Browsing by Author "Herce M"

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    Effects of real-time electronic data entry on HIV programme data quality in Lusaka, Zambia.
    (2020-Mar-21) Moomba K; Williams A; Savory T; Lumpa M; Chilembo P; Tweya H; Harries AD; Herce M; Centre for Infectious Diseases Research in Zambia (CIDRZ), Lusaka, Zambia.; London School of Hygiene & Tropical Medicine, London, UK.; Institute for Global Health & Infectious Diseases, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.; Operational Centre Brussels, Medical Department, Médecins Sans Frontières - Operational Research Unit (LuxOR), MSF Luxembourg.; The Lighthouse Clinic, Lilongwe, Malawi.; International Union Against Tuberculosis and Lung Disease, Paris, France.
    SETTING: Human immunodeficiency virus (HIV) clinics in five hospitals and five health centres in Lusaka, Zambia, which transitioned from daily entry of paper-based data records to an electronic medical record (EMR) system by dedicated data staff (Electronic-Last) to direct real-time data entry into the EMR by frontline health workers (Electronic-First). OBJECTIVE: To compare completeness and accuracy of key HIV-related variables before and after transition of data entry from Electronic-Last to Electronic-First. DESIGN: Comparative cross-sectional study using existing secondary data. RESULTS: Registration data (e.g., date of birth) was 100% complete and pharmacy data (e.g., antiretroviral therapy regimen) was <90% complete under both approaches. Completeness of anthropometric and vital sign data was <75% across all facilities under Electronic-Last, and this worsened after Electronic-First. Completeness of TB screening and World Health Organization clinical staging data was also <75%, but improved with Electronic-First. Data entry errors for registration and clinical consultations decreased under Electronic-First, but errors increased for all anthropometric and vital sign variables. Patterns were similar in hospitals and health centres. CONCLUSION: With the notable exception of clinical consultation data, data completeness and accuracy did not improve after transitioning from Electronic-Last to Electronic-First. For anthropometric and vital sign variables, completeness and accuracy decreased. Quality improvement interventions are needed to improve Electronic-First implementation.
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    Lost in translation: key lessons from conducting dissemination and implementation science in Zambia.
    (2024-Oct-29) Maritim P; Munakampe MN; Nglazi M; Mweemba C; Sikombe K; Mbewe W; Silumbwe A; Jacobs C; Zulu JM; Herce M; Mutale W; Halwindi H; Department of Health Policy and Management, School of Public Health, University of Zambia, Lusaka, Zambia. triciamarie20@gmail.com.; Implementation Science Centre for Advancing Practice and Training (IMPACT), University of Zambia, Lusaka, Zambia. triciamarie20@gmail.com.; Implementation Science Centre for Advancing Practice and Training (IMPACT), University of Zambia, Lusaka, Zambia.; Department of Epidemiology and Biostatistics, School of Public Health, University of Zambia, Lusaka, Zambia.; Ministry of Health, Lusaka, Zambia.; Implementation Science Department, Centre for Infectious Disease Research in Zambia (CIDRZ), Lusaka, Zambia.; Department of Health Policy and Management, School of Public Health, University of Zambia, Lusaka, Zambia.
    BACKGROUND: As the field of implementation science continues to grow, its key concepts are being transferred into new contexts globally, such as Low and Middle Income Countries (LMICs), and its use is constantly being reexamined and expanded. Theoretical and methodological positions commonly used in implementation research and practice have great utility in our work but in many cases are at odds with LMIC contexts. As a team of implementation scientists based in Zambia, we offer this commentary as a critical self-reflection on what has worked and what could limit us from fully utilizing the field's promise for addressing health problems with contextual understanding. MAIN BODY: We used a 'premortem,' an approach used to generate potential alternatives from failed assumptions about a particular phenomenon, as a way to reflect on our experiences conducting implementation research and practice. By utilizing prospectively imagined hindsights, we were able to reflect on the past, present and possible future of the field in Zambia. Six key challenges identified were: (i) epistemic injustices; (ii) simplified conceptualizations of evidence-informed interventions; (iii) limited theorization of the complexity of low-resource contexts and it impacts on implementation; (iv) persistent lags in transforming research into practice; (v) limited focus on strategic dissemination of implementation science knowledge and (vi) existing training and capacity building initiatives' failure to engage a broad range of actors including practitioners through diverse learning models. CONCLUSION: Implementation science offers great promise in addressing many health problems in Zambia. Through this commentary, we hope to spur discussions on how implementation scientists can reimagine the future of the field by contemplating on lessons from our experiences in LMIC settings.