Cancer Care Ontario (CCO) is the clinical advisor to the Ontario Ministry of Health and Long-Term Care for the funding and delivery of cancer services. Data contained in radiology reports are inaccessible for analysis without significant manual cost and effort. Synoptic reporting includes highly structured reporting and discrete data capture, which could unlock these data for clinical and evaluative purposes. To assess the feasibility of implementing synoptic radiology reporting, a trial implementation was conducted at one hospital within CCO's Lung Cancer Screening Pilot for People at High Risk. This project determined that it is feasible to capture synoptic data with some barriers. Radiologists require increased awareness when reporting cases with a large number of nodules due to lack of automation within the system. These challenges may be mitigated by implementation of some report automation. Domains such as pathology and public health reporting have addressed some of these challenges with standardized reports based on interoperable standards, and radiology could borrow techniques from these domains to assist in implementing synoptic reporting. Data extraction from the reports could also be significantly automated to improve the process and reduce the workload in collecting the data. RadLex codes aided the difficult data extraction process, by helping label potential ambiguity with common terms and machine-readable identifiers.

中文翻译：

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解锁放射学报告数据：在低剂量CT癌症筛查中对映放射学报告的实现。

安大略省癌症护理（CCO）是安大略省卫生和长期护理部的临床顾问，负责资助和提供癌症服务。放射报告中包含的数据无法进行分析，而无需付出大量的人工成本和精力。摘要报告包括高度结构化的报告和离散的数据捕获，可以为临床和评估目的解锁这些数据。为了评估实施天气概要放射学报告的可行性，在CCO的肺癌高危人群筛查试验中心的一家医院中进行了试验实施。该项目确定，捕获具有某些障碍的天气数据是可行的。由于系统内缺乏自动化，放射科医生在报告带有大量结节的病例时需要提高认识。这些挑战可以通过实施某些报告自动化来缓解。病理学和公共卫生报告等领域已经通过基于可互操作标准的标准化报告解决了其中一些挑战，放射学可以借鉴这些领域的技术来协助实施天气报告。从报告中提取数据也可以实现高度自动化，以改善流程并减少收集数据的工作量。RadLex代码通过使用常用术语和机器可读标识符帮助标记潜在的歧义，从而帮助了困难的数据提取过程。放射学可以借鉴这些领域的技术来协助实施天气报告。从报告中提取数据也可以大大自动化，以改善流程并减少收集数据的工作量。RadLex代码通过使用常用术语和机器可读标识符帮助标记潜在的歧义，从而帮助了困难的数据提取过程。放射学可以借鉴这些领域的技术来协助实施天气报告。从报告中提取数据也可以实现高度自动化，以改善流程并减少收集数据的工作量。RadLex代码通过使用常用术语和机器可读标识符帮助标记潜在的歧义，从而帮助了困难的数据提取过程。