Evidence-Based Decision Making for Nutrition Policy and Programme Formulation in Ethiopia: A Qualitative Study Exploring Barriers and Facilitators

Objectives Despite much nutrition research conducted in Ethiopia, none has described existing opportunities for synergy or possible missed opportunities to use research to inform policy and program decisions to foster accelerated progress. The study aimed to describe prevailing processes on evidence use in formulating nutrition policy and program decisions and identify potential barriers and opportunities for evidence-based decision-making for nutrition for Ethiopia's context. Methods In 2017, 29 purposively selected key informants (KIs) were interviewed. They were identified using a consultative stakeholder mapping workshop and represented National Nutrition Program coordinators, key actors in government sectors, program coordinators from selected local and international NGOs, local and international universities and research institutes involved in nutrition research and key actors in policy decision-making. A framework analysis including identifying themes, coding, indexing, charting, mapping and interpretation was used. A validation workshop discussed findings and added perspectives to interpretation. Results The KIs perceived that demand for evidence from the Ethiopian government had been increasing over time. Majority referred to poor research quality as a barrier for using research in decision-making processes. Other challenges identified included limited cross-linkage, coordination gaps between researchers and decision makers, and inadequate translation of research evidence into meaningful information for policy makers. Availability of different forums, research dissemination conferences and suitable institutional structures that enable research and evidence dissemination were considered to be opportunities that should be leveraged to inform policy making. Conclusions The quality of research, and of collaborative engagement between those who produce evidence and decision makers who formulate policies need to be strengthened. Regular evidence dissemination events and publication of action oriented easy to read briefs could increase use of evidence among nutrition policy makers. Funding Sources Ethiopian Public Health Institute and Evidence-informed Decision-making in Health and Nutrition Network.

Predictors of Citations of Systematic Reviews in Oral Implantology: A Cross-Sectional Bibliometric Analysis

Citation count is an important measure of academic productivity and evidence dissemination. This cross-sectional bibliometric assessment is aimed at identifying predictors of citations of systematic reviews (SRs) published in 2010 in the field of oral implantology. SRs published in the field of oral implantology in the year 2010 in three electronic databases were identified. Following which, data were extracted from selected SRs including number of authors, number of institutions, international collaboration status, number of references, and journal impact factor (JIF). Methodological quality of SR was evaluated separately using the “Assessing the Methodological Quality of Systematic Reviews” (AMSTAR) checklist. Bivariate associations between the extracted variables, including AMSTAR score, and citation count were examined. Simultaneous effect of all extracted variables and SR citation count were examined by a multivariable linear regression model. In the included 26 SRs, the number of authors and institutions ranged from 1 to 8 and 1 to 5, respectively. The JIF was on average 3.22 (±1.81), and the AMSTAR score ranged from 2 to 10. Total citations ranged from 0 to 123 in Web of Science and 1 to 245 in Google Scholar. Our analysis revealed a lack of significant ( p > .05) correlation between the extracted variables and citation count. No reliable indicator that could predict the citation counts for SRs published in 2010 in oral implantology was identified. Of importance was the lack of significant correlation between AMSTAR score and citation count, which underscores the importance of careful appraisal of SR before incorporating its findings in clinical practice.

A unified conceptual model for diagnostic errors: underdiagnosis, overdiagnosis, and misdiagnosis

Progress in diagnostic error research has been hampered by a lack of unified terminology and definitions. This article proposes a novel framework for considering diagnostic errors, offering a unified conceptual model for underdiagnosis, overdiagnosis, and misdiagnosis. The model clarifies the critical separation between ‘diagnostic process failures’ (incorrect workups) and ‘diagnosis label failures’ (incorrect diagnoses). By dividing processes into those that are substandard, suboptimal, or optimal, important distinctions are drawn between ‘preventable’, ‘reducible,’ and ‘unavoidable’ diagnostic errors. The new model emphasizes the importance of mitigating diagnosis-related harms, regardless of whether the solutions require traditional safety strategies (preventable errors), more effective evidence dissemination (reducible errors; harms from overtesting and overdiagnosis), or new scientific discovery (currently unavoidable errors). Doing so maximizes our ability to prioritize solving various diagnosis-related problems from a societal value perspective. This model should serve as a foundation for developing consensus terminology and operationalized definitions for relevant diagnostic-error categories.