doing it That was this update has no bad impact on your existing files Everything all of the things I gave to you are being updated all of your stuff stays the way that it was They're gonna continue good. So let's close that we can minimize or close this. We no longer need it Okay, let's close out of this Let's close out of this Okay, and go to Restart who not so it's simply just updated the who net files Okay, wait for it to start good. So let's choose your laboratory One of things I want to discuss on the call is the idea of a national configuration So let's get that. Let's do that later So go to data analysis and I want to just refresh people how to make a macro clicking data analysis. No, no click on exit Go to data analysis analysis Okay, and click on analysis type. You know, we can just choose for example on the left choose isolate listing and summary Okay for the columns it says specimen date by month. Let's change that so change columns Now on the right side of the screen columns Specimen date, let's just change that for example to your location. Perfect. Yes location click on okay at the bottom of the screen Click on okay Click on organisms and let's just put three organisms. So put s a u ECO What ECO as you wish your coli ECO. Okay. E coli. E coli. Yes, and kpn for klepselin ammonia All right and okay, and click on data files and Let's just find just choose one of your data files Also, this reminds me that you have one lab called zero one a different lab called zero zero one. We can also standardize that Yeah, that's good. Yeah, look, okay Good and let's for something different go to isolates and let's put specimen type equals blood Okay Go down a little more a little more There it is specimen type Good, you can click on to find criteria or you can double click it does the same thing Click on blood is good and click it says include or exclude will include click on. Okay. Yeah Good click. Okay. Click. Okay And before talking about the marker just to begin analysis, I just want to make sure that there's some data here Normally with the not our target. So you will see a few number of labs Then just yeah, that's fine. That's fine. There are some data you see at the top of the screen. There are 74 isolates Yeah, and you see some of them on the left column summer zero one summer zero zero one We will standardize that so they're all the same. Okay. Good. So Originally the code was Zero zero one so later on We just created a new laboratory with zero one only so while we are merging the two data, you'll see two kinds of Yes, that's perfectly fine. It is a bit inconvenient So I will also show you how we can change it so that all of them are zero one Yeah, this is it like that click on click on continue Click on continue and here you can see By look oh the location column is empty so I didn't pick a good field click on continue. Yeah Click on continue and go to analysis type Change the column to laboratory. It's the second column. It's the it's the very top laboratory Yeah Yeah, perfect. Clicking okay and click in analysis So the listing is not changed but now click on continue and Now you can see we have tabs can being to have them as two separate to just be one Okay, and and as you can see most of the data are You know, we have 52 Klebsiella in zero one, but we only have seven Klebsiella in zero zero one So the majority of your data has the zero one code So that we'll talk about that when we get to data cleaning click on continue Good. So the reason I did this is to show you the macro. So click on macros Yes Yeah Good and call this new macro. Just click on new Okay, and we just give it a name. We give it any name, but let's try something descriptive call it isolate listing and summary or dash Okay, that's an underline but yeah, it doesn't matter. Okay put SAU comma ECO comma KPN for the three bacteria that we did and then underscore Yeah, and that is cool. You want to maybe and either bl or blood, you know, whatever you want Okay, you just want to give a name. That's descriptive click that saves the macro name Now it's seven. Yeah No, did you click it should have okay? Okay, it went by there's a delay. So what it did is it you save the name and then you say great So now you have this new file there that you made Isolating in summary state and click on edit right now Click on edit. So as you can see when it made the syntax So personally, you don't need not you do not need to know the language You don't need to know the syntax when it does it automatically. Does that make sense? Yeah, that's good. But you know, sometimes who need is cannot do everything So there are some tasks that can be done using only macros Can you take an example? Yeah, because last time, you know, if you remember I asked you The old condition and also the end condition in that case you cannot do that kind of Task is using the cool it by itself rather you are expected to write a macro like this kind of land Okay No, no, no, no stop the answer that is sort of yes and sort of no What we were discussing last time about the ands and the oars was not macro. That's not a macro feature That was an alert feature. So we reviewed the the alerts. We did that using Excel So using Excel allows you more flexibility with ands and oars So that is a very useful feature with complicated and and oars, but that is not a macro feature. That's an Okay, does that make sense? So if you want to if you want to complicated ands and oars You can do that, but that's not a macro feature. That's an alert feature Okay, and then The alert file. Okay. There is one thing here. There is one. There's only one example. I can think of of something you can do in a macro Manually and I can show you that. Okay. Can you click on edit at the bottom of the screen? edit No, not it. Okay edit Good. So you do not need to know this syntax when it does it automatically But you can edit it easily for example after KPN Go up to KPN Yeah, and type comma type comma Yeah space PAE That's sort of monosurgeon. Oh, yeah, okay, comma Colmar ECL Okay, go down to blood Okay, and blood comma You are for urine Yeah Now click on save So now what we have done is we we have who net made the macro for us, but you can manually edit it So personally myself. I never make a macro out of my memory I just use who not to make the macro after who that makes the macro then I can do this to make small edits to it Does that make sense? Yeah Good, of course if we were to can you and then of course if you go to row one your row one So you see row one it says KPN there Yeah, that's a macro name. Yes. So after the KPN after the KPN put comma PAE comma ECL We don't have to do this, but I just want to make sure the macro name Corresponds with what the macro does so after blood you can you can put blood comma urine So all that makes sense Yeah, click on save. Great. There's one other thing. So There is one thing that we can do here Can you click after the false you see where it says false? Oh And hit enter try to begin analysis begin space analysis perfect He is what I is I s It's the same as the name on the button. Okay, hit enter. Okay, and type organism equals For organisms equal it does not matter. You can type organism or organisms. It doesn't matter okay equals SMA That's right. Hey, SMA Serratium or sessions Like these or I don't know M a m like mother s m a comma. Yeah EFA that's enter a caucus Ficalis comma And EF M enter caucus Ficium EF M Yeah, hit enter hit enter Type begin analysis in Analysis, so this is very it's a little bit more advanced, but it is also very useful analysis and then click on save good and exit So now what will happen is it click on exit click on exit? Okay, and go to data analysis go to a quick analysis Type new click on new report and just as an example, let's call this weekly report Weekly at the top of the screen report name type weekly report Okay, maybe I can search it down Yeah, that's right. You just type it right there. We're giving a name to you've already given a name to your macro Now we're giving a name to the report and a report is simply a collection of macros The types of word report weekly report Okay, we clear report Yes Because we just want to give it a descriptive name that means something to people Now to find the report that you made so you made that report called isolate listing and summary So double-click on that Or you'd be arrow key it means the same thing So we can put here many reports we can put here five reports twenty reports a hundred reports This time we're just putting one report one report is fine. Click on save meant to say macro. This is one macro click on save so we're now saving the weekly report and Save again That saves the name of the file And click on exit at the bottom of the screen click on exit. Yeah Okay, up good. So now we have here a new report. It's called the weekly report You also see below the report all of those standard reports When it standard report I should alerts when it standard for organism and antibiotic results Those are the reports that I just sent to you by email. Can you go down a little bit further? I want to see the reports at the bottom Good a little more a little more. Yeah, good. Let's start with you click on the one called patient and sample statistics Click on edit So this is what I just sent to you by email and you can see that this report does six analyses This report is laboratory by month sex by lab age by lab location by lab location type by lab specimen type by lab make sense Yeah, so basically