Why local antibiotic resistance data matters – Informing empiric prescribing through local data collation, app design and engagement in Zambia
Background: Control of antimicrobial resistance (AMR) relies on local knowledge and local intervention implementation. Effective antibiotic stewardship requires locally-suitable prescribing guidelines. We aimed to use a novel digital tool (the ZARIApp) and a participatory approach to help develop lo...
| Main Authors: | , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-12-01
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| Series: | Journal of Infection and Public Health |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1876034123003957 |
| _version_ | 1827687013166350336 |
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| author | Sombo Fwoloshi Uchizi Chola Ruth Nakazwe Timothy Tatila Tebuho Mateele Mwewa Kabaso Theresa Muzyamba Ilunga Mutwale Anja St Clair Jones Jasmin Islam Enock Chikatula Aggrey Mweemba Wilson Mbewe Lloyd Mulenga Alexander M. Aiken J. Anitha Menon Sarah Lou Bailey Gwenan M. Knight |
| author_facet | Sombo Fwoloshi Uchizi Chola Ruth Nakazwe Timothy Tatila Tebuho Mateele Mwewa Kabaso Theresa Muzyamba Ilunga Mutwale Anja St Clair Jones Jasmin Islam Enock Chikatula Aggrey Mweemba Wilson Mbewe Lloyd Mulenga Alexander M. Aiken J. Anitha Menon Sarah Lou Bailey Gwenan M. Knight |
| author_sort | Sombo Fwoloshi |
| collection | DOAJ |
| description | Background: Control of antimicrobial resistance (AMR) relies on local knowledge and local intervention implementation. Effective antibiotic stewardship requires locally-suitable prescribing guidelines. We aimed to use a novel digital tool (the ZARIApp) and a participatory approach to help develop locally-relevant empiric antibiotic prescribing guidelines for two hospitals in Lusaka, Zambia. Methods: We produced an AMR report using samples collected locally and routinely from adults within the prior two years (April 2020 – April 2022). We developed the ZARIApp, which provides prescribing recommendations based on local resistance data and antibiotic prescribing practices. We used qualitative evaluation of focus group discussions among healthcare professionals to assess the feasibility and acceptability of using the ZARIApp and identify the barriers to and enablers of this stewardship approach. Results: Resistance prevalence was high for many key pathogens: for example, 73% of 41 Escherichia coli isolates were resistant to ceftriaxone. We identified that high resistance rates were likely due to low levels of requesting and processing of microbiology samples from patients leading to insufficient and unrepresentative microbiology data. This emerged as the major barrier to generating locally-relevant guidelines. Through active stakeholder engagement, we modified the ZARIApp to better support users to generate empirical antibiotic guidelines within this context of unrepresentative microbiology data. Qualitative evaluation of focus group discussions suggested that the resulting ZARIApp was useful and easy to use. New antibiotic guidelines for key syndromes are now in place in the two study hospitals, but these have substantial residual uncertainty. Conclusions: Tools such as the free online ZARIApp can empower local settings to better understand and optimise how sampling and prescribing can help to improve patient care and reduce future AMR. However, the usability of the ZARIApp is severely limited by unrepresentative microbiology data; improved routine microbiology surveillance is vitally needed. |
| first_indexed | 2024-03-10T09:26:40Z |
| format | Article |
| id | doaj.art-7ab7182496fe438594e75f9967ba5ec3 |
| institution | Directory Open Access Journal |
| issn | 1876-0341 |
| language | English |
| last_indexed | 2024-03-10T09:26:40Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Infection and Public Health |
| spelling | doaj.art-7ab7182496fe438594e75f9967ba5ec32023-11-22T04:47:09ZengElsevierJournal of Infection and Public Health1876-03412023-12-01166977Why local antibiotic resistance data matters – Informing empiric prescribing through local data collation, app design and engagement in ZambiaSombo Fwoloshi0Uchizi Chola1Ruth Nakazwe2Timothy Tatila3Tebuho Mateele4Mwewa Kabaso5Theresa Muzyamba6Ilunga Mutwale7Anja St Clair Jones8Jasmin Islam9Enock Chikatula10Aggrey Mweemba11Wilson Mbewe12Lloyd Mulenga13Alexander M. Aiken14J. Anitha Menon15Sarah Lou Bailey16Gwenan M. Knight17University Teaching Hospital, Lusaka, ZambiaUniversity Teaching Hospital, Lusaka, ZambiaUniversity Teaching Hospital, Lusaka, ZambiaKanyama General Hospital, Lusaka, ZambiaLevy Mwanawasa University Teaching Hospital, Lusaka, ZambiaLevy Mwanawasa University Teaching