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The CIDRZ Research Repository serves as an open-access archive for peer-reviewed publications, conference papers, and other scholarly outputs from CIDRZ researchers. Our goal is to promote the dissemination of knowledge and support evidence-based public health initiatives.
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Item Operational characteristics of antiretroviral therapy clinics in Zambia: a time and motion analysis.(2019-Apr-24) Tampi RP; Tembo T; Mukumba-Mwenechanya M; Sharma A; Dowdy DW; Holmes CB; Bolton-Moore C; Sikazwe I; Tucker A; Sohn H; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD, 21205, USA.; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD, 21205, USA. hsohn6@jhu.edu.; Centers for Infectious Disease Research (CIDRZ), Lusaka, Zambia.BACKGROUND: The mass scale-up of antiretroviral therapy (ART) in Zambia has taken place in the context of limited infrastructure and human resources resulting in many operational side-effects. In this study, we aimed to empirically measure current workload of ART clinic staff and patient wait times and service utilization. METHODS: We conducted time and motion (TAM) studies from both the healthcare worker (HCW) and patient perspectives at 10 ART clinics throughout Zambia. Trained personnel recorded times for consecutive discrete activities based on direct observation of clinical and non-clinical activities performed by counselors, clinical officers, nurses, and pharmacy technicians. For patient TAM, we recruited consenting patients and recorded times of arrival and departure and major ART services utilized. Data from 10 clinics were pooled to evaluate median time per patient spent for each activity and patient duration of stay in the clinic. RESULTS: The percentage of observed clinical time for direct patient interaction (median time per patient encounter) was 43.1% for ART counselors (4 min, interquartile range [IQR] 2-7), 46.1% for nurses (3 min, IQR 2-4), 57.2% for pharmacy technicians (2 min, IQR 1-2), and 78.5% for clinical officers (3 min, IQR 2-5). Patient workloads for HCWs were heaviest between 8 AM and 12 PM with few clinical activities observed after 2 PM. The length of patient visits was inversely associated with arrival time - patients arriving prior to 8 AM spent 61% longer at the clinic than those arriving after 8 AM (277 vs. 171 min). Overall, patients spent 219 min on average for non-clinical visits, and 244 min for clinical visits, but this difference was not significant in rural clinics. In comparison, total time patients spent directly with clinic staff were 9 and 12 min on average for non-clinical and clinical visits. CONCLUSION: Current Zambian ART clinic operations include substantial inefficiencies for both patients and HCWs, with workloads heavily concentrated in the first few hours of clinic opening, limiting HCW and patient interaction time. Use of a differentiated care model may help to redistribute workloads during operational hours and prevent backlogs of patients waiting for hours before clinic opening, which may substantially improve ART delivery in the Zambian context.Item Economic evaluation of implementation science outcomes in low- and middle-income countries: a scoping review.(2022-Nov-16) Malhotra A; Thompson RR; Kagoya F; Masiye F; Mbewe P; Mosepele M; Phiri J; Sambo J; Barker A; Cameron DB; Davila-Roman VG; Effah W; Hutchinson B; Laxy M; Newsome B; Watkins D; Sohn H; Dowdy DW; Technical University of Munich, Munich, Germany.; Fogarty International Center (FIC), National Institutes of Health (NIH), Bethesda, MD, USA.; University of Washington, Seattle, WA, USA.; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. ddowdy1@jhmi.edu.; Cavendish University Zambia, Lusaka, Zambia.; Ezintsha, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa.; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.; University of Botswana, Gaborone, Botswana.; Center for Global Noncommunicable Diseases, RTI International, Seattle, WA, USA.; Infectious Diseases Research Collaboration, Kampala, Uganda.; Washington University in Saint Louis, Saint Louis, MO, USA.; Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, South Korea.; Department of Health Policy and Management, Yale School of Public Health, New Haven, CT, USA.; Centre for Infectious Disease Research in Zambia, Lusaka, Zambia.; University of Zambia, Lusaka, Zambia.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)BACKGROUND: Historically, the focus of cost-effectiveness analyses has been on the costs to operate and deliver interventions after their initial design and launch. The costs related to design and implementation of interventions have often been omitted. Ignoring these costs leads to an underestimation of the true price of interventions and biases economic analyses toward favoring new interventions. This is especially true in low- and middle-income countries (LMICs), where implementation may require substantial up-front investment. This scoping review was conducted to explore the topics, depth, and availability of scientific literature on integrating implementation science into economic evaluations of health interventions in LMICs. METHODS: We searched Web of Science and PubMed for papers published between January 1, 2010, and December 31, 2021, that included components of both implementation science and economic evaluation. Studies from LMICs were prioritized for review, but papers from high-income countries were included if their methodology/findings were relevant to LMIC settings. RESULTS: Six thousand nine hundred eighty-six studies were screened, of which 55 were included in full-text review and 23 selected for inclusion and data extraction. Most papers were theoretical, though some focused on a single disease or disease subset, including: mental health (n = 5), HIV (n = 3), tuberculosis (n = 3), and diabetes (n = 2). Manuscripts included a mix of methodology papers, empirical studies, and other (e.g., narrative) reviews. Authorship of the included literature was skewed toward high-income settings, with 22 of the 23 papers featuring first and senior authors from high-income countries. Of nine empirical studies included, no consistent implementation cost outcomes were measured, and only four could be mapped to an existing costing or implementation framework. There was also substantial heterogeneity across studies in how implementation costs were defined, and the methods used to collect them. CONCLUSION: A sparse but growing literature explores the intersection of implementation science and economic evaluation. Key needs include more research in LMICs, greater consensus on the definition of implementation costs, standardized methods to collect such costs, and identifying outcomes of greatest relevance. Addressing these gaps will result in stronger links between implementation science and economic evaluation and will create more robust and accurate estimates of intervention costs. TRIAL REGISTRATION: The protocol for this manuscript was published on the Open Science Framework. It is available at: https://osf.io/ms5fa/ (DOI: 10.17605/OSF.IO/32EPJ).