 Okay folks it is now 1 p.m. here in Oslo and that means that we are gonna get started with the with was it day 3 now of the annual DHIS 2 conference day 4 day 4 okay time has been flying by so welcome to the session this session will be on logistics and lab management information systems my name is Scott Russ Patrick I'm the DHIS 2 analytics product manager at the University of Oslo and I am very pleased to have the opportunity to tell you a little bit about what we're doing with logistics management information systems and then I'm also very happy to have a wonderful group of folks that will take us through several use cases and experiences from the field and using DHIS 2 for logistics and lab so let me just progress through a little bit of the program I'm gonna get us started off with going through the DHIS 2 or slash the University of Oslo strategy for supply chain fill in some gaps that you guys know what we're planning to do with DHIS to be able to support logistics information systems and then we have a really interesting story from George McGuire on the international Red Cross's use of DHIS 2 for logistics tracking in filled hospitals in Yemen and actually George is joining us from a filled hospital in Yemen so that's quite exciting hopefully his connection stays good then we have another really interesting use case from Zuina Kondo on the TB lab sample referral system in Tanzania I believe and then Billy Rajab from Malawi is gonna wrap us up with a case study on integrated lab management software hopefully at the end we'll have maybe five ten minutes for questions if we can if we don't have time please post your questions to the community practice we'll keep an eye on the community practice as the questions come in and make sure that you get answers to them alright let's just started in with the University of Oslo's approach to logistics management information systems we actually give this presentation every year and every year it actually is significantly different from the next we make pretty dramatic improvements in terms of DHIS to use and functionality and support for supply chain so I'm gonna kind of go through what we've done a little bit in the past as well as what's on the roadmap going forward why do we always keep talking about this every year well it's actually really quite simple it is because countries keep asking for it every single year and they keep asking for more and more and specifically what they're saying is we use DHIS 2 for routine health surveillance why can't we use it for routine supply chain monitoring and over the for the first few years that this was going on we didn't actually have a very clear answer we just said yeah maybe it kind of works that sometimes it doesn't work just exactly like you want it to but you know it it kind of goes along over the years we have realized that that is profoundly insufficient and that we as a health information system need to be able to support the supply chain component to make sure that we get all the data into one place so that we're providing DHIS 2 as a platform that can host all data coming from all sources in the country so you can get all of your analytics together in one place and that's really kind of the key principle that we're operating off of we as and in partnership as a collaborating center with WHO moving very hand-in-hand with them on this believe that a strong health information system should include the ability to have analytics and data from all of your various health programs as well as your logistics and your and other things like HR and maybe even finance as well and it's by getting all of these various data sources in one place being able to build indicators being able to build dashboards composite analytics across all of these various data sources are you actually able to get to kind of the goal of everyone which is bottleneck analysis root cause analysis being able to tie your health outcomes your clinical services specifically to issues with supply chain or issues with human resources and being able to know exactly where the problem is to be able to address it we appreciate that all these data sources need to be in one place and we want DHS to be able to be that place if countries want it to be so what exactly then do we want to do to be a little bit more specific with you we want to make sure that DHS to is a single platform that can facilitate all data sources coming from the health facilities as well as community health workers as that specifically includes supply chain and logistics data we also want DHS to to be able to be able to speak with more specialized systems so you can think of like warehouse systems or ERPs well DHS to is not a warehouse system or an ERP but we want DHS to be able to push and pull data to those systems so we have to maintain a solid API for that kind of interoperability we want DHS to also be able to produce all key logistics indicators so again that supply chain data can enter into DHS to from the lowest levels and from that supply chain data we want actually DHS to have the analytics capacity to be able to calculate all logistics indicators and we've been doing a lot of work and I'll go through that on its ability to do that the second the last point here is to we want to be able to provide countries guidance on how to use DHS to for supply chain we want them to know what they can do what they can't do and to be able to help and reinforce these kinds of implementations over time and the last point is arguably probably most the most important one and it is that we do not want DHS to to be a warehouse system or an ERP DHS to is just poorly suited for those particular use cases now it should again be able to speak to those systems but it definitely should not actually function as those systems here's a little bit of a model actually we're working with a specific supply chain system an LMIS called Medexus in Burundi and what we've actually managed to do with Medexus has come up with this nice model and it kind of I won't go through it in detail but it kind of shows you the connection between DHS to and an LMIS that a country might have specifically that monitors their warehousing system there and their trend more transactional supply chain data so in Burundi they have all supplied data entered at the facility level into DHS to and then DHS to