you did it today for the weekly report using one macro I did it for you With a number of reports and a number of macros So it just basically allows you to automate a lot of these analyses so that you don't have to do everything manually every single time So click on exit May ask you regarding macros Yeah, actually, I understand the clearly what you are discussing. So it's good. So good, but my concern maybe Do macros are case sensitive or not? For example, they're not if you are right in big enough Excellent question. No, they are not case sensitive Okay Yeah, and also, you know, I told you this I told you to put You know a capsule a comma space PAE comma space. It also doesn't need the spaces I like the spaces because it looks nicer, but we try to make it small details Do not matter. It can be upper or lower case. You can put extra spaces So if you find any problems, let us know but these these are excellent questions These are the same questions. I would want to know but no it is not case sensitive Okay, great. Let's start off with your weekly report click on the weekly report Click on data files Good, and we can choose the same file that we chose before or we can choose a different file Oh Okay Okay, no, I under this is an important different issue for us to discuss We're gonna take a break now from macros click on okay Click on okay Yeah, just cancel at the bottom cancel just click on cancel. Okay. It doesn't matter click on exit Again exit. Yes exit Okay Click on data analysis. I just want to try one more thing because we've had a lot of compatibility issues It's important for us to discuss it and this could be a good time to do it click on data analysis Yeah At the bottom click on data files Okay, okay, and try to choose the file try to choose the same file we chose before Okay, yeah So you can see there's some something happened and So so I'm gonna so we're gonna take a break from macros and reports This is an important a very important compatibility issue for the last 20 years Who net is using a very simple old-fashioned data structure called debase? Problem is Microsoft it's making it more and more difficult to use debase files So we're seeing a lot of laboratory starting to have exactly this issue that we just saw it worked 10 minutes ago But it's not working now So we're gonna talk about an upgrade click on cancel or okay. We're going to leave the screen Good. Okay. Go to click on exit Okay, go to data entry and click on update data files to SQL light I wasn't planning on covering this during this call, but since it came up, it's important. So click on select data files Choose all of your files. Yeah. Okay. No, no, we can do them one at a time Or we can do all three at the same time All three are all three of these are valid files correct Yeah, but they are the same actually one of the data is just encrypting the patient information So the one I sent you this one. Yes. Yes. Okay. Great. Let's choose all three files Oh, yeah, three files But say it's not everybody did a video. Oh, no, why is that is this is supposed to be this is supposed to be okay You know, maybe it's not on the website yet. Oh This is how I make this one What is this one? Um, okay, I thought this was can you click on cancel? Okay, click on help I'm sorry. Click on cancel again Click on help Click on about. Oh, this is from last week. That's why I understand why click on. Okay. Okay. I'm gonna show you my computer screen Okay, I can do that screen Okay, uh, so Mikael if you can make me a presenter share So here you see I have this one called who net test So I have who not 2020 here I have who net 2020 test here the feature that I want to show you is in this new test version. There it is, okay EPH I'm data entry update data files to SQL light and I'm going to select the data file and I'm going to all files. So where are your data? Oh I know they're not in they're not in the who net test folder. They are in the normal who net folder when that data And here here are your data. Okay, so you can see on my computer works fine Okay, I say, okay Good so here you see that the original file is on the left the new file. We're putting on to the right the gain conversion It's been completed and now when I go to my folder Here you see it says nrl one year encrypted zero one sequel light So I'm going to send this file to you Or we could update your who net either way would be fine. Let's update your who net But not quite yet. Just because that's going to take a little bit to do I'm going to say, okay, and the long and attach and Here and if I go to who net data start a star zero one star and there's a sequel light and say, okay and SQL light data and click on Send can you check your email? Okay, so Miguel I want it. Let's go back to I'm going to stop sharing my screen Stop sharing my web. Oh, no my webcam not that but my screen um good So should I make Zalaam? presenter again I did that So a lot of them you should have received the request Yes, so so we've been For the last three years this issue of debase incompatibility has been slowly increasing and each time we come up with this temporary fix and There from February to February March April it took us three months where we replaced that we offer Well, we didn't replace me. We're still there. So debase is still there But we're having more and more compatibility issues So we're going to start recommending people switch to sequel light to avoid the exact kind of compatibility issue that we just saw Did you receive the file yet? Yeah, maybe no not yet Okay, check your inbox again. Oh, of course, let me make sure it left my outbox. You sometimes you get stuck No, it did leave so it should be in its way As it arrived, I'm not looking at your screen right now Okay, now we can continue. Yes. Did you save it to your who net folder? Yeah, yeah, I can find it from my desktop. That's fine. That's fine. Okay, great. Um, good Uh, we go back to your screen. There it is. Great. Go to data analysis normal data analysis And go to data files, I just want to make sure that it works So go to your desktop and change this to all files, you know at the top just change it to all files What was the name of the fight? Same thing NRL at the beginning of the name is the same. It's simply instant sequel light. It's number four It's the go down the one that's a sequel light. Good Yeah Good that that's fine. Good. That's fine. Click on exit. I just wanted to make sure that it worked Good so basically if you're if you're if you do not if who net has no trouble with your D base files There is no need to go to sequel light But we thought today there was a problem. So that's why we went to sequel light So in the next six months, we're going to encourage people to start moving to sequel light because it's more compatible It's faster. It's more modern. It is a lot more features for security like we can do passwords and things So over in the next six months, I'm going to be writing to countries to recommend they switch over to sequel light Anyway, we can discuss that's not the purpose of this call, but it came up. Let's go to data analysis Okay, but what was the reason behind? What is that? What was the reason? You know, what was the reason having Not a compatible data. Well, okay Um, I already know the answer to this question. Have you in your life ever seen the software debase? Actually, I'm not actually using the debase Yes, I already know that I already know that because D bit the heyday of the high point of debase was the 1980s It still existed in the 1990s It still existed but it went out of fashion very quickly Because it was replaced by access and Oracle and my SQL and all these other things. Yeah. Well in 1994 I For the who net data structure, I wanted to use Microsoft access but in 1994 access was too new and had too many compatibility issues I That time it was access number access to so access to I wanted to use this the who net data structure But it was too unreliable. So the next best thing was debase because debase was widely used at the time It was on its way out, but you know, it still existed and it was compatible and it was simple So I made the decision to use debase in 1994 and even in 1994 it was on its way out in February of this year in the last few years Debase is not a Microsoft product. So in the last few years debate windows is making making debase files more and more difficult to use and Then it we used the technology called No, we use the technology in who net called DAO stands for data access technology It was later replaced by a DO. It was later replaced by a DO net So it of this year Microsoft put on quote temporarily removed support for DAO But temporarily They didn't say so so in February. We said we have to get right We have to move on from debase to something more modern So that's the entry to your question is that we've been trying to keep debase going Year in and year out a year after year and it's just becoming more and more difficult Debase continues to work very well for the large majority of who net users But more and more people are having the exact issue that you are having now Not a valid file and it is a valid file, but who net does not realize that because the DAO stuff So that's why okay. Thank you Now we're going to go back to our previous discussion of the markers and reports. So go to quick analysis and Go to weekly report and else and now we're going to choose the sequel light file. That's on your desktop good Okay, and click on okay and good So you can