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首页> 外文期刊>Journal of Digital Imaging >Automated Detection of Radiology Reports that Document Non-routine Communication of Critical or Significant Results
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Automated Detection of Radiology Reports that Document Non-routine Communication of Critical or Significant Results

机译：自动检测放射报告，该报告记录了关键或重要结果的非常规交流

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The purpose of this investigation is to develop an automated method to accurately detect radiology reports that indicate non-routine communication of critical or significant results. Such a classification system would be valuable for performance monitoring and accreditation. Using a database of 2.3 million free-text radiology reports, a rule-based query algorithm was developed after analyzing hundreds of radiology reports that indicated communication of critical or significant results to a healthcare provider. This algorithm consisted of words and phrases used by radiologists to indicate such communications combined with specific handcrafted rules. This algorithm was iteratively refined and retested on hundreds of reports until the precision and recall did not significantly change between iterations. The algorithm was then validated on the entire database of 2.3 million reports, excluding those reports used during the testing and refinement process. Human review was used as the reference standard. The accuracy of this algorithm was determined using precision, recall, and F measure. Confidence intervals were calculated using the adjusted Wald method. The developed algorithm for detecting critical result communication has a precision of 97.0% (95% CI, 93.5–98.8%), recall 98.2% (95% CI, 93.4–100%), and F measure of 97.6% (ß = 1). Our query algorithm is accurate for identifying radiology reports that contain non-routine communication of critical or significant results. This algorithm can be applied to a radiology reports database for quality control purposes and help satisfy accreditation requirements.
机译：这项研究的目的是开发一种自动方法，以准确检测表明关键或重要结果非常规交流的放射学报告。这样的分类系统对于性能监控和认证将是有价值的。使用包含230万个自由文本放射学报告的数据库，在分析了数百个放射学报告后，开发了基于规则的查询算法，这些报告表明已将关键或重要结果传达给医疗保健提供者。该算法由放射科医生用来指示此类通信的单词和短语以及特定的手工规则组成。对该算法进行了迭代完善，并在数百份报告上进行了重新测试，直到两次迭代之间的精度和召回率均没有显着变化。然后，在230万份报告的整个数据库中对该算法进行了验证，其中不包括在测试和优化过程中使用的那些报告。人工审查被用作参考标准。使用精度，查全率和F度量确定该算法的准确性。使用调整的Wald方法计算置信区间。开发的用于检测关键结果沟通的算法的精度为97.0％（95％CI，93.5–98.8％），召回率为98.2％（95％CI，93.4–100％），F值为97.6％（ß= 1） 。我们的查询算法可准确识别包含关键或重要结果的非常规通信的放射报告。该算法可以应用于放射线报告数据库，以进行质量控制，并有助于满足认证要求。

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