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Retrieving the Vital Status of Patients with Cancer Using Online Obituaries

机译:使用在线ob告检测癌症患者的重要地位

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The aim of this study was to develop a methodology to link mortality data from Internet sources with administrative data from electronic health records and to assess the performance of different record linkage methods. We extracted the electronic health records of all adult patients hospitalized at Rennes comprehensive cancer center between January 1, 2010 and December 31, 2015 and separated them in two groups (training and test set). We also extracted all available online obituaries from the most exhaustive French funeral home website using web scraping techniques. We used and evaluated three different algorithms (deterministic, approximate deterministic and probabilistic) to link the patients' records with online obituaries. We optimized the algorithms using the training set and then evaluated them in the test set. The overall precision was between 98 and 100%. The three classification algorithms performed better for men than women. The probabilistic classification decreased the number of manual reviews, but slightly increased the number of false negatives. To address the problem of long delays in the publication or sharing of mortality data, online obituary data could be considered for real-time surveillance of mortality in patients with cancer because they are easily available and time-efficient.
机译:本研究的目的是制定一种方法,以将来自互联网来源的死亡数据与来自电子健康记录的行政数据联系起来,并评估不同记录联动方法的性能。我们在2010年1月1日至2015年12月31日之间提取了在雷恩综合癌症中心住院的所有成年患者的电子健康记录,并分为两组(培训和测试集)。我们还使用Web缩写技术从最令人遗憾的法国殡仪馆网站上提取所有可用的在线obituaries。我们使用并评估了三种不同的算法(确定性,近似确定性和概率),以将患者的记录与在线obitairs联系起来。我们使用训练集优化了算法,然后在测试集中进行评估。整体精度在98到100%之间。对于男性而言,三种分类算法比女性更好。概率分类减少了手动评论的数量,但略微增加了假底片的数量。为了解决发表的延迟延迟或分享死亡率数据的问题,可以考虑在线ob告数据,以便实时监测癌症患者的死亡率,因为它们很容易获得和延时的。

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