you chose the data from zero one, but you can choose the data from zero two zero three zero four This report is not specific for zero one We made it with zero one, but you can apply to any laboratory or any groups of laboratories We could choose all of the data from all of Ethiopia So that's one of the nice things about the data files here is that whatever you choose here will be used for the analysis Click on begin analysis and What you are going to see is first the step aureus the E coli and you see those five pathogens listed at the top Yeah Okay, click on continue That's the list. This is the summary look on continue again And now you should see the other pathogens You know, you see the sorority of marcessons the enterococcus focaleus and that's because we did begin analysis So you remember how we did that we had a first group of organisms begin analysis We had a second group of organisms begin analysis So that so you can use the same macro to do many many many different species or specimens or other things Simply by manually editing the macro Okay question question So we can do a lot of macros within a single. I don't know how can it you know, you are you are doing two macros on The same page, right? Well, sort of what we're what we are doing are two Analyses using the same macro. It's the same macro, but that macro has multiple components Okay, so if the multiple so all we did it's basically exactly the same analysis except we change the organism So if the macro is very very similar, that's what I do begin analysis make changes begin analysis make changes So if it's different variations like different organisms different specimens, I do it inside of the same macro On the other hand, if the macros are completely different, I just make a different macro Okay, okay What you typed in begin analysis that is the only Undocumented feature so begin analysis you type that manually that is not available Automatically you do have to type it manually. So that's why I showed you how to do that manually Look on continue Maybe if we left blank without using begin analysis, what will happen? Well, then it'll just it just runs to the end So that's how so normally who net does not say begin analysis So if it does not say begin analysis when that begins the analysis once it gets to the end of the macro Okay, yeah So that's why the macro that I the macro that we first made did does not say begin analysis at the end because there's No need it automatically begins the analysis once it gets to the end Okay, click on continue and so that's simply the same exact analysis, but with the second group of organisms Click on continue Good now I want though that's the new report we made together now I want to show you some of these other reports which are going to be valuable for data cleaning and epidemiology So everything till now is sort of been teaching but now we're it's still teaching but we're doing this for real So now we can focus more to interpretation of your data So go down three more. I want I don't want to do the alerts We're gonna do all of them, but let's start in a in a nice rational sequence. Go down a little more more Good patient samples statistics is a good place to start Just as a reminder, you don't have to do this but just as a reminder click on edit And what this is going to do is it's going to run six analysis laboratory by month Lab age by lab location location by lab Okay, click on exit and you can add to lead you can change those however you want Okay, now the first time we do this we click on begin analysis So it's going to do six analyses. This is analysis number one So let's see as you can see it's two different quote-unquote laboratories. You have laboratories zero zero one And you have laboratories zero one Yeah, what's interesting is that you're used hospital zero zero one in February March and April And then I made a comeback in August and September Yeah, somebody must have just chose the wrong configuration file Okay So actually we are using we are using two computers desktop and my laptop so The configuration in my laptop is zero one. It is exactly the same as the other sides But the old desktop The code was zero zero one so two confirmations On the purpose of this call the purpose of this call is not to clean your data The purpose of this call is to find issues On a set on the next call then we can talk about how to clean these things up So what what it would like a duration to be the same on the two computers I want all of these to say zero one So right now we are finding issues on the next call. We will talk about fixing issues Okay, okay, so it's basically cleaning in two parts part of cleaning is finding the issues the other part of cleaning is fixing the issues So okay, so that's a that's a cleaning issue. Let's see. What else do we have we have that? You know from the first row we have 477 isolates from 416 people to do that who net is using either the patient's medical record number or the patient's name So there are repeats, but they're not a lot of repeats and Okay, so I can see the graph for hospital zero zero one now click on the graph for hospital zero one Of course, I'm not hospital but laboratory click on the second graph zero one So now you can see this is laboratory zero a lot for March because that was mostly zero zero one You use the other computer and none for September because you use the other computer Now let's click on the month of January. Let's click on the graph for January Down at the lower right-hand corner So you can see the distribution in January. It's all zero one look on February and Good so that you it's a combination zero zero one. So so this this lab this analysis is called laboratory in the rows months in the columns Now click on continue Okay, and here you see we have sex in the rows and the labs in the columns So, you know, for example, it's 45 percent female 55 percent male Here you have two labs except these two labs are exactly the same lab But if you put in laboratories, you're two zero three zero four you can put all of the laboratories into this analysis And then you can see in the columns on the left number of isolates number patients the national distribution of male and female But you can also see the distribution male and female separately for each of the laboratories Okay, so this is sex by lab now click on continue I think this one is age So here you see the age distribution for example at the lower right-hand corner click on zero one Let's look on the graph for zero one Yeah, I see it all down at the bottom in the columns No, no the box called columns you're in the wrong box Columns zero one. Let's do the second one which has more data Good. So here you can see I See that I have a formatting issue that we can fix later You see you have a nice distribution here the most common age group you have is age 25 to 34 Okay You do see that the group less than one is also a very big group. In fact, it's the biggest group Logically it should be on the left side of the screen But I didn't realize that so the babies are on the right side of the screen I need that to move that back to the left side of the screen so it makes more logical sense Let me just make a copy of that. Let me discuss it I'm gonna make a copy and I'll discuss it with the programmer later So I'm going to word and I'm going to put the word. Okay, great. I'll discuss that with him later. Okay Okay, so you see the value of this kind of demographic view And you do and you do have a lot of babies is that correct? Yeah, that's true. Yeah Because basically one of the reasons we're doing this is for epidemiology That's a good second reason. The first reason is is quality control Does this make sense to you if it doesn't make sense to you? There's probably a mistake if you look at one of these graphs and say that doesn't that doesn't seem right You just see why you think it's not right. Okay Yeah, let's take one. Yes if age information Units or treats Information Well, you see on the right-hand side, it says unknown Where is it The light the on the graph the last graph item. It says the one that go down to the graph. It's unknown. Yeah It's unknown. Yeah, that's missing or it's missing. It means we don't know what the ages missing means unknown Go to the bottom of the table drag down to the bottom of the table I want to go to the bottom of the table No, that's the bottom of the table. Yeah, it's the last row go to the last row of the table Sorry go to the last row of the table The last okay So there you see Yeah, unknown missing it means the same thing. I am very pleased you have very complete data out of how many do we have? We have about 1,800 records and out of 1,842 of them the ages missing Sometimes the age is missing because we have the patient's ages Sometimes the age is missing Because it's not a human specimen. It might be quality control. It might come from a sink It might come from a water sample. It might come from food So, you know, so if it's from a person, we would like to know the age If it's a quality control stream, we don't need to know the age So I'm very pleased here that your data are here. The here the age is very complete Maybe Maybe age a new unit For example, one unit this age is less a Three days. So we were entering this kind of data 3d to indicate the day That's not a problem who that would automatically who that that's what we want you to do who now would include those in the people less than one Okay They would be included under less than one