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Building Quality diagnostic systems for AMR; the AMR Lab score card
Debi Boeras presents building a quality framework for diagnostic systems for AMR including the AMR Lab score card.
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DEBI BOERAS: In this step, we will discuss how to build quality diagnostic systems for antimicrobial resistance– specifically how to build lab capacity, the core elements for quality assurance that include point of care testing, and how we can use the new AMR Lab scorecard to assess progress. Building lab capacity includes strengthening the lab, as well as the lab systems and networks, and positioning the lab as the command centre. As you heard in week two, diagnostics are key in epidemic preparedness and One Health.
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For early detection of infection, to help inform clinicians on how to treat their patients, and for quickly identifying outbreaks, early case detection also allows public health measures, such as isolation and contact tracing, to be put in place to protect others from being infected. We will discuss this further in the next few slides. Africa CDC is working with countries to strengthen clinical and public health laboratory systems and networks across the continent, through continued improvements and workforce competency to assure quality and safety.
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The model includes mapping the existing lab systems, assisting countries in developing national labs strategic and implementation plans, enabling policies that include regulations of diagnostics and secure safe handling of dangerous pathogens, implementing modern, advanced, molecular technologies and multiplex pathogen assays, introducing patient-centred approaches for integrated point of care testing for syndromic management and surveillance at the community level, developing strain banks as repositories for diagnostics and vaccine development for emerging and re-emerging pathogens, and supporting lab workforce development. In 2017, Debbie Boris, John Nkengasong and Rosanna Pealing published an article on the need to position the lab as the command centre, as point of care diagnostics are being introduced into low and middle income countries.
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They highlighted three areas that needed strengthening to prepare countries for the next public health emergency. One– building a comprehensive system of laboratories and POC testing sites to provide quality-assured diagnostic services, with a good laboratory clinic interface. Two– coordinating a comprehensive national surveillance and communication system for disease control in global health emergencies. Three– conducting local research to monitor the impact of newly-introduced tools and interventions. Global epidemics of infectious diseases are increasing in frequency and severity and diagnostics are needed for rapid identification of the cause of the epidemic, to facilitate effective control and prevention.
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Lessons learned from Ebola, Zika, and now COVID are that delays in developing the right diagnostic for the right population at the right time has been a barrier to disease control and prevention. Here you see a five-pronged strategy to accelerate and optimise diagnostic development for the lab response in epidemic preparedness, starting with the global landscape analysis of diagnostic availability worldwide, as captured at the top centre of the figure. This allows countries to assess diagnostic availability and surveillance systems. Strategic partnerships can accelerate test development, in particular with vaccine companies, to identify novel, diagnostic targets. Creating and sharing repositories of data, reagents and well-characterised specimens can accelerate new technology development and evaluations.
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Involving key public and private stakeholders, including regulatory bodies and policymakers, ensures faster access to diagnostics and tools. And fostering and enabling environment for local research can drive new technologies that are appropriate for local needs. We also want to consider the role of the laboratory in the One Health approach. Considerations for the role of the lab are increased coverage and sampling for increased surveillance, decentralised lab with sequencers, biobanking and reference labs, sharing data across the multiple sectors, quality standardised testing. And at the fifth international One Health Congress, actions to answer the following were identified. One– what are the top zoonotic diseases of importance across the African continent?
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Two– how should national public health institutes conduct surveillance for a selection of these priority zoonotic diseases? Three– how do NPHIs assess the risk of zoonotic cases and clusters in collaboration with animals and environmental sectors? We previously reported data from GLASS, using a standardised approach to the collection, analysis, interpretation, and sharing of data, and in week two, you heard about the Tricycle Project. As mentioned, the Tricycle Project has identified ESBL E. coli as a common indicator to be detected across human samples, poultry and water bodies– specifically, sewage, market runoff and river sites in urban areas.
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In this slide, we want to highlight that the ESBL protocol has been piloted in nine member states– Ghana, India, Indonesia, Jordan, Madagascar, Malaysia, Nepal, Pakistan, and Senegal, and is currently being implemented in Iran, Morocco, Nigeria, Zambia, and Zimbabwe. There are two documents included as references that would be good for you to read– the WHO-integrated global surveillance on ESBL-producing E. coli, using a One Health approach, was published in March of this year, based on the experiences gathered from the countries.