Hospital, Lusaka, ZambiaKanyama General Hospital, Lusaka, ZambiaKanyama General Hospital, Lusaka, ZambiaBrighton Lusaka Health Link, Brighton, United KingdomBrighton Lusaka Health Link, Brighton, United KingdomLevy Mwanawasa University Teaching Hospital, Lusaka, ZambiaLevy Mwanawasa University Teaching Hospital, Lusaka, ZambiaKanyama General Hospital, Lusaka, ZambiaUniversity Teaching Hospital, Lusaka, ZambiaLondon School of Hygiene and Tropical Medicine, London, United KingdomUniversity of Zambia, Lusaka, ZambiaGuy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom; Corresponding author.London School of Hygiene and Tropical Medicine, London, United KingdomBackground: Control of antimicrobial resistance (AMR) relies on local knowledge and local intervention implementation. Effective antibiotic stewardship requires locally-suitable prescribing guidelines. We aimed to use a novel digital tool (the ZARIApp) and a participatory approach to help develop locally-relevant empiric antibiotic prescribing guidelines for two hospitals in Lusaka, Zambia. Methods: We produced an AMR report using samples collected locally and routinely from adults within the prior two years (April 2020 – April 2022). We developed the ZARIApp, which provides prescribing recommendations based on local resistance data and antibiotic prescribing practices. We used qualitative evaluation of focus group discussions among healthcare professionals to assess the feasibility and acceptability of using the ZARIApp and identify the barriers to and enablers of this stewardship approach. Results: Resistance prevalence was high for many key pathogens: for example, 73% of 41 Escherichia coli isolates were resistant to ceftriaxone. We identified that high resistance rates were likely due to low levels of requesting and processing of microbiology samples from patients leading to insufficient and unrepresentative microbiology data. This emerged as the major barrier to generating locally-relevant guidelines. Through active stakeholder engagement, we modified the ZARIApp to better support users to generate empirical antibiotic guidelines within this context of unrepresentative microbiology data. Qualitative evaluation of focus group discussions suggested that the resulting ZARIApp was useful and easy to use. New antibiotic guidelines for key syndromes are now in place in the two study hospitals, but these have substantial residual uncertainty. Conclusions: Tools such as the free online ZARIApp can empower local settings to better understand and optimise how sampling and prescribing can help to improve patient care and reduce future AMR. However, the usability of the ZARIApp is severely limited by unrepresentative microbiology data; improved routine microbiology surveillance is vitally needed.http://www.sciencedirect.com/science/article/pii/S1876034123003957Antimicrobial resistanceAntimicrobial stewardshipAntibioticsMicrobiology samplingDigital epidemiology |
| spellingShingle | Sombo Fwoloshi Uchizi Chola Ruth Nakazwe Timothy Tatila Tebuho Mateele Mwewa Kabaso Theresa Muzyamba Ilunga Mutwale Anja St Clair Jones Jasmin Islam Enock Chikatula Aggrey Mweemba Wilson Mbewe Lloyd Mulenga Alexander M. Aiken J. Anitha Menon Sarah Lou Bailey Gwenan M. Knight Why local antibiotic resistance data matters – Informing empiric prescribing through local data collation, app design and engagement in Zambia Journal of Infection and Public Health Antimicrobial resistance Antimicrobial stewardship Antibiotics Microbiology sampling Digital epidemiology |
| title | Why local antibiotic resistance data matters – Informing empiric prescribing through local data collation, app design and engagement in Zambia |
| title_full | Why local antibiotic resistance data matters – Informing empiric prescribing through local data collation, app design and engagement in Zambia |
| title_fullStr | Why local antibiotic resistance data matters – Informing empiric prescribing through local data collation, app design and engagement in Zambia |
| title_full_unstemmed | Why local antibiotic resistance data matters – Informing empiric prescribing through local data collation, app design and engagement in Zambia |
| title_short | Why local antibiotic resistance data matters – Informing empiric prescribing through local data collation, app design and engagement in Zambia |
| title_sort | why local antibiotic resistance data matters informing empiric prescribing through local data collation app design and engagement in zambia |
| topic | Antimicrobial resistance Antimicrobial stewardship Antibiotics Microbiology sampling Digital epidemiology |
| url | http://www.sciencedirect.com/science/article/pii/S1876034123003957 |
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