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首页> 外文期刊>International journal of medical informatics >Modeling cancer clinical trials using HL7 FHIR to support downstream applications: A case study with colorectal cancer data
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Modeling cancer clinical trials using HL7 FHIR to support downstream applications: A case study with colorectal cancer data

机译：使用HL7 FHIR建模癌症临床试验支持下游应用：以结肠直肠癌数据为例

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Background and objective: Identification and Standardization of data elements used in clinical trials may control and reduce the cost and errors during the operational process, and enable seamless data exchange between the electronic data capture (EDC) systems and Electronic Health Record (EHR) systems. This study presents a methodology to comprehensively capture the clinical trial data element needs.Materials and methods: Case report forms (CRF) for clinical trial data collection were used to approximate the clinical information need, whereby these information needs were then mapped to a semantically equivalent field within an existing FHIR cancer profile. For items without a semantically equivalent field, we considered these items to be information needs that cannot be represented in current standards and proposed extensions to support these needs.Results: We successfully identified 62 discrete items from a preliminary survey of 43 base questions in four CRFs used in colorectal cancer clinical trials, in which 28 items are modeled with FHIR extensions and their associated responses for colorectal cancer. We achieved promising results in the data population of the CRFs with average Precision 98.5 %, Recall 96.2 %, and F-measure 96.8 % for all base questions. We also demonstrated the autofilled answers in CRFs can be used to discover patient subgroups using a topic modeling approach.Conclusion: CRFs can be considered as a proxy for representing information needs for their respective cancer types. Mining the information needs can serve as a valuable resource for expanding existing standards to ensure they can comprehensively represent relevant clinical data without loss of granularity.
机译：背景和目的：临床试验中使用的数据元素的识别和标准化可以控制和降低操作过程中的成本和错误，并在电子数据捕获（EDC）系统和电子健康记录（EHR）系统之间实现无缝数据交换。本研究提出了一种全面捕获临床试验数据元素需求的方法。用于临床试验数据收集的材料和方法：案例报告表格（CRF）用于近似临床信息需要，从而将这些信息所需的需要映射到语义上等效现有的FHIR癌症剖面内的领域。对于没有语义等同字段的项目，我们认为这些项目是无法以当前标准中的信息需求和建议的扩展来支持这些项目，以支持这些需求。结果：我们从四个CRF中的43个基本问题的初步调查中成功地确定了62项离散项目用于结直肠癌癌症临床试验，其中28项用FHIR延伸和它们对结肠直肠癌相关的反应进行建模。我们实现了有希望的CRF数据群，平均精度为98.5％，召回96.2％，以及所有基本问题的F-Mabote 96.8％。我们还展示了CRF中的自动填充答案可用于使用主题建模方法发现患者子组。结论：CRF可以被视为代表各自癌症类型的信息需求的代理。采矿信息需求可以作为扩大现有标准的宝贵资源，以确保他们可以全面代表相关的临床数据而不会损失粒度。

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