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The next few slides will focus on the quality aspect of lab systems for the AMR response, including point of care. A Quality Management System is a systematic integrated set of activities to establish and control the work processes, from pre-analytical through post-analytical processes, manage resources, and make continual improvements to ensure consistent, quality results. All aspects of the laboratory operation, including the organisational structure, processes, and procedures need to be attended to in a QMS. This means that point of care testing is part of the lab network and the same QMS. The top of this slide depicts testing at a laboratory facility and some of the activities meant to ensure accurate results.
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Within the laboratory, there are processes and guidelines for staff, tests and testing, such as licensure, external quality assurance programmes, and guidelines and protocols. But it is challenging to enforce pre-analytical quality processes to ensure the right specimen has been collected and will be transported correctly to the lab. Point of care testing resolves many of these pre and post-analytical issues because specimens collected are immediately loaded on a cartridge and tested. POC devices are often thought of as sample in, answer out. But because they are often placed in remote settings further from the lab systems, they can lack quality management. Quality should be thought of as a continuum, as shown in this flow diagram, where quality begins with manufacturing a quality product.
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Stringent regulatory authorities should oversee test quality and grant approvals for use. Then after procurement of the approved products, lot testing ensures the product has arrived in good conditions, and post-market surveillance continues to monitor the quality of the product. And under step three, is the quality management system processes to ensure quality testing, quality results, and reporting. Most countries have some sort of an external quality assurance programme that they can leverage for AMR. Shown here are models and how to organise EQA for point of care testing that have been developed by different countries.
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On the left is the centralised model, where the National Reference Laboratory oversees the quality assurance programme and provides direct oversight, including EQA panels to the point of care testing facilities, shown in green. The next panel shows a decentralised model, where there are numerous centralised testing facilities and each of these may oversee a group of POC sites, perhaps doing more specific type of testing. The centralised testing sites would then provide specific EQA panel for these POC sites. The last panel on the right shows the regional model. This is a slightly more complex model but also can provide greater coverage, as there are hubs set up that may be doing near POC testing, while also overseeing nearby point of care sites.
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Each of these models has considered mapping disease prevalence to provide the necessary testing coverage, and EQA can be either active, passive, or an intermediate process. Active may be that the country is producing their own EQA panel, sourcing materials developing and distributing the panels, and analysing the data and generating reports. A passive approach would be, perhaps, where each POC site is enrolled in an outside commercial EQA provider, and they simply receive the results and may even solely interact with the EQA provider. The jeopardy in this is that there may not be complete national QA data.
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An intermediate approach, then, might be where the MOH has enrolled the labs and testing sites and EQA programmes, but is involved with the process and ensures that all data are collected and reported to the MOH. Some additional considerations when planning for these models are cost and using connectivity to also capture the EQA data. And lastly, no programme or model should be complete without corrective action. If it is found that a testing facility is not performing well, root cause analysis should be performed and a corrective action plan put in place with the testing site.
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In 2016, a group of quality assurance experts published a supplement in the African Journal Laboratory Medicine, sharing real world experiences with building QA programmes in low and middle income countries. In this supplement, you will find lessons from the field and country profiles as listed here. There is an opening call to action piece, by John Nkengasong and colleagues, that the time is now to build robust QA programmes, followed by real world lessons from the field that highlight QA tools such as external quality assurance and data connectivity, and numerous country experiences with building and maintaining QA programmes. This will be available to you as a reference.
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FIND, in collaboration with partners, has developed an AMR lab quality scorecard to assess basic lab procedures, and identify gaps in quality control and quality assurance, that could potentially lead to inaccurate results. The scorecard has been piloted in a few countries. It is now available to the broader audience in the link shown here, bottom of the figure.
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This step addresses quality assurance for laboratory and point-of-care testing in building laboratory capacity for the AMR response. An AMR laboratory score card has been developed as a tool to guide countries in building laboratory capacity.
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This article is from the online course:
Diagnostics for AMR: Building Back Better from the COVID-19 Pandemic

This article is from the free online
Diagnostics for AMR: Building Back Better from the COVID-19 Pandemic

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