pushes that data to Medexus to go so it sends information to the warehouse and the people in the warehouse are using Medexus they're not using DHS to the people in the warehouse fill orders they monitor stocks they push stocks out to health facilities and then that data comes back to DHS to so that a DHS to at any point all of the program managers know what supply of key commodities are available at each health facility and we find this to be a pretty good model that we want to build on top of we want to reinforce this and if any country actually wants to adopt DHS to in more of the supply chain capacity we want to be able to present this as a model in partnership with Medexus and other open and other kind of leading supply chain systems out there like OpenLMIS as well as kind of an approach that would be appropriate for a for any country this approach has essentially four legs that I'm going to go through quite quickly and they are DHS to functionality content interoperability and integration with other supply chain systems and technical expertise I'll just touch on each one of these quite quickly for DHS to functionality we have been improving the ability for DHS to to capture specific supply chain data specifically we've incorporated QR and barcode scanning which is very important for supply chain be able to scan in vials barcodes from commodities boxes that kind of stuff get that data very quickly into DHS soon I think maybe George might touch on this in his use case a little bit later we also want DHS to be a platform that other people can innovate and develop new applications that are more specific to supply chain data capture we actually seen this in quite a few places where in Mali and Burkina Faso there's a specific app that those countries use that's a DHS to app developed by his West Africa to enable them to enter the supply chain data at facility level the same story in Bangladesh as well as in Uganda the last point is that the capture app that we've developed ourselves has been totally integrated or has integrated aggregate data capture and tracker data capture and we find that both aggregate and tracker are required in kind of the logistics supply chain space you won't necessarily have all your data in aggregate you won't necessarily have all your data in the tracker and that usually you're using a combination of the two and the great thing about the the Android app nowadays is that both of those kind of appear together the user doesn't have to move between multiple apps they kind of it's a very seamless workflow for them another big point in terms of the functionality is that we have been building our ability to calculate very advanced indicators really the supply chain and logistics space has some very complex indicators and we've been building out things like predictors advanced indicator logic new indicator relationship models into the DHIS to core to be able to calculate these kinds of indicators and I'll give you just a quick example these are the some of the key supply chain indicators that we know DHIS to is able to calculate now so things like resupply average consumption stock status based upon available stock and average consumption order full rates monitor stock out days know how many facilities are stocked out and exactly where those facilities are the lead time which is the time between the the warehouse and the and the and the health facility and we can do things like I just mentioned line list all of the stockouts and just make it extremely clear where the facilities that have poor stock availability or stocked out are and I think that that's exactly what we set up for Malawi over the last couple of years we've been working with the Malawi government our his partner in Malawi and several other development partners to be able to tie their supply chain system there their LMIS which is open LMIS directly into DHIS to and all of the open LMIS data actually pushes into DHIS to and they use DHIS to as their key analytics platform for their entire supply chain system so what you're actually looking at right here is a simple is a as an example dashboard from Malawi that shows very very easily and clearly all of the health facilities that have stock problems you see some of the maps there those big red spots on those maps those are health facilities that have a stock out at that particular moment in time of a real stock out and this is very actionable data you can also see in the other charts and maps that they can see the facilities where there is some facilities are overstocked and they are actually able to use this data to transfer commodities between facilities that are close by those facilities that are under stocked or out of stocked and those facilities that are adequate or over stocked and it's this is a this is not just a passive dashboard that they look at every once a while when they're when they're doing quarterly planning they look at this dashboard every day and see today where do I have my stock problems so very actionable information we also see some other really cool analytics coming out of it the great thing about having all of your data into one place is that you can actually build indicators that look at your caseload as well as your stock consumption and availability data so again in Malawi and that's using another example from Mali where they're actually able to build some really interesting indicators like issuance to consumption ratio or caseload to consumption ratio or caseload to issuance ratio these kinds of indicators are actually much better at kind of forecasting where my stock is will will become for example if I have an adequate stock this month but my caseload is higher than my average then and if I don't get an adequate resupply then next month I'll be under stocked or potentially even stocked out and so being able to look at the trends in caseload is a really great way of actually doing some forecasting for supply chain and again getting all that data in one place into DHIs too enables you to actually do that finally on the content side just a few things to point out is that actually as of today I received the copy from the WHO we've been working with them for quite a long time George the next presenter has been pretty integral to this process to actually be able to get standard indicators supply chain indicators