GLOBAL HEALTH
Innovating AR Data Reporting to WHONET in Zambia
By Kasimona Sichela , program coordinator , Informatics , APHL Zambia ; and Reshma Kakkar , manager , Global Health Informatics
WHONET Flow .
Antimicrobial resistance ( AR ) is a growing concern in public health . Timely and accurate reporting of AR pathogen data is essential for the development of antibiograms , tracking resistance trends and the control of infections to prevent large-scale morbidity and mortality . Globally , laboratories are challenged with reporting AR data due to lack of standards , manual data entry and duplication of effort .
APHL Zambia has developed a practical approach to identifying appropriate solutions for AR reporting . A key strategy is to establish a country-specific laboratory data repository , regardless of systems or tools being used at individual laboratories / hospitals . This approach entails collaborating with existing systems including laboratory information system providers , while establishing new technologies where required . The emphasis is on transmitting AR data to a designated central repository that minimizes the effort needed to report on AR and establishes a single point for data integration with AR surveillance and AR reporting systems . This data centralization approach used by Zambia has gained traction in multiple countries and supported an emphasis on laboratory data standards as national governments
realize the unique opportunities afforded to them . In addition , WHONET , a microbiology laboratory database software supported by the World Health Organization ( WHO ) Collaborating Center for Surveillance of Antimicrobial Resistance , is a widely accepted standard for laboratories to report AR data .
Zambia , through the Zambia National Public Health Institute ( ZNPHI ), has developed an integrated framework for AR surveillance . This framework builds on the work initiated by other global cooperating partners that include the WHO , the Food , and Agriculture Organization of the United Nations ( FAO ), the World Organisation for Animal Health , ( WOAH ) and United Nations Environment Programme ( UNEP ) among others . The surveillance activities are supposed to feed into WHO ’ s Global Antimicrobial Resistance and Use Surveillance System ( GLASS ).
The framework stipulates the laboratories targeted according to the scale-up schedule , which also incorporates a One Health approach . Laboratories enrolled in AR surveillance are required to utilize WHONET for data management , as it has analysis features tailored to the program . However , as far back as 2013 , the Zambia Ministry of Health ( MOH ) adopted the use of a single laboratory information management system ( LIMS ) in public health laboratories . The laboratories have consistently been using the LIMS to capture laboratory order requests made for the purposes of clinical care , therefore the LIMS data are up to date . Additionally , all data from laboratories using LIMS for managing microbiology testing have their data aggregated in the Open Laboratory Data Repository ( OpenLDR ) hosted at MOH headquarters . However , since the laboratories that are part of the surveillance network had to re-enter the information into WHONET for analysis and reporting to GLASS , they usually had several months of data entry backlog for WHONET . The implication is that whatever analysis was being done was usually retrospective , and any alerts generated would not be timely .
The approach decided on was to leverage the already existing complete dataset in OpenLDR at the MOH . An automated utility script would run at scheduled intervals against the OpenLDR . The data exported in the desired data format would then be shared with the laboratories responsible for AR surveillance . After a process of data review and / or data cleaning , the data are then imported into WHONET using a WHONET-provided utility called BacLink .
Training was conducted with the MOH and partners supporting AR surveillance on how to utilize BacLink to address the data gaps . Participants were able to start utilizing WHONET . The outcome of the training and use of data from the OpenLDR is that hospitals no longer have data entry backlog for WHONET . Additionally , the historical data are also more complete and up to date . Two of Zambia ’ s largest hospitals have since even begun working on their antibiogram guides based on complete data from the last two years . g
22 LAB MATTERS Summer 2024
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