Chishtie Jawad Ahmed, Babineau Jessica, Bielska Iwona Anna, Cepoiu-Martin Monica, Irvine Michael, Koval Andriy, Marchand Jean-Sebastien, Turcotte Luke, Jeji Tara, Jaglal Susan
Rehabilitation Sciences Institute, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
Institute of Health Services and Policy Research, Canadian Institutes of Health Research, Ottawa, ON, Canada.
JMIR Res Protoc. 2019 Oct 28;8(10):e14019. doi: 10.2196/14019.
Visual analytics (VA) promotes the understanding of data using visual, interactive techniques and using analytic and visual engines. The analytic engine includes machine learning and other automated techniques, whereas common visual outputs include flow maps and spatiotemporal hotspots for studying service gaps and disease distribution. The principal objective of this scoping review is to examine the state of science on VA and the various tools, strategies, and frameworks used in population health and health services research (HSR).
The purpose of this scoping review is to develop an overarching global view of established techniques, frameworks, and methods of VA in population health and HSR. The main objectives are to explore, map, and synthesize the literature related to VA in its application to the two main focus areas of health care.
We will use established scoping review methods to meet the study objective. As the use of the term visual analytics is inconsistent, one of the major challenges was operationalizing the concepts for developing the search strategy, based on the three main concepts of population health, HSR, and VA. We included peer reviewed and grey literature sources from 2005 till March 2019 in the search. Independent teams of researchers will screen the titles, abstracts and full text articles, whereas an independent researcher will arbiter conflicts. Data will be abstracted and presented using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews checklist and explanation by two independent researchers.
As of late August 2019, the scoping review is in the full-text screening stage. Data synthesis will follow and the first results are expected to be submitted for publication in December 2019. In this protocol, the methods for undertaking this scoping review are detailed. We present how we operationalized the varied concepts of population health, health services, and VA. The main results of the scoping review will synthesize peer reviewed and grey literature sources on the main methods of VA in the interrelated fields of population health and health services research from January 2005 till March 2019.
VA is being increasingly used and integrated with emerging technologies to support decision making using large data sets. This scoping review of the VA tools, strategies, and frameworks applied to population health and health services aims to increase awareness of this approach for uptake by decision makers working within and toward developing learning health systems globally.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/14019.
可视化分析（VA）通过视觉交互技术以及分析和视觉引擎促进对数据的理解。分析引擎包括机器学习和其他自动化技术，而常见的视觉输出包括用于研究服务差距和疾病分布的流程图和时空热点图。本范围综述的主要目的是考察VA的科学现状以及在人群健康和卫生服务研究（HSR）中使用的各种工具、策略和框架。
本范围综述的目的是对人群健康和HSR中VA的既定技术、框架和方法形成一个总体的全球视角。主要目标是探索、梳理并综合与VA在医疗保健两个主要重点领域应用相关的文献。
我们将使用既定的范围综述方法来实现研究目标。由于“可视化分析”一词的使用并不一致，主要挑战之一是基于人群健康、HSR和VA这三个主要概念，将这些概念转化为可操作的搜索策略。我们在搜索中纳入了2005年至2019年3月期间的同行评审文献和灰色文献来源。独立的研究团队将筛选标题、摘要和全文文章，而由一名独立研究人员来仲裁冲突。数据将由两名独立研究人员使用系统评价和Meta分析的首选报告项目扩展版（PRISMA-ScR）清单进行提取和呈现，并加以解释。
截至2019年8月下旬，范围综述正处于全文筛选阶段。随后将进行数据综合，预计第一批结果将于2019年12月提交发表。在本方案中，详细介绍了进行此范围综述的方法。我们展示了如何将人群健康、卫生服务和VA的不同概念进行操作化。范围综述的主要结果将综合2005年1月至2019年3月期间同行评审文献和灰色文献来源中关于VA在人群健康和卫生服务研究相关领域主要方法的内容。
VA正越来越多地被使用，并与新兴技术相结合，以支持利用大数据集进行决策。本次对应用于人群健康和卫生服务的VA工具、策略和框架的范围综述旨在提高全球范围内致力于发展学习型卫生系统的决策者对这种方法的认识。
国际注册报告识别号（IRRID）：DERR1-10.2196/14019