that should be in the HMIS from all of the key WHO programs together in one place and what we're actually going to do is take that list of indicators which again I just got emailed to me today the finalized list what what we'll actually be able to do is convert this into a standard metadata package so the indicators come pre-configured at DHIs too they come with the data elements they come with some of the reporting forms and analytics from the dashboards and we're going to package this up for you and if you're a country that wants to implement DHIs too for some element of their supply chain and you want to follow the WHO standards then all of that a lot of that works already been done for you you can download the package install it into your DHIs too instance and then you just need to modify it and update it based upon any of the unique features or functionalities reporting flows context of your of your country but we've done this for other programs as well like HIV immunization malaria tuberculosis and it's really exciting that we're actually going to have something very similar for supply chain now as well the next point that I just want to make quickly is on interoperability and integration so we are working increasingly closely with various other software out there that support the supply chain specifically those systems that are solely designed to be logistics management information systems and that cover areas like warehousing like ERPs that DHIs too is not suitable to cover so these are like open LMIS a little bit of communication with M supply and we're working quite closely nowadays with a platform called Medexus that's implemented in Burundi and a couple of other countries in Africa so it's an excellent LMIS I highly recommend it and we're working quite closely with those developers you know that our developers talking to their developers to be able to make sure that these platforms are able to speak to each other the goal being that countries have been struggling with these complex interoperability layers and we want to work with directly with the other platforms out there to either have integration or out-of-the-box interoperability so countries don't have to struggle with these interoperability layers as much or or make this make make the burden on the country significantly less the last point that I want to make is on the expertise this year we have invested a lot of additional resources into supply chain and so I'm really excited to be able to say that we are actually going to have two staff on the University of Oslo team specifically focus on the logistics systems and supporting those so we will have an LMIS portfolio lead we actually have identified the person he's already signed the contract so we're really excited to have him on board in the very near future the he's coming from the Norwegian Red Cross a huge amount of supply chain experience very practical and then we also have the we have an LMIS technical advisor coming aboard which will actually be your next presenter George and George is an absolute guru of supply chain LMIS been working in it longer than I've basically been doing anything in my life and and so we're gonna have an incredible team here at the University of Oslo in the next couple of months to work more closely with countries and the last thing that I want to announce and this is also very exciting for us is that we have in collaboration with the University of Basel the Swiss Tropical the Swiss Tropical and Public Health Institute set up a LMIS HMIS Center for Excellence based sorry if you're not speaking could you please meet yourself thanks yeah so we are setting up the Center of Excellence in in Basel and there will be full-time implementation support staff working with countries able to help countries as also development staff actually making new apps making new features and functionalities everybody working towards having getting that HMIS data and that LMIS data all into one place and giving the countries the tools that they need to be able to do that so with that I think I will hand it now over to George will stop sharing my screen and George you can start sharing yours and you can take us through the work that you're doing with the ICRC okay thank you very much Scott just confirm whether you can see my screen first slide okay thank you very much so thanks a lot for the invitation I'm very honored to to join the DHIS II Academy I'm joining you from the south of Yemen from the healthcare facility where we're actually piloting our system I hope the line holds so I call the system the real-time medical stock management and basically we are piloting the use of the DHIS II capture app for this purpose so just to explain briefly where we are coming from our starting point is basically a conventional stock management system that you probably all in all know from any kind of stock could be a pharmacy could be a laboratory could be a stock of education material and basically the way we have been operating and we still operate around the world is that we have a monthly physical stock count of all items in the medical store so you go you count each item takes you two to three days every month then usually there's a manner recording of the daily consumption of all the medical supplies that have been given out to to the world so to the other services like the operating theater the laboratory and then at the end of the month usually from the manner record you will add up your daily consumption for calculating the monthly consumption which will then in turn be used for forecasting and planning and calculating your replenishment orders and in in our case where we the healthcare facilities we support usually those systems are paper-based but they could also be using spreadsheets usually Excel so the disadvantages of this system is that you have to carry out the complete physical stock counts every month which is very time-consuming and you basically counting every item regardless of whether you actually issued that stock or not one of the big drawbacks is that the data is available only once a month so at the end of the month you have your stock count you have your consumption you can calculate your coverage time and determine how how much stock you have left and how long it will last and this is one of the main issues that we have in terms of