Browsing by Author "Kabongo M"

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    Measuring Oral Pre-exposure Prophylaxis (PrEP) Continuation Through Electronic Health Records During Program Scale-Up Among the General Population in Zambia.
    (2023-Jul) Heilmann E; Okuku J; Itoh M; Hines JZ; Prieto JT; Phiri M; Watala K; Nsofu C; Luhana-Phiri M; Vlahakis N; Kabongo M; Kaliki B; Minchella PA; Musonda B; Eastern Provincial Health Office, Ministry of Health, Chipata, Zambia.; Palantir Technologies, Paris, France.; Southern Provincial Health Office, Ministry of Health, Choma, Zambia.; Division of Global HIV & TB, Centers for Disease Control and Prevention, 351 Independence Avenue, Lusaka, Zambia.; Division of Global HIV & TB, Centers for Disease Control and Prevention, 351 Independence Avenue, Lusaka, Zambia. qng0@cdc.gov.; Lusaka Provincial Health Office, Ministry of Health, Lusaka, Zambia.; Western Provincial Health Office, Ministry of Health, Mongu, Zambia.; Ministry of Health, Lusaka, Zambia.; PHI/CDC Global Health Fellowship Program, Public Health Institute, Oakland, CA, USA. qng0@cdc.gov.; Centre for Infectious Disease Research in Zambia, Lusaka, Zambia.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)
    HIV pre-exposure prophylaxis (PrEP) is being scaled-up in Zambia, but PrEP continuation data are limited by paper-based registers and aggregate reports. Utilization of Zambia's electronic health record (EHR) system, SmartCare, may address this gap. We analyzed individuals aged ≥ 15 years who initiated PrEP between October 2020 and September 2021 in four provinces in Zambia in SmartCare versus aggregate reports. We measured PrEP continuation using Kaplan-Meier survival analysis and Cox proportional hazards models. SmartCare captured 29% (16,791/58,010) of new PrEP clients; 49% of clients continued at one month, and 89% discontinued PrEP by February 2022. Women were less likely than men to discontinue PrEP (adjusted hazard ratio [aHR]: 0.89, 95% CI 0.86-0.92, z = - 6.99, p < 0.001), and PrEP clients aged ≥ 50 years were less likely to discontinue PrEP compared to clients 15-19 years (aHR: 0.53, 95% CI 0.48-0.58, z = - 13.04, p < 0.001). Zambia's EHR is a valuable resource for measuring individual-level PrEP continuation over time and can be used to inform HIV prevention programs.
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    Using best-worst scaling to inform policy decisions in Africa: a literature review.
    (2024-Sep-27) Beres LK; Campoamor NB; Hawthorn R; Mugambi ML; Mulabe M; Vhlakis N; Kabongo M; Schuster A; Bridges JFP; Department of Biomedical Informatics, The Ohio State University College of Medicine, 220 Lincoln Tower, 1800 Cannon Drive, Columbus, OH, 43210, USA. John.Bridges@osumc.edu.; Center for the Advancement of Team Science, Analytics, and Systems Thinking in Health Services and Implementation Science Research (CATALYST), The Ohio State University, 700 Ackerman Road, Columbus, OH, 43202, USA.; Department of Biomedical Informatics, The Ohio State University College of Medicine, 220 Lincoln Tower, 1800 Cannon Drive, Columbus, OH, 43210, USA.; Centre for Infectious Disease Research in Zambia, Stand 378A / 15, Main Street, P.O. Box 34681, Ibex, Lusaka, Zambia.; Department of Global Health, University of Washington, UW Box #351620, Seattle, WA, 98195, USA.; Department of International Health, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe Street, Office, Baltimore, MD, 5032, 21205, USA.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)
    BACKGROUND: Stakeholder engagement in policy decision-making is critical to inform required trade-offs, especially in low-and-middle income settings, such as many African countries. Discrete-choice experiments are now commonly used to engage stakeholders in policy decisions, but other methods such as best-worst scaling (BWS), a theory-driven prioritization technique, could be equally important. We sought to document and explore applications of BWS to assess stakeholder priorities in the African context to bring attention to BWS as a method and to assess how and why it is being used to inform policy. METHODS: We conducted a literature review of published applications of BWS for prioritization in Africa. RESULTS: Our study identified 35 studies, with the majority published in the past four years. BWS has most commonly been used in agriculture (43%) and health (34%), although its broad applicability is demonstrated through use in fields influencing social and economic determinants of health, including business, environment, and transportation. Published studies from eastern, western, southern, and northern Africa include a broad range of sample sizes, design choices, and analytical approaches. Most studies are of high quality and high policy relevance. Several studies cited benefits of using BWS, with many of those citing potential limitations rather than observed limitations in their study. CONCLUSIONS: Growing use of the method across the African continent demonstrates its feasibility and utility, recommending it for consideration among researchers, program implementers, policy makers, and funders when conducting preference research to influence policy and improve health systems. REGISTRATION: The review was registered on PROSPERO (CRD42020209745).