Also, you might wonder what we have the state say it straight. I don't like these age groups 5 to 14 15 to 24 I don't like these age groups. I would prefer 10 to 19 20 to 29 We have these age groups because these are the age groups that debajo ask for these are the official debajo age groups I don't like them, but that's why you see these age groups Okay, good. Now, let's click on continue. There was was analysis number three There's analysis number four. It's either location. So the look so you are not entering a location I think you are entering a department, but not a location So you are leaving the location column empty, which is okay. And that's simple what that's the interpretation of this So this is not interesting because you're not using this particular field click on continue and this is location type So you can see most of yours the number one category is I see you Well, I'm sorry the number one category is the first row the location type is missing Yeah So what is the difference between on moon and the first the first and the last The last one means somebody typed it in somebody typed in you and cake Okay, yeah, okay. Yeah So you and it has one of the location types is unknown. So that's what the person typed unknown the first one means it's empty Click on continue So this is a comment. This is not about this is not about data cleaning or this is about going back to the laboratory and say Thank you in January. You were 70% complete. Let's try to do a better job in February Let's try to do a better job in March so that we can look at the completeness improvement over time Okay, this is not the distribution by specimen type. So you see where it's you see the heading that says number of isolates Click on the heading once Number of isolates click on the heading click on the heading once And I mean You did it exactly correct click on so what that does it sorts it so the most common one is at the top of the list So the most common thing that you have is blood Followed by urine followed by pus Okay For example at the bottom in the lower right hand corner of the graphs Click on zero one. I want to see the graphs for zero one So I can see the most common is blood Followed by urine followed by pus. It's exactly the same data. They're in the table, of course I'm very pleased because or no missing data. There's nothing unknown. You have always entered a specimen type Okay Good click on continue and that was the last one So does that make sense how easy how nice it is? This is very valuable if you're looking for data completeness You're looking for epidemiology. You're looking for comparison between 10 different hospitals So this macro serves a number of purposes Okay I have a question. This is firm. Yes, can can this who net allow a country to program age specific? You know age groups country specific age groups rather than using the WHO standard age groups That is definitely on our list of things that we want to do And in short, no who not cannot do that, but it is planned okay, I Especially I will for one. I just I think it's prettier You know like 10 to 20 10 to 19 20 to 29 or it would be nice to do like zero to 18 19 to 64 65 up Or people who work in pediatrics people who work in pediatrics often want to do less than one one to four But so there are different reasons why different people would want different age groups. It's definitely something we want to do We have spent so much time in the last few years on who net on modernizing the data issues replacing everything I'm very happy to see how completed all aspects of the modernization now going forward start working on new features improved performance So so this is going to be a good time for us to start thinking about things like configurable age groups Yes, but I guess we can still export the isolates and Make our own age groups in another software like Excel or some statistical That's it. So good. So let's see and it's we have an hour left. We still have plenty of time You can do things like that with who net Can you click on exit right now? Okay, go to data analysis Data analysis Okay, and go to analysis type and let's call this isolate listing and summary. I Do not want the list. I just want the summary. So on the left side of the screen click on summary On the left side of the screen. Now, that's the right side of the screen the left side of the screen click on summary He saw the select the yeah Well, both was selected I don't you did it perfectly. I wanted number two summary I don't want number three both because I don't want to see the list the list is too long Unless it's not interesting to me right now. Okay, and good and good. Let's click on okay look, okay and Click on organisms type all and hit enter Good click. Okay Click on dated fields and select the sequel light file Okay, no you have to at the top of the screen change it to all files. Otherwise, you're gonna have this unfortunate message So Never mind. Okay good. Good. Instead of all files go back to all files That drop-down box. No, no, no stop that at the top of the screen. You see where it says all files Yeah, change it to sequel light. That's just gonna be more convenient now. It's only showing you the sequel light file Okay, good select that click okay and What else? Okay, good now go to isolates Go to age Yeah, define criteria or double click. It means the same thing and for example here type 0 to 18 Greater than or equal to 0 Beetle 0 and then then 18. I don't I don't I'm just making these up But yeah in the United States, that's what our range for pediatrics in other countries It's more a lot of countries thing is 15 instead, but you know, I'll just go by the United States standards So put 19 and put 18 there 18 1 8, okay. Yes. Click. Okay. Okay. Good. Click. Okay. And let's just see what this looks like click on begin analysis Are the organisms in the patients age 0 to 18 Okay, click on continue click on macros New macro, let's call this. I don't know organism summary hyphen your organism summary Hyphen or underscore No, no, no, no, no That's okay, but I meant afterwards Okay on the court age Ages 0 to 18. Okay. Good and two is misspelled Well, I mean, I think that's an I don't know if that's an award. Okay. Good. Click on save click on save The first is saving the macro name the second is saving the file name. I Want to show you a different way to edit this now Click on exit Exile not edit click on exit Exit click on exit Click on exit The whole the whole net we're leaving who net right now Okay, or minimize it. I don't really care Okay, I want to see the file folder. So can you now go to my computer who net macros folder? So this is the new part of the lesson go to who net macros who net macros Okay, so you see that macro that you just made called organism summary Ages 0 to 18 Yes, so copy that file twice so copy and paste twice Okay, good now makes the column wider so I can see the full name Good perfect. Okay. No, you pick you pasted it once. I want you to paste it again Yeah, the first one with this one and the second one is this one. I want a third one I want three copies of it Okay, okay great food Perfect now what we're going to do is we're going to change the file names. So go to one of your copies Rename and let's put it. Let's change it to nineteen to sixty four I'm just going by United States United States, you know ranges 1964 so these are basically Non-elderly results adults Okay, and you have an extra space after the four Doesn't matter okay rename this one to You know, we can say greater than 60 You know, you can type the words greater than 60 Whatever greater than or equal to 65 or you can say greater than 64. Just put it greater than simple Actually, you know That's fine, that's fine type type 60 type 65 hyphen 100 or hyphen, you know, just put some big age Yeah, that's fine, okay good okay, and Good good, so we need we changed the name of the macro But we didn't change the macro itself So double click on the first one double click on zero to 18 This one is called a this one is correct. So you see isolates age equals zero to 18 So that one we don't have to change. We're just gonna leave that one the way it is. Okay, close the way I went through the language What example I? Went to know this language for example. No, I already understand I understand I personally do not know the language So what I do is I have who net making it the first time So what I do is it make it manually and once you have it manually then you can edit it So, you know, if you do this enough then you start to learn it But we I don't plan to document the language because who net does it for you? So so the first time make the macro manually once you made the macro manually then edit it however you want Okay, the reason for that is who net has so many options and so many features We continue to change them. We continue to add more that you know It's just easier if you make it first using who net and then manually edit it afterwards Also, you will see the language is pretty simple, you know, you'll learn very quick. They simply by looking at these examples Okay, let's let's okay good, let's close. Okay. Yeah, just change this to 1964 Okay, and then you see the first row there the macro name is zero to 18 Yeah, we changed that so as you can see we have the file name and the macro name so we change them separately But it's not a problem, right? Not a problem. Yeah File save file exit. Okay, and then we do the same thing for the last one the age 65 We've got maybe 120. I mean