Department of Prosthodontics, Faculty of Dentistry, Manipal University College Malaysia, Bukit Baru, Malaysia
Institute for Research in Operative Medicine (IFOM), Faculty of Health-School of Medicine, Witten/Herdecke University, Cologne, Nordrhein-Westfalen, Germany.
BMJ Glob Health. 2022 May;7(5). doi: 10.1136/bmjgh-2021-008113.
Uncertainty is an inevitable part of healthcare and a source of confusion and challenge to decision-making. Several taxonomies of uncertainty have been developed, but mainly focus on decisions in clinical settings. Our goal was to develop a holistic model of uncertainty that can be applied to both clinical as well as public and global health scenarios.
We searched Medline, Embase, CINAHL, Scopus and Google scholar in March 2021 for literature reviews, qualitative studies and case studies related to classifications or models of uncertainty in healthcare. Empirical articles were assessed for study limitations using the Critical Appraisal Skills Programme (CASP) checklist. We synthesised the literature using a thematic analysis and developed a dynamic multilevel model of uncertainty. We sought patient input to assess relatability of the model and applied it to two case examples.
We screened 4125 studies and included 15 empirical studies, 13 literature reviews and 5 case studies. We identified 77 codes and organised these into 26 descriptive and 11 analytical themes of uncertainty. The themes identified are global, public health, healthcare system, clinical, ethical, relational, personal, knowledge exchange, epistemic, aleatoric and parameter uncertainty. The themes were included in a model, which captures the macro, meso and microlevels and the inter-relatedness of uncertainty. We successfully piloted the model on one public health example and an environmental topic. The main limitations are that the research input into our model predominantly came from North America and Europe, and that we have not yet tested the model in a real-life setting.
We developed a model that can comprehensively capture uncertainty in public and global health scenarios. It builds on models that focus solely on clinical settings by including social and political contexts and emphasising the dynamic interplay between different areas of uncertainty.
不确定性是医疗保健中不可避免的一部分，也是决策产生困惑和挑战的根源。已经开发出了几种不确定性分类法，但主要侧重于临床环境中的决策。我们的目标是开发一种全面的不确定性模型，该模型既可以应用于临床场景，也可以应用于公共和全球卫生场景。
我们于 2021 年 3 月在 Medline、Embase、CINAHL、Scopus 和 Google Scholar 上搜索了与医疗保健中的不确定性分类或模型相关的文献综述、定性研究和案例研究。使用批判性评估技能计划（CASP）检查表评估实证文章的研究局限性。我们使用主题分析综合文献，并开发了一个不确定性动态多层次模型。我们寻求患者的意见来评估模型的相关性，并将其应用于两个案例示例。
我们筛选了 4125 项研究，纳入了 15 项实证研究、13 项文献综述和 5 项案例研究。我们确定了 77 个代码，并将这些代码组织成 26 个描述性主题和 11 个分析性主题的不确定性。确定的主题包括全球、公共卫生、医疗保健系统、临床、伦理、关系、个人、知识交流、认识论、随机和参数不确定性。这些主题被纳入一个模型中，该模型捕捉了宏观、中观和微观层面以及不确定性的相互关系。我们成功地在一个公共卫生案例和一个环境主题上对该模型进行了试点。主要限制是，我们模型的研究输入主要来自北美和欧洲，并且我们尚未在现实环境中测试该模型。
我们开发了一种可以全面捕捉公共和全球卫生场景中不确定性的模型。它通过纳入社会和政治背景，并强调不同不确定性领域之间的动态相互作用，构建在仅关注临床环境的模型之上。