logistics and demand planning is that if you have a big increase of consumption during the months for any reason let's say you have a large number of patients or you have an outbreak then you will basically only be able to analyze the data at the at the end of the month so you will only know that when you carry out your physical stock count and you have the data at the end of the month so what we are here piloting since 10 days and it's working very well is basically to look at how we can have a real-time data flow so starting at the left basically the idea is that you have on the bottom you have a container of a moxicillin tablets let's say 1000 tablets and you have here the patient word and we are not recording each and every stock issue that would of course not be practical to record every time you use a compressor you use a canola or administer a tablet or an infusion what we do is we will scan a container when it is empty so every time we empty let's say one container of 1000 tablets or one box of 25 canolas then that container will be scanned with a barcode and the data will be stored in DHIS tool and in order to keep the stock replenishment system in the hospital as simple as possible basically we use this concept of the one-on-one replenishment it means that for every container that you emptied in a ward or in a service you get a new container now you don't have to do that on a daily basis you could but you don't have to do that basically DHIS tool will add up all the stock issues that you have that the words have used during the day or the week or you can do it once a month every two weeks depending on how you manage your internal distribution system in the hospital and you could have let's say weekly supply so you basically tally up all the containers that you have entered let's say in the pediatrics ward in the first week of September and then the pharmacy will then provide all these items that you have issued so that you replenish your stock levels according to the to the previous stock level so you could also in principle record each and every ampoule of a vaccine for example or container that is up to how you want to use the system the one one replenishment basically ensures that you don't have a complicated system with calculation and paper every time you scan a container in the ward the pharmacy will basically see what has been used and can basically automatically replenish and the beauty of the system is that if you record all the stock issues by scanning the barcodes and you can you enter all your stock receipts from your upstream distribution center let's say you receive monthly supplies you will do that with an electronic data file ideally so you don't have to scan all the items when you receive it in the hospital so this is part of the project to have an integrated state of law from an ERP system where basically when electronic document behind that and EDI electronic data interchange document with all the items and the item codes and the quantities and even the batch numbers and expiry dates and basically when you receive those consignments in the pharmacy you will basically load it into THIs too and those quantities will be added to your stock so if you enter all your stocks electronically and you issue all your stocks that you are distributing to the wards and services also electronically then basically the system can automatically calculate the stock on hand without the need for for any stock count of course you have to have checks and balances because if you just run the system and assume that everyone is 100% reliable eventually there will be mistakes and you will have to make corrections but there are checks and balances in the system that allow you doing the doing the day for example when you enter an entire container to check whether that container that you are now emptying in the pharmacy matches your current stock position and then this data that you are collecting at the end user level so at a hospital pharmacy can then be fed in real time to your logistics management information system whatever you are using so Scott already mentioned the possible integration with Medexys which has been in principle tested that integration with the REST API is working and you can feed that demand data directly from the health care facility all the way up even to include your suppliers if they if they want the data so that they they can plan and then of course you have the DHS to as a established health management information system and it's got pointed out you can then link the HMIS and LMIS data in in real time for for various analytics purposes and since you know at all levels of the supply chain if you are recording the stock issues and tiling up the totals per week or per month then it's very simple to replenish all the stocks basically at all the district provincial national level ideally basically everyone is just receiving from upstream what they have issued doing the doing the last months so the my last slide you can see at the bottom of the screen is basically the system as we are actually using it on a daily day-to-day basis so you can see we have these containers where we have for example Povidon and we have the malaria test and each of those containers are labeled actually is a barcode and the description and when we want to issue let's say one box of malaria test 25 tests in a box we will simply scan the barcode and then record the the quantities of one kit and then you can even record exactly to what service you have distributed to those items you can record basically the day the time that it has been given to the female or male ward or operating theater with the quantity and that is then locked and available in the analytics table in DHS to so the advantages of the system is that is it's paperless as I said you do have to have checks and balances you have an electronic record of all stock transactions so that's actually quite impressive you can actually scan a stock issue and you can go on your database and you can see all your stock issues with the date time and so on you have an automatic record of your daily weekly monthly consumption so you don't have to record that consumption on paper one thing that is really nice is that you have a real-time stock on hand information that you can share with the hospital staff so every time somebody