you might have some people 101 102, you know Just put something that we think is a reasonable upper limit Maybe can we do this one greater than something? I See if I remember correctly, I think I think you can just get rid of the one I think if you put 65 hyphen, I think it will work Get rid of the one there. I think this will work Yeah, the upper age group in the US is 124 the official Yeah Oldest person ever to live with good documentation is Jean Camont. She was a French woman who died at 122 and Maybe 10 months. So the oldest person ever with proper documentation lived to almost 123 So 124 makes sense She was a very very funny woman She said what did she say she said oh, yes, so yeah, they told her they asked her You know, they asked her oh, how are you doing? Oh, I am just here waiting waiting for death and reporters And they said oh madam come on you have such beautiful skin. Yes, I only have one wrinkle and I'm sitting on it so 22 she was a comedian. Okay. Good. So let's save this Yeah, I saved already Let's close this Good, so let's close out of this And You know good And just restart who net so go to go to open laboratory go to data entry. I told you to put 65 hyphen I think that is correct, but I am not sure So you asked me about learning the language. I'm going to show you what I personally do go to data analysis Go to data analysis Go to isolate Go to isolates No, I did not want you to do that click on okay. Do not do this out Look on okay Leave data analysis Leave data analysis Okay exit good go to data analysis data analysis Go immediately to isolates I saw it these ones Now go to age And you can just double click on it. It's faster than to find criteria. They mean the same thing. Yeah Okay, and now just put 65 in the top box Click on okay Okay, click okay So who net does 150? Yes, click on okay and click on macros click on new macro new Just type the word junk junk Test or whatever junk J. You and get Click on save Click on save save and now click on edit So here you can see so I just made a quick minimal minimal macro Because you asked me the syntax and the answer is I don't know the syntax I just rely on who net to know the syntax So I just make a little macro then what you can do is copy that row copy that row right now click on copy highlight the row No, no the last row. No, no, no just the the only row. I'm interested in just highlight the last row Click on copy Yeah Good you copied it controls here something great. Yeah, click on exit Okay, let's find the marker that you made. I forget if it's further up or further down Organism it's an alphabetical order go down further. There it is. So click on the 65 and above Click on edit click on edit at the bottom of the screen No, you have to click on edit first. It's at the bottom of the screen Yeah Now highlight that row and paste we're gonna replace it with the good version of the row So put on save Yeah, so I'm looking this gives you a better comfort at Editing so I never create a macro from scratch because I don't I don't personally know the syntax myself I use I use who not to make the macro and then I manually edited You know because editing it is very simple. I just don't personally remember all of these details from scratch Yeah, thank good click on exit click on exit click on data analysis Click on quick analysis, let's go to that weekly report that you made Look on edit and right now your report has one macro in it go down to the bottom of the left Go down to the bottom of the left Good and select all three of those organism ones And you can select all three at the same time good. Yeah now select those Click on save You can agent Okay, now choose your data file at the top of the screen change it to sequel light or it's on the desktop it Click okay Macro click on begin analysis Good, so this is the macro that we made about an hour ago click on continue. That's the listing Okay for five species Summary continue now we have the listing for the other three species Continue That's exactly what we did an hour ago now click on continue Now it's going to do the new macros that you just added so here you have eight categories 0 to 18 Click on continue 19 to 64 continue So for an answer to your questions. No one that does not allow you to change the age groups That's fixed But in the way that I just showed you you can make up your own macros and you create your own mage groups You have to do the age groups separately and then you can combine them later Okay, does that help? Yeah, it's a very nice example Yes, so click on continue Click on exit click on file Click on settings Configuration Close to the bottom. No, no, it's very close to the bottom configuration. Oh Where is it? It's close to the bottom Okay, yeah good So here you can see you can configure the look file locations Click on font All right Fonts click on cluster alerts. This is for outbreak detection. That will be a subject for a future call Click on cluster alerts Okay, so we'll discuss this on a later call about outbreak detection click on caliper Caliper is for measuring disk diffusion zone diameters. So we'll talk about these features later caliper data protection So we have expanded who nets features for protecting, you know about Delete so I've you already saw the who net encryption feature, but we've expanded it This is an expanded version of the encrypted feature Okay, the reason I'm showing you this is later. You're going to see another sheet here for age age groups Okay, so this configuration error we will continue to expand to allow more Configurability more customization. Does that make sense? Yeah, I have one additional question. Sure Is it possible to create a new variable on the base of the existing variables? No, it is not Maybe in the well if the answer to your question is who net does not allow you to do that But you can do that using Microsoft access So personally like sometimes, you know, sometimes I do this a lot when I'm cleaning the data One hospitals has super flocks in five the other hospitals has super flocks in ten The super flocks in ten is a mistake and I want to move it into the super flocks in five column So a lot of times who net does not allow you to do that, but I do that personally myself using Microsoft access Okay, that's yeah, that's good, but you know the reason why I asked you these questions. Yeah You know Who net Gives you Many variables that can be used for microbiology But if I need additional variables, I can create using who net actually But some pupils can use excel For their that entry after the internet the data in excel they want to convert that excel to who net yes So can we Bring all the variables that are found in the excel into who net is it possible? Yes, is it possible all the variables all of the variables. Yes, you can Okay Let's see. Okay, so you do that in back link So, yeah, can you click on cancel here? So the reason I showed you can configuration is that in the future you will start to see more and more options Including age group definition We also want to put their definition of a patient, you know, is it the patient ID? Is it the country and the lab ID or is it the age and the name? So we're gonna you're gonna start to see more options there for configuration. So can you click on file modify laboratory? Data fields, so you're familiar with this screen. Yes Yeah, so go to modify lists Good. So you can add and create a lot of new data fields here Backlink has exactly the same screen. So click on okay Let's leave who net completely. So exit out of who net or minimize it. I don't care Save changes. No, we didn't change anything. Okay, either minimize the other time now open up backlink Click on new format. Okay. Click on file structure. We have to answer one of the antibiotic questions. Click on antibiotics Click on dis diffusion Click okay We have to enter that antibiotic question before the next part which is important Look on data fields the ball bottom of the screen data fields Yeah Okay, click on modify the list of data fields This is exactly the same screen that you see inside of who net Click on modify list So so this is the same as who net so you asked me if they create a lot of files in Excel Yeah, you know with like diagnosis or county or anything like that Yes, you can change backlink to capture everything Okay, that's great. Yeah. Yeah, personally, I don't want to capture everything I want to capture the things that are interesting to me You know like they might have things I really don't care about like phone number or something like that So, yes, anything you want to capture you can capture by doing this Yeah, so maybe the question asked by fun We do have three age groups, right? Yes So we can create a new variable using x in That contains three groups of age He is smart that is a very that's a very clever idea I showed you how to do that as three separate different analyses But in excel if you created your own variable called age group, then you just call your variable It's called ephi or Ethiopia age group. So then when I would easily allow you to analyze your different age groups So that would be a clever way to do it by editing it in Excel Okay. Yeah Okay, thank you very much. Sure Okay, good. There's some other things to discuss in backlink, but that we discussed backlink for Vitek last time We can discuss Vitek for Polytech Vitek for Excel another time or I forget did we do that? Did we do I? Think we did backlink for Vitek. I don't think we did backlink for Excel last time. Did we? No