Abstract：
BACKGROUND: Clinical practice guidelines are statements which are based on the best available evidence, and their goal is to improve the quality of patient care. Integrating clinical practice guidelines into computer systems can help physicians reduce medical errors and help them to have the best possible practice. Guideline-based clinical decision support systems play a significant role in supporting physicians in their decisions. Meantime, system errors are the most critical concerns in designing decision support systems that can affect their performance and efficacy. A well-developed ontology can be helpful in this matter. The proposed systematic review will specify the methods, components, language of rules, and evaluation methods of current ontology-driven guideline-based clinical decision support systems.
METHODS: This review will identify literature through searching MEDLINE (via Ovid), PubMed, EMBASE, Cochrane Library, CINAHL, ScienceDirect, IEEEXplore, and ACM Digital Library. Gray literature, reference lists, and citing articles of the included studies will be searched. The quality of the included studies will be assessed by the mixed methods appraisal tool (MMAT-version 2018). At least two independent reviewers will perform the screening, quality assessment, and data extraction. A third reviewer will resolve any disagreements. Proper data analysis will be performed based on the type of system and ontology engineering evaluation data.
CONCLUSIONS: The study will provide evidence regarding applying ontologies in guideline-based clinical decision support systems. The findings of this systematic review will be a guide for decision support system designers and developers, technologists, system providers, policymakers, and stakeholders. Ontology builders can use the information in this review to build well-structured ontologies for personalized medicine.
BACKGROUND: PROSPERO CRD42018106501.
METHODS: This review will identify literature through searching MEDLINE (via Ovid), PubMed, EMBASE, Cochrane Library, CINAHL, ScienceDirect, IEEEXplore, and ACM Digital Library. Gray literature, reference lists, and citing articles of the included studies will be searched. The quality of the included studies will be assessed by the mixed methods appraisal tool (MMAT-version 2018). At least two independent reviewers will perform the screening, quality assessment, and data extraction. A third reviewer will resolve any disagreements. Proper data analysis will be performed based on the type of system and ontology engineering evaluation data.
CONCLUSIONS: The study will provide evidence regarding applying ontologies in guideline-based clinical decision support systems. The findings of this systematic review will be a guide for decision support system designers and developers, technologists, system providers, policymakers, and stakeholders. Ontology builders can use the information in this review to build well-structured ontologies for personalized medicine.
BACKGROUND: PROSPERO CRD42018106501.
摘要：
背景：临床实践指南是基于现有最佳证据的声明，他们的目标是提高病人护理的质量。将临床实践指南集成到计算机系统中可以帮助医生减少医疗错误并帮助他们获得最佳实践。基于指南的临床决策支持系统在支持医生的决策方面发挥着重要作用。同时,系统错误是决策支持系统设计中最关键的问题，可以影响其性能和效率。一个完善的本体可以在这个问题上有所帮助。拟议的系统审查将具体说明方法，组件,规则的语言，当前基于本体驱动的基于指南的临床决策支持系统的评价方法。
方法：这篇综述将通过搜索MEDLINE（通过Ovid）来识别文献，PubMed,EMBASE,科克伦图书馆,CINAHL,ScienceDirect,IEEEXplore,ACM数字图书馆。灰色文学，引用列表,并将检索所纳入研究的引用文章。纳入研究的质量将通过混合方法评估工具（MMAT-2018版）进行评估。至少有两名独立审稿人将进行筛选，质量评估，和数据提取。第三位审稿人将解决任何分歧。将根据系统类型和本体工程评估数据进行适当的数据分析。
结论：该研究将为在基于指南的临床决策支持系统中应用本体提供证据。这项系统审查的结果将为决策支持系统设计人员和开发人员提供指导，技术人员,系统提供商,政策制定者，和利益相关者。本体构建者可以使用本综述中的信息为个性化医疗构建结构良好的本体。
背景：PROSPEROCRD42018106501.
方法：这篇综述将通过搜索MEDLINE（通过Ovid）来识别文献，PubMed,EMBASE,科克伦图书馆,CINAHL,ScienceDirect,IEEEXplore,ACM数字图书馆。灰色文学，引用列表,并将检索所纳入研究的引用文章。纳入研究的质量将通过混合方法评估工具（MMAT-2018版）进行评估。至少有两名独立审稿人将进行筛选，质量评估，和数据提取。第三位审稿人将解决任何分歧。将根据系统类型和本体工程评估数据进行适当的数据分析。
结论：该研究将为在基于指南的临床决策支持系统中应用本体提供证据。这项系统审查的结果将为决策支持系统设计人员和开发人员提供指导，技术人员,系统提供商,政策制定者，和利益相关者。本体构建者可以使用本综述中的信息为个性化医疗构建结构良好的本体。
背景：PROSPEROCRD42018106501.