let's say if I issue this kit of 25 malaria tests then basically in real time the server is calculating recalculating my stock position anybody who wants to know what is the stock position of our 180 items today in the pharmacy at any time they can basically connect and they can view that data so they don't need to ask you don't need to share exel files or post it or if somebody even in the ward wanted to know where the certain item is available they could just pull out their mobile phone and check what is available in the pharmacy as I mentioned you have real-time visibility in the upstream LMIS so that's very useful for planners at upstream level let's say national regional logistic centers to determine if there's a large increase for any item let's say you had an outbreak and instead of waiting until the end of the month and then noticing that you have a lot of clinics asking for a large amount of a certain antibiotic or a certain diagnostic test you could basically anticipate these orders by setting about the magic alerts in the system that will notify you when there is an exceptional large increase of demand of certain items and then of course you it allows complex analytics Scott already showed some dashboards particularly on the stock stock availability and the potential shortage and you can also link your real-time stock data with the HMIS data as Scott also already mentioned number of patients the epidemiology thank you very much for your attention great thanks so much George that's a really incredible cutting-edge case of how to use DHS to for supply chain so now we're going to change it up a little bit and switch over to talking about our a few case studies on lab management information systems and our first presenter is Zouina and I'll invite you to go ahead and start sharing your screen and take it away thank you thank you okay first great hi everyone good day to everyone my name is Zouina from Tanzania working with the Minister of Health in the national program for tuberculosis and leprosy I'm going to share with you just our experience how the tracker module really improved the effectiveness of our sample referral laboratory sample referral system so Tanzania is an East African country about 900,000 square kilometers with a population around 56 million people by last year and health care wise we have around 8,400 facilities which most of them are dispensaries at the lower level administrative wise this is how the health care is organized from the lower level the community and then reporting to the facility then to the district region and at the national level where the ministry the ministry sits well what was the problem as as you know Tanzania is among the high TB burdened country we still have the tuberculosis problem and this is a deadly disease causes a lot of deaths but it is treatable however the treatment is with the antibiotics which are I can say strong but also possible and they take a long time so because of that we really need to do the sensitivity testing so that we make sure that these patients are really cured and we do that before the sensitivity we do the growing of the bacteria that is the culture and then the sensitivity part so in Tanzania we have two main groups of patients for the tuberculosis which we are supposed to to perform the culture and the DST we have those patients who are being sick for the second or third time with TB and but also we have those patients who are directly being diagnosed with drug resistance so what happened is that in our country as I've said it's a little bit fairly large however with we have only six laboratories which we call the Zono the Zono labs which are able to to conduct the culture you can see these are the ones but we have only one here around here which actually can perform the drug and sensitivity test the phenotypic one which is the one which is more reliable so what happens is that all these patients of course the country their samples will be sent to the Zono labs and then from the Zono labs may be up to the to the the central laboratory laboratory one which is in the Dar es Slam region so we used our post office for this transportation and this is usually used to happen in the past four to three years when we sit to discuss our cases especially the drug resistance cases the expert panel sees to discuss usually used our paper files and you start to discuss how are the patients doing and all that and it happened that when we we want to know the results at a certain time period when they checked we found that there's no results and they when the laboratory representative will be asked we'll have several reasons like actually the samples not it was rejected the samples not enough or okay the results are here but the results actually did not reach the point where the patient is so really this call caused a lot of frustrations among the health care workers and the coordinators and the situation was not good about only 13 percent of our treatment patient have the results for the drug sensitivity test and about half of the drug resistant to be patient did not have their complete sets of the results so that's why we decided to use the trucker module at that time we were using the DHS to aggregate and then we started using the trucker module for the case beds so we introduced the culture and BST lab register so that now it can be used to request the samples so when the health care workers send a sample through the post office they request that requesting the system and immediately the laboratory personnel will receive that message that there's a sample which is on the way and when they receive the sample then they will respond if it is accepted or not so at least there is a communication about that if another sample is needed then that can be done but also when the results are out results are out then the laboratory personnel they just key in the results and those health care workers they will receive the results as we can see here is an alert message that the results are actually out for that patient and they can instantly see the results so this really improved the condition because previously we used to depend on the emails until you scan the results and then send to emails and sometimes it was not working or sometimes just calling so after that for the 2018 we could see that really this improved