Yeah, we did but so your question is extremely appropriate for this backlink configurability option Like as another example you talked about creating a new column for the age group and yes backlink and then capture your column for age group That would completely Satisfy Fern's question where you make the age group on your own in Excel before it gets to who next? Yeah, we'll allow you to do that inside of who net later. Okay? So that's one example a different example is you know, sometimes I've worked with hospitals in Excel They have one column for the age and a different column for the age unit It'll say in one column. It'll say five in the next column. It'll say days months or years Meaning the age is on the ages in two different columns at the present time backlink is not yet smart enough to Combine those two columns together I would like backlink to have the flexibility to say that age is equal to age plus age unit We do plan to do that in the future It's not difficult to do but we got a lot of different things we're trying to do so right now if a if a hospital has a data file with the age in one column and the age unit and another column in Excel I use a formula to combine the two age groups to combine the two columns together So if one column says five and the next column says D, then I have a new column that says 5d So that's basically cleaning the Excel file a bit just so that it more closely matches the who net in the backlink logic Okay, so let's continue. Let's go back to data analysis and quick analysis Good. So we have seen the third standard report now Let's click on this. Let's click on the one that calls unit standard report organism and antibiotic results So the last one any questions on the last one the last one is very well Let's go one more comment on the last one click on the last one patient and sample statistics Click on edit. So the one on the right you see that I gave you a macro called location by laboratory Can you click on it location by laboratory? On the road the right Okay, location So this macro is not useful for you because you are not entering the location You are entering the department. I believe if I remember correctly, okay? So normally other sites, sorry other sites. They have location the only site that cannot capture this location information is the national reference lab So other sites can use this this macro, right? This brings up a different issue sometimes hospital one did it completely correctly Hospital two did it completely correctly, but they did it in a different way It's just less convenient because you know hospital one is one way hospital two is another way Both of them are correct, but it just makes it harder to combine the data So we could discuss that later as a potential issue so that we want all the hospitals to be as standardized as possible For the things that we care about If there things we don't care about, you know, if one has diagnosis and the other has the name of the doctor And the other has the urine colony count That's not part of my national protocol. I don't care if that's standardized, but the things I do care about I do want that to be standardized Okay, great. So yes, it's important. So for right now for EPHI this one called location by laboratory It's not useful for you because you do department But for the other hospitals it is useful for so for the other hospitals I would leave this in For EPHI I would also add department by lab because right now I'm not getting information about department here You can make your own macro. You can edit the one I gave you I gave you one called location by lab All you need to do is replace the word location by the word department and then you can use it for the EPHI data So basically we're trying to help you as much as possible, but there is always room for additional customers optimization An optimization Okay Great. So my comment there was for location. It's not useful for you Department would be more useful for you, but location is useful for the other laboratories Okay, click on exit So we're now finished discussing this one called patient and sample statistics Now let's do the one called organism and antibiotic results So let's click on edit and let's see what this is going to give you So this one is all about organisms and antibiotic statistics So it's organism by lab organism by date organism by sex organism by age group organism location type location specimen type and After it does all of that it will then do the percent resistant intermediate susceptible in detail for staph aureus and E. Coline and Then it will do the percent susceptible for the gram positives followed by the percent susceptible for the gram negatives Is that okay? That makes sense Yeah, great. So let's click on exit. We're not changing it. I just wanted to show you what this report does Click on exit. Good. Good. Now. Let's click on data files No, no, no, stay on that screen data analysis quick analysis organism and antibiotic results data files Perfect, and now go find your SQL life file. It's on your desktop to SQL life. Yeah, perfect. Good and Click on okay and begin We're saving all this to the screen, but of course we could also save it to an Excel file Okay, so this is now organism by laboratory and of course you've got the two different versions of the lab But if you had all 20 labs here, this would be valuable as a national picture The columns called number of isolates number of patients is the national picture and then after that you see the different laboratories individually So good. This is organism by lab now click on continue and this is now organism by month Okay, as an example in the lower right-hand corner. Let's look for the graph for E. Coli It's an alphabetical order. So just go down to Escherichia coli here We can see the distribution month to month of E. Coli. There are a lot of E. Coli in November sometimes that means there's a lot of you know There's an outbreak sometimes it means data entries incomplete or sometimes EPG is different because you know hospitals usually have a pretty steady amount of volume every month a similar number of patients come in National reference lab it might vary more because they're doing research projects and this than that and the other So when you look at this what you might see is that some months might be missing You might see You might see data from the year 2040 that would be a typing mistake. So I first before thinking of epidemiology I'm always thinking of quality issues. So here I have January to December for the year whatever 2018. That's perfect If I see data from 2016 2010 1962 it usually means somebody made a typing mistake in data entry. So it's part of quality review I'm a little surprised how few there are in October and how many there are in November But you know if it's if it's not surprising to you then there's no need to investigate it Well, you want to look at for things that don't make sense to you Let's see let's go to staff or is I start with the common ones because the common ones highlight, you know Some big issues like missing months step Good, so you see there's a lot of staff for us in the first half of the year and then it goes down Then it comes up again You know if you have a reason great if you don't have a disease and all So I am I am focusing mostly at this time. Does it make sense? Are there months missing? If it makes sense to you then we're getting about epidemiology and then that you take over because you are epidemiologists Okay, let's click on the graph for January So here we can see that the most common organism quote-unquote is xxx meaning no growth Yeah, we did discuss a lot previously The value or lack of value of no growth. Yes, there is value to them But it's also a lot of extra work as you can see the large majority of data entry here was for the no gross and If laboratories have a small data volume, I think it's a reasonable request a small data volume If they have a laboratory information system, it's also easy to get the negatives usually But if they have a large data volume or if they just don't have time if they're so busy with cove it I would be from my perspective It's okay to leave out the negatives because it's a lot of extra work and it gives a little extra value There is value there, but it's also a lot of extra work. We had the discussion previously. Okay, so this analysis is organism by date Look on continue and this is organism by male female So for example, well, it's good Yeah, click on click on female and there will probably be a lot of E. Coli's in The graph so yes, of course, there's the xxx no growth It's the letters a little hard to see is that E. Coli? Yeah. Yeah, this is E. Coli and What is the other one KP is what's the one? Is that club? What is that? That one that one is actually no growth because no pathogenic growth. Oh, I see Let's go to the column heading. You see what says number of isolates click on the cal column heading once Sorry go to the column heading in the table go to the table number of isolates click that once And click it again So yes, as you just pointed out the majority are no growth and no pathogens found Which is almost the same thing Followed by E. Coli. So the number one pathogens in in females are E. Coli eclipse yellow Let's check them out. Let's check the men click on M Do the same thing. Let's sort the database number of isolates go back to the table. Oh, no, never mind You see okay in the table click on the letter F once and click on the letter F