Browsing by Author "Davies, Justine"

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    Improving nursing documentation for surgical patients in a referral hospital in Freetown, Sierra Leone : protocol for assessing feasibility of a pilot multifaceted quality improvement hybrid type project
    (BioMed Central, 2021-01-27) Brima, Nataliya; Sevdalis, Nick; Daoh, K.; Deen, B.; Kamara, T. B.; Wurie, Haja; Davies, Justine; Leather, Andrew J. M.
    Background: There is an urgent need to improve quality of care to reduce avoidable mortality and morbidity from surgical diseases in low- and middle-income countries. Currently, there is a lack of knowledge about how evidence-based health system strengthening interventions can be implemented effectively to improve quality of care in these settings. To address this gap, we have developed a multifaceted quality improvement intervention to improve nursing documentation in a low-income country hospital setting. The aim of this pilot project is to test the intervention within the surgical department of a national referral hospital in Freetown, Sierra Leone. Methods: This project was co-developed and co-designed by in-country stakeholders and UK-based researchers, after a multiple-methodology assessment of needs (qualitative, quantitative), guided by a participatory ‘Theory of Change’ process. It has a mixed-method, quasi-experimental evaluation design underpinned by implementation and improvement science theoretical approaches. It consists of three distinct phases—(1) preimplementation( project set up and review of hospital relevant policies and forms), (2) intervention implementation (awareness drive, training package, audit and feedback), and (3) evaluation of (a) the feasibility of delivering the intervention and capturing implementation and process outcomes, (b) the impact of implementation strategies on the adoption, integration, and uptake of the intervention using implementation outcomes, (c) the intervention’s effectiveness For improving nursing in this pilot setting. Discussion: We seek to test whether it is possible to deliver and assess a set of theory-driven interventions to improve the quality of nursing documentation using quality improvement and implementation science methods and frameworks in a single facility in Sierra Leone. The results of this study will inform the design of a large-scale effectiveness-implementation study for improving nursing documentation practices for patients throughout hospitals in Sierra Leone.
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    An integrated approach to processing WHO-2016 verbal autopsy data : the InterVA-5 model
    (BMC (part of Springer Nature), 2019-05-30) Byass, Peter; Hussain-Alkhateeb, Laith; D’Ambruoso, Lucia; Clark, Samuel; Davies, Justine; Fottrell, Edward; Bird, Jon; Kabudula, Chodziwadziwa; Tollman, Stephen; Kahn, Kathleen; Schioler, Linus; Petzold, Max
    Background: Verbal autopsy is an increasingly important methodology for assigning causes to otherwise uncertified deaths, which amount to around 50% of global mortality and cause much uncertainty for health planning. The World Health Organization sets international standards for the structure of verbal autopsy interviews and for cause categories that can reasonably be derived from verbal autopsy data. In addition, computer models are needed to efficiently process large quantities of verbal autopsy interviews to assign causes of death in a standardised manner. Here, we present the InterVA-5 model, developed to align with the WHO-2016 verbal autopsy standard. This is a harmonising model that can process input data from WHO-2016, as well as earlier WHO-2012 and Tariff-2 formats, to generate standardised cause-specific mortality profiles for diverse contexts. The software development involved building on the earlier InterVA-4 model, and the expanded knowledge base required for InterVA-5 was informed by analyses from a training dataset drawn from the Population Health Metrics Research Collaboration verbal autopsy reference dataset, as well as expert input. Results: The new model was evaluated against a test dataset of 6130 cases from the Population Health Metrics Research Collaboration and 4009 cases from the Afghanistan National Mortality Survey dataset. Both of these sources contained around three quarters of the input items from the WHO-2016, WHO-2012 and Tariff-2 formats. Cause-specific mortality fractions across all applicable WHO cause categories were compared between causes assigned in participating tertiary hospitals and InterVA-5 in the test dataset, with concordance correlation coefficients of 0.92 for children and 0.86 for adults. The InterVA-5 model’s capacity to handle different input formats was evaluated in the Afghanistan dataset, with concordance correlation coefficients of 0.97 and 0.96 between the WHO-2016 and the WHO-2012 format for children and adults respectively, and 0.92 and 0.87 between the WHO-2016 and the Tariff-2 format respectively. Conclusions: Despite the inherent difficulties of determining “truth” in assigning cause of death, these findings suggest that the InterVA-5 model performs well and succeeds in harmonising across a range of input formats. As more primary data collected under WHO-2016 become available, it is likely that InterVA-5 will undergo minor reversioning in the light of practical experience. The model is an important resource for measuring and evaluating cause-specific mortality globally.