our performance you can see in 2018 now we have almost 80% of the retreatment cases having their DST results but also another thing is that now the drug resistant TB patient we have all their results and really this made it possible during the COVID-19 outbreak when we had to do the virtual experts reviews so this really made it possible because of this of this system so I can say that the tracker module really improved our sample referral system that the culture and drug sensitivity system and it has improved visibility and also communication linkage with the alert messages and all that but we still have challenges with the ICT at the rural areas as we are all familiar with this but also the fact that our register you can see there our our our surveillance system it has three registers the TB register the DRR TB register and now the culture and DST register so it means registering a patient three or two times so we're working on this to manage all the registers to make the system more user friendly so that the patient can be just registered just once but we are also going to improve the system improve the tracking by using the backward but also those areas which do not have internet connectivity to start using the Android app so really that was just as not sure to follow the tracker module really helped us and improve the effectiveness and efficiency of our sample transportation thank you so much great thank you so much Zuyna that's a really incredible case study I'd like to maybe explore more with you on how you are looking across those three programs for that one patient I think that if you tune in tomorrow for the road map session we're going to start to hopefully we'll present some like actual solutions to to that particular problem that I know a lot of folks out there having with with tracker multiple programs for just one patient you want to see all that data in one place okay so absolutely so let's pass it on over to Billy and Malawi and you can start sharing your screen Billy and take it away so greetings everyone I hope I'm audible and you can see my screen yeah looks great yeah so my name is Billy Roger I work as a software products manager for the Ministry of Health under the quality management directory and data has this is the clinic a project so the theme of the presentation is how Malawi has integrated the lab management system with national surveillance to that was dealt with the GHS to truck tracker programs to reduce the human capacity strain and also to streamline the COVID-19 response alright so the clinic data for action project is funded by the Bill and Melinda Gates Foundation so the goal is to increase data demand supply and promote data governance so we focus our focus is on six districts but due to COVID-19 we have to scale up to all the 29 districts in Malawi so so the the Malawi government adopted the integrated disease surveillance and response as the main disease surveillance approach just recently we adopted the idea of the one health surveillance now the one health surveillance is an integrated multi-sector and cooperative approach to disease surveillance so it promotes the compartmentalization of human animal ecosystem health for more efficient and sustainable governance of complex health issues so we use the GHS to instance as the one health surveillance platform alright so we we have revered the GHS to one health surveillance flight from COVID-19 digital response by customizing the WHO COVID-19 surveillance digital data package so what you what you're looking at on the screen here is the the DHS to the whole workflow how we are able to integrate different systems I mean sorry the the LMI the LIMS system with the case-based surveillance system as a surveillance tool to track lab orders as well as to send lab requests and get a response from the different labs alright so if you can see the pointer here this is the one health surveillance we have enough of a number of programs that were created within the one health surveillance platform as a surveillance tool we have the part of entry screening we have the case-based surveillance we have the contact registration and follow-up in the confirmed case clinical management program so within the case-based surveillance program we have a couple stages so we start with the clinical examination then a lab order is generated so this is a stage which is an event based so you can create as many lab orders as you like so this request it's relayed through the interoperability layer and this is the we leverage the open him for health information health information exchange and this information is relates to the national LIMS the laboratory information management system and this system here it's also integrated with another system that is also managed by another partner which is the the EIDVL which does the the PCR tests for COVID-19 so when the when the tests are done here the information is sent back through the same the same channel it goes back to the national LIMS then that information also is relayed through the interoperability layer then it's so captured into the lab results as a response to the request that was generated so we have managed to deploy this surveillance tool to about 23 districts and we have more than 700 users in on daily basis we have about for the four lab requests that are generated from different areas where reduced the human capacity needed for instance for you to be able to capture the report systems so we have the HS2 tracker as well as the the the national laboratory information management system that would that would take time and we'll need people to do that also transporting the forms when the samples are collected the we have people who are responsible to do that we call them the district rapid response teams so these people they have to transport the forms to the labs then when the tests are done we have to find ways or mechanism how the information would be relayed back to the districts now that's proved to be a bit of challenging so what was needed here is the retained sort of like the retaining sort of approach in how people are able to send the lab results to the different facilities or different districts we had to automate the process now this information flows back through that same channel to the to the to the respected presses or districts so this also has