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Improving the creation and reporting of structured findings during digital pathology review

机译:在数字病理学检查中改善结构化发现的创建和报告

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Background&58; Today, pathology reporting consists of many separate tasks, carried out by multiple people. Common tasks include dictation during case review, transcription, verification of the transcription, report distribution, and report the key findings to follow-up registries. Introduction of digital workstations makes it possible to remove some of these tasks and simplify others. This study describes the work presented at the Nordic Symposium on Digital Pathology 2015, in Link?ping, Sweden. Methods&58; We explored the possibility to have a digital tool that simplifies image review by assisting note-taking, and with minimal extra effort, populates a structured report. Thus, our prototype sees reporting as an activity interleaved with image review rather than a separate final step. We created an interface to collect, sort, and display findings for the most common reporting needs, such as tumor size, grading, and scoring. Results&58; The interface was designed to reduce the need to retain partial findings in the head or on paper, while at the same time be structured enough to support automatic extraction of key findings for follow-up registry reporting. The final prototype was evaluated with two pathologists, diagnosing complicated partial mastectomy cases. The pathologists experienced that the prototype aided them during the review and that it created a better overall workflow. Conclusions&58; These results show that it is feasible to simplify the reporting tasks in a way that is not distracting, while at the same time being able to automatically extract the key findings. This simplification is possible due to the realization that the structured format needed for automatic extraction of data can be used to offload the pathologists′ working memory during the diagnostic review.
机译:背景&58;如今,病理报告由许多人执行的许多单独的任务组成。常见的任务包括在案件审阅中进行口授,笔录,笔录的验证,报告分发以及将关键发现报告给后续注册表。数字工作站的引入使删除其中一些任务并简化其他任务成为可能。这项研究描述了在瑞典林雪平举行的2015年北欧数字病理学研讨会上提出的工作。方法&58;我们探索了拥有一种数字工具的可能性,该工具可以通过辅助记录来简化图像查看,并且只需花费很少的额外精力即可填充结构化报告。因此,我们的原型将报告视为与图像审阅交错的活动,而不是单独的最终步骤。我们创建了一个界面来收集,分类和显示针对最常见的报告需求的发现,例如肿瘤大小,分级和评分。结果&58;该界面旨在减少在头部或纸上保留部分调查结果的需要,同时,其结构应足以支持自动提取关键调查结果以进行后续注册管理机构报告。最终的原型由两名病理学家评估,诊断出复杂的部分乳房切除术病例。病理学家体验到原型在审查过程中为他们提供了帮助,并且创建了更好的整体工作流程。结论&58;这些结果表明,以不分散注意力的方式简化报告任务是可行的,同时又能够自动提取关键发现。由于认识到自动提取数据所需的结构化格式可用于在诊断检查期间减轻病理学家的工作记忆,因此这种简化是可能的。

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