School of Health and Social Care, University of Essex, Essex, United Kingdom.
Division of Public Health, University of Sheffield, Sheffield, United Kingdom.
PLoS One. 2024 Jul 10;19(7):e0306786. doi: 10.1371/journal.pone.0306786. eCollection 2024.
Many areas of healthcare are impacted by a paucity of research that is translatable to clinical practice. Research utilising real-world data, such as routinely collected patient data, may be one option to efficiently create evidence to inform practice and service delivery. Such studies are also valuable for exploring (in)equity of services and outcomes, and benefit from using non-selected samples representing the diversity of the populations served in the 'real world'. This scoping review aims to identify and map the published research which utilises routinely collected clinical healthcare data. A secondary aim is to explore the extent to which this literature supports the pursuit of social justice in health, including health inequities and intersectional approaches.
This review utilises Arksey and O'Malley's methodological framework for scoping reviews and draws on the recommended enhancements of this framework to promote a team-based and mixed methods approach. This includes searching electronic databases and screening papers based on a pre-specified inclusion and exclusion criteria. Data relevant to the research aims will be extracted from included papers, including the clinical/professional area of the topic, the source of data that was used, and whether it addresses elements of social justice. All screening and reviewing will be collaborative and iterative, drawing on strengths of the research team and responsive changes to challenges will be made. Quantitative data will be analysed descriptively, and conceptual content analysis will be utilised to understand qualitative data. These will be collectively synthesised in alignment to the research aims.
Our findings will highlight the extent to which such research is being conducted and published, including gaps and make recommendations for future endeavours for real-world data studies. The findings from this scoping review will be relevant for practitioners and researchers, as well as health service managers, commissioners, and research funders.
许多医疗保健领域都缺乏可转化为临床实践的研究。利用真实世界数据（如常规收集的患者数据）进行研究可能是一种有效方法，可以创建证据来为实践和服务提供提供信息。此类研究对于探索服务和结果的公平性也很有价值，并受益于使用代表实际服务人群多样性的非选择性样本。本范围综述旨在确定和绘制利用常规收集的临床医疗保健数据进行的已发表研究，并探索该文献在多大程度上支持健康领域的社会正义，包括健康不公平和交叉方法。
本综述利用 Arksey 和 O'Malley 的范围综述方法框架，并借鉴该框架的推荐增强功能，以促进团队合作和混合方法方法。这包括搜索电子数据库并根据预先指定的纳入和排除标准筛选论文。将从纳入的论文中提取与研究目的相关的数据，包括主题的临床/专业领域、使用的数据来源，以及是否涉及社会正义元素。所有筛选和审查都将是协作和迭代的，利用研究团队的优势，并对挑战做出响应性的改变。定量数据将进行描述性分析，概念内容分析将用于理解定性数据。这些将根据研究目的进行集体综合。
我们的研究结果将突出此类研究的进行和发表程度，包括差距，并为真实世界数据研究的未来努力提出建议。本范围综述的研究结果将对从业者和研究人员以及卫生服务管理人员、决策者和研究资助者具有相关性。