again Good and click again. So we can see that females are E. Coli 47 Cepcielus. So E. Coli is by far the most common organism Let's do the same thing for the men So click on M once the column heading once and Again, so for men the most common pathogen is staph aureus Whereas E. Coli is number three Yeah, the men have a lot of the women the the men and women have a lot of the same diseases Of course, but the women have many more urine infections than the men do So for the women E. Coli is the number one pathogen, but for men E. Coli is the number three pathogen So that kind of makes sense. You always want to make sure that reality checked if the data makes sense Okay, good You know, for example, let's go to the row graph go to the row graph and look for staph aureus The graph area right at the bottom So you can see there are a lot more staph aureus in men than in women Now go up and do the similar graph for E. Coli and you can see women. They're more E. Coli than in men So these are a lot of the pathogen like pseudomonas are probably pretty similar if it's a hospital infection Well, that's enough of that. Click on continue. This one was organism by gender and Now we're seeing organism by I don't know by age group Okay. Yeah, my age group here Of course, it's my age groups But if you put your variable if you put Ethiopia age groups, then the three columns are going to be your variable rather than my variable So yes, if you do that with Excel put it through backlink. You will be able to do this now with the age groups The way that you would like it to do them Okay, great. Um, I am glad that the less than one category is on the left. What's supposed to be that's good Okay, click on continue That's organism by that was by age. This is by what is this by location type emergency inpatient outpatient. I Don't we're not going to go through all these right now click on continue And what this is the location, but that's the column is empty. So click on continue It's not useful for you if you would want department for that Um What is this this one a specimen type so I can see BL is blood Okay, you know, for example, click on the column heading for blood. I want to sort this by blood Sort by blood once Twice So the most common pathogen is therefore is follows a surprise to me Bercal Darius apacea Do you have outbreaks? This is not a very common organism, but for you it is It's the number two pathogen in blood. Oh, I'm sorry. No, I made a mistake number three number one Yeah, follow by staff follow by Bercal Darius That's very common. Okay, let's do the same for the urine. So so let's sort it on urine Urine column towards the right that you are Towards the right you are click once click again So not a surprise the number one pathogen is E. Coli followed by Klebsiella followed by mixed and Bercal Darius nowhere to be seen, you know, it might be down further But so you can see that it's quite different for some of these key pathogens You also can see that the three most common specimen types you have her blood pus and urine Click on continue, I don't know what's coming next Okay, now we're on the percent resistance for the staph aureus We're going in sequence through each of the macros now click on number tested at the bottom of the screen I want to see the graph for number tested I like to look at this because this number tested the last graph Yes Good this tells me what drugs you're testing How often you test them? I'm starting at the left I'm starting at the left penicillin is correct Oxicillin disc is not a correct test staphoxidin disc is I was okay. Tobers, okay. Sipros, okay Daps, okay. That's reminds you through micellanesal it. These are appropriate drugs Um, let's see Yeah, so we discussed a lot about the oxicillin last time that the staphoxidin is the disc you want But you know, so I won't go into the detail of the explanation because we've already had that But what I'm looking for here are two things. Are they testing appropriate antibiotics? Are they testing the antibiotics in the national minimal protocol? And here you are you're testing all the common things the important things for staph aureus Secondly, are they testing them systematically? so Saphoxidin yes, but it's not even consistent like Sipro is a little bit less than sxt a little bit less than Clean the mice and it's nice if everything is perfect if everything is equally tested Then you have things like deptomycin and nitroferantoin and chloramphenicol and tover mycin that are infrequently tested Tested in urine tested as second-line testing of multi-resistant strains So for example, if you look at the Look at the table for tover mycin You see the row for tover mycin You see it says a hundred percent susceptible that sounds great But there are only two results Yeah, it's not meaningful So can you click on the number column once and click on it again? Click once click on them again Good. So these antibiotics at the top I have confidence in the antibiotics at the bottom Are they're just too little data and I see that very visibly in the graph So tover mycin not enough data deptomycin not enough data I'm interested in deptomycin. Let's go find the deptomycin go down to the bottom here I expect it to be a hundred percent sensitive But it isn't and you have the question mark The reason for that is a break point. There are no break points Oh, it's because okay, so there's another issue. I don't want to get into this now because we're running short on time So so the main thing I'm looking for now I'm not that interested right now in the percent resistances The reason I put this is I want to see the test patterns Do they test appropriate drugs and do they test them systematically? Let's do the same for acolyte Click on continue Okay, click on the number tested graph First of all on the far left you see penicillin That's an inappropriate drug and you even see it in the table. You see there's penicillin one time It might have been a typing mistake. It might maybe they test either way. It's a mistake It's either a laboratory mistake or a typing mistake. So ampicillin is good. Pippa. Pippa is good But it's an old drug. Nobody really tests peppercylin peppercylin taso back ten is very important clinically peppercylin by itself. I don't I don't First of all, I want to make sure. Okay. You do have pip taso. I do see pip taso So in the in the table, you see pip taso 76 times Pip taso is an important drug peppercylin by itself really is not very important Amc, tzp, cdo, cxm So I'm looking to see are there drugs that are not drugs that are incorrect. Azithromycin I'm not certain about this. I don't think azithromycin is appropriate for E. Coli. I'm not certain of that And also you can see it's a bit haphazard. Cipro and SXT and MEM are tested all of the time You see the nice big peak mem cit SXT But amp is less and tzp is less and cephapim is less. So in the future, I'm hoping that we can pick a certain minimum standard That is tested consistently on every isolate Does that make sense? Yeah, it's good for statistics, but it's also good for patient care It's good if the doctors know they're going to get the same course set throughout the country of the most common things that they should have Of course, it's the lives want to do more testing. That's fine Um, but they should at least do the minimum Okay, now let's let's click on the graph for ampicillin in the lower right hand corner. Click on ampicillin So here we see the zone numbers. You see high level resistance on the left Sensitive on the right and they're not a lot of sensitives. Let's go to the graph for pipicillin This is a very good drug. So go to pipicillin tazobactam. So you see most of them are sensitive You know, you see some high level resistance some low level resistant. So that's enough of that click on continue Okay, and now we're going to do the anti biogram for some of the most important gram positive pathogens And or cock I did not put all gram positives. I just put some of the most important ones And our caucus focalis fissium species And there were no strep pneumonia because I also put strep pneumonia on the list The the grant look gram positive organisms are very different from each other Staff is very different from enter caucus and our caucus is very different from strep pneumonia So let's have this discussion, but let's have it with the gram negatives. Click on continue So here the here the gram negatives are very similar. E. Coli, Klebsiella, they're all kind of similar organisms So in the lower right hand corner, click on the graph for ECO Click on the graph for E coli Good, so I can see sensitive resistant. Click on the graph for klebsiella pneumonia Click on the graph for ABA. Acinetobacter is usually very resistant So that's not as resistant as I thought it does depend on the country um Or click at the bottom on ampicillin the graph for ampicillin So, uh, let's use a more interesting example. Click on the graph for pipicillin tazobactam Well, no, no, no, no, it's uh, let's go back to the ampicillin I said it's not interesting, but in fact, it's a little bit interesting But okay, okay, stay right where you are. Let's finish the discussion in pip tazel So here is pip tazel per E coli is about almost 80 percent sensitive But for ABA, it's about almost 40 percent sensitive. Homophilus influenza is zero percent sensitive Now let's go back to the ampicillin So you can see that some of the E coli are sensitive. Many of the homophilus are sensitive Homophilus is about 50 percent