reduced the number I mean the huge logistical investment so we need people to be moving up and down within the district and in it and the different labs that are there for for us to be able to coordinate the work and also it has increased the data quality in the integrity so there's no there's no one who is the data is captured once so the information is relayed to the other systems so there's no need for someone to recapture the data of course we have a couple of challenges with implementation connectivity is a challenge so sometimes the lab the lab the samples reach the labs but the information hasn't really reflected in the the other systems the national laboratory information management system so the the lab technicians would won't be able to see the the records at some point in time so that's one of the challenges we have so like users are not adhering some to the weight flows that we have implemented so some they take time to capture the information into the case-based surveillance system and also to actually generate the lab orders so the samples reach the labs before that information reaches the the actual labs through the integration in some of the equipment that we have deployed people are not using them for work related issues they're using the proportional that's another huge challenge with the setup so that marks the end of my presentation so thanks so much for your attention thank you so much Billy another really incredible use case and it's it's incredible to see what you all have built in terms of the interoperability layer using open HIM that it's really a pretty unique success story on on building off that platform and connecting these various systems to DHIS too we do actually have a few minutes for some questions from the community we'll start with the folks who actually posted in the community of practice for me again we if you have questions please post those to the link in the community practice link the first question there's actually two questions here I think for George and Zuna you might be able to weigh in on this one as well using the barcode scanner Arthur Haywood one of the original founders of DHIS too all right well DHIS one asks do you need electricity or how often do you need electricity if you're using the barcode scanner does it work offline do you need to have your phone plugged in all the time what are the resources that you need to be able to do the barcode scanning George okay so for the barcode scanning we use a simple mobile phone I prefer I prefer to use a tablet PC because the screen is larger but it works with a mobile phone I don't think we have particular issues with with charging of course it's a kind of trap when you use barcoding you always have to make sure that your mobile phone your devices is charged at all times one interesting aspect is just you need to be sure to to have enough light in your store and also to make sure that those barcodes are printed nicely and evenly because apparently when you have wrinkles it doesn't work well but on the charging issue I we don't really have an issue we also use power banks so that's always a good device to have with you in case you have would have a prolonged power failure so that you always have another let's say a half day of power to to run your barcode scanner thank you thanks another question and I think this goes for everyone here I think everyone could answer it is Kim asks is there any customization have you done any like custom scripts or custom applications or anything on these three various projects to get them to work have you developed your own applications or custom scripts and DHS to and maybe Billy we can or George can we start with you and just quickly say if you've done any customization or not no I have I have not done any customization so all stock DHS to nothing yeah okay and standard do we have you guys done any customization we had our our our local expertise are online ballistic was that a customized one yes of course the one that is currently on use was a bit customized but of course we are almost deploying another one which is not customized at all right okay so a little bit of customization to get yourself started but now it's you're moving back to more generic features is that correct okay that's really that's really interesting and Billy did you guys do any customization on the DHS to side and high score not really that's the generic setup so there was no any customization that's that's really incredible actually that DHS to is able to be so generically across these really three very different but and and very advanced use cases we have just a few more minutes three minutes any other questions out there from the community can I just chip in something quickly yes you're glad George so just because I was reading the original question so related to electricity so I mean since DHS to has this great offline functionality you're not depending on electricity or network connection to actually do the scanning so as long as your mobile phone is charged you can you can scan the codes let's say for an hour if there's a power failure even for for half a day and then when your net when the power supply comes back or if your network was not available then you can synchronize your data so you're you're not dependent for your daily routine work you're not dependent on either electricity or having a permanent internet connection thank you okay so maybe time for one more question George just comes in from Winnie Monze he's asking how do you handle products that don't have barcodes from suppliers or manufacturers George how do you're muted well maybe George will have to answer that one in the community of practice and I think that that then winds us up for our session I again I really want to sincerely thank George Zouina and Billy for their willingness to present and for telling us about their really incredible case studies I would also appreciate every all of you who've listened in if you do have any questions please don't hesitate to post those questions still in the community of practice we'll make sure that you get an answer to your questions and of course if you're really interested in knowing more about the supply chain use case you can always just email me I'm scott at dhis2.org and I think with that I will hand it back over two minutes early to grant thanks Scott