sensitive But all of the other ones are zero percent sensitive Meaning they're resistant and that's normal because these organisms are intrinsically resistant Acinetobacter should be ampicillin resistant Apsiola should be so I said it was uninteresting because of the resistance, but it's also good from a quality perspective I am glad to see that homophilus is relatively susceptible Well, not half. It's not great, but homophilus is relatively susceptible Whereas the other organisms are completely resistant or mostly resistant Now click on continue Okay, so these two things that just sent you the the two Reports we have just seen the two reports we have just seen have no confidential data in them. There's no patient details There's no patient names. No patient numbers So if you want to share data with others people these don't these just only have statistics Now we're going to continue with that other one called icid alert. So please click on icid alerts What do you think? I saw that that one icid alerts I You just had your notes on it icid alert who net standard report icid alert Okay, look on edit You can see this one does three macros important species important resistance that's important for epidemiology quality control or invalid data Click on exit Okay, choose your seat. Well, it's already chosen to go like now click on begin analysis We're running short on time. Normally. I'm sure you had to export this to excel Oh, but it's easy. You just choose excel um So this is a list of bacteria that have either an important species alert or an important resistance alert Uh at the top of the screen you see there were 209 isolates Move over to the right side of the screen Slowly, I just want to see after the antibiotics a little more to the right more to the right Just a little bit after the antibiotics Load down that spot stop right there. Okay Uh, actually a little more to the right a little more to the right Good, you see those three columns called priority organisms and icid alerts Not too far. That's right. Stop right there. Uh, you see the three columns called priority organisms and icid alerts Get the column called organisms, please make that column wider And the icid alerts I wanted to make both of those columns wider make it even wider than that because some of these comments are quite long A little more make it wider That's good. And yeah, that's good. Okay. Good. Now. Let's make the organism column a little bit wider I just need to see the name of the organism Yeah, a little bit more than that Good, that's fine. That's fine. Okay. So here you can see um You see let let's click on the column that says priority. I want to sort this by priority Click on priority once No, no, you don't need to make it wider, but you know that's I want to sort it so makes it so click priority once Then we see our medium priority alert. Oh, we see our high priority Is this right because h is an alphabetical order before medium click on priority again I want to see the high priority alerts And high is an alphabetical order higher. That's perfect So here you see in the column called ice alerts. We have carbon pentam resistance We have a lot of c re this is a high priority alert. We have possibly espl Most of your alerts are the same the carbon pentam resistance. Can you go down further? And I see vancomycin resistance And I think we discussed this last time and I think we discussed this in detail last time And I think those are I think those are just a mistake I think staff and two of them were resistant, but it's not real resistance So we discussed those vancomycin resistant ones last time Possibly espl. I'm occasion. So do you get a sense of this? This is just to find for you interesting results If you receive data on a monthly basis from laboratories, I would recommend that you be interested in the high priority alerts I don't think the medium priority alerts is so interesting at the national level Their statistics are interesting. I do want to know the percent MRSA But I don't want to see a list of all the MRSA What you have here is the list Can you go back to the far left Go back to the far left of the table Obviously the red is the actual the alert so you can see where the promise go far left far left all the way left Good. So I want to emphasize here. You do see the confidential patient data here So this is a very valuable report for people inside the network with approval. Do not send this to anybody else Especially if there are names and things there So we're going to put that on the screen just to highlight that some of these things have patient details And some of them don't so this is analysis is very valuable for the lab and for the national coordinators But it does have confidential data in it He clicked on continue So this one was about high priority resistance and high priority or important species and important resistance This is a summary. So the most common rule you have Is possible espl You see so any questions on this? I'm just looking at the time. It's just a summary of the alerts And they're categorized. You see the checkbox important species Okay Good now, let's click on continue All of those were important species or important resistance Now we're doing exactly the same thing, but these are no quality control alerts Can you go over to the right again? I want to see what the alerts are Good and let's just make isolate alerts column a little bit wider We don't have to do all of them. Just isolate alerts make that a little bit wider I'm not a little bit make it a lot wider Good. So here just as an example You see it says do you see the row that's you see the one that says cephalosporin 3 equals susceptible Enter a factor is usually resistant So, so it's just it's just saying that well, you see the one that says immunoglycosides discordant Do you see the row that says immunoglycosides discordant? Can you click on it? These one No immunoglycosides discordant up to Up. Yeah, that's one. That one's fine. That one's fine. Immunoglycosides discordant You know, there's a drug genomycin, which is old and cheap. There's a newer drug amiccation It's just much more expensive and much newer Usually an E. Coli will be resistant to genomycin, but sensitive to amiccation If you have amiccation resistant but genomycin sensitive It might be a mistake and that's what this means. It means the results don't make the results seem wrong Or in a similar way if you have an MRSA that is sensitive to penicillin that doesn't make any sense So you can see the columnical quality control these little mistakes. It doesn't mean it's a mistake, but it means you should double check it Click on continue Some of these alerts are obvious mistakes. Some of these alerts. It's not a necessarily mistake Like clepsiola can be sensitive to ampicillin. It's rare But it just means if you have clepsiola sensitive to ampicillin, you should just retest it Because maybe it's not sensitive or maybe it's not a clepsiola. Maybe the identification is wrong And here's a summary. So the most common rule is uh, rule number 16 rule number 16 Let's click on continue I am going quickly because i'm looking at the clock. Click on continue That's all There were no invalid data because that was number three But just one small point Hoonet right now like if the person had male and female and they accidentally typed a letter w As a mistake Hoonet is doing a little bit of validity checking Oh, no, I take that back. It's not even I just take it back. It was it's just not that part's not ready yet We're gonna make that better Okay, the last thing you see the one here at the top of the screen called standard report Click on the one called standard report Hoonet has had the exact of this feature for 20 years I like it, but I don't like I like it, but it can be better click on begin analysis This one we're going to discuss in greater detail on the next call, but I want to show you that everything we just did Uh, it's kind of summarized here Section a a little summary section go to section b Percent valid percent and complete you see down at the bottom. It says the male and the female It has the departments Now click on organisms go to tab c It has so basically now click on d and the bottom results booked on e uh I mean go to f just click quickly f g i Okay, now click on okay Click on edit So you can see here this did a lot of this stuff. We already saw today The difference is that this is much advantage is it's concise It's easy It's it's not all the details. It's it's we're trying to make a pdf file So for the for the stakeholders, that's easier to excel files are great, but there's a ton Or this is much shorter What I don't like is that it's not configurable. So it's sort of uh, I've been okay Click on outputs to screen My goal here is to add and the word works, but it's not what we want to do is make a very pretty attractive report That you can share with the physicians with you know with the idds people other colleagues So At you as the national data managers you want all the details But if you want to share this with somebody else, they don't want the same level of detail They want pretty things and text a nice cover page. So we're sort of moving in that direction So we can discuss I want this is a little teaser, but I just wanted to show you where we are going with this So basically the standard report is a short version of this phone call We covered a lot of reports in detail. The standard report is just sort of the summary of all of those things