Determining the Time of Cancer Recurrence Using Claims or Electronic Medical Record Data
Determining the Time of Cancer Recurrence Using Claims or Electronic Medical Record Data
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DOI：
10.1200/cci.17.00163
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发表时间：
2018-05-15
影响因子：
4.2
通讯作者：
Hassett, Michael J.
中科院分区：
文献类型：
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作者：
Uno, Hajime;Ritzwoller, Debra P.;Hassett, Michael J.
目的 索赔和电子病历 (EMR) 中的数据经常用于识别临床事件（例如癌症诊断、中风）。然而，准确确定临床事件的时间可能具有挑战性，并且用于生成时间估计的方法还不完善。我们试图开发一种方法，使用高维纵向结构化数据来确定临床事件（癌症复发）的时间。方法手动图表抽象提供了有关癌症复发的实际时间的信息。这些数据与医疗保险索赔或癌症研究网络的结构化电子病历数据相关联，这些数据用于确定肺癌或结直肠癌患者的复发时间。我们分析了可以帮助确定复发时间的代码的纵向概况，根据代码日期和复发日期之间的系统差异进行调整，并整合不同代码的时间估计，以凭经验得出最佳算法。结果我们确定了 12 个可以帮助确定复发时间的代码组。使用肺癌患者的理赔数据，最佳算法由三个代码组组成，平均预测误差为 4.8 个月。使用 EMR 数据或将此方法应用于结直肠癌患者会产生类似的结果。 结论 通过选择不一定与用于识别复发的代码相同的代码、结合多个代码组的时间估计以及调整代码日期和复发日期之间的系统偏差，可以改进时间估计。提高临床事件时间估计的准确性可以促进研究、质量测量和流程改进。 (C) 2018 年美国临床肿瘤学会
Purpose Data from claims and electronic medical records (EMRs) are frequently used to identify clinical events (eg, cancer diagnosis, stroke). However, accurately determining the time of clinical events can be challenging, and the methods used to generate time estimates are underdeveloped. We sought to develop an approach to determine the time of a clinical event-cancer recurrence-using high-dimensional longitudinal structured data.Methods Manual chart abstraction provided information regarding the actual time of cancer recurrence. These data were linked to claims from Medicare or structured EMR data from the Cancer Research Network, which were used to determine time of recurrence for patients with lung or colorectal cancer. We analyzed the longitudinal profile of codes that could help determine the time of recurrence, adjusted for systematic differences between code dates and recurrence dates, and integrated time estimates from different codes to empirically derive an optimal algorithm.Results We identified twelve code groups that could help determine the time of recurrence. Using claims data for patients with lung cancer, the optimal algorithm consisted of three code groups and provided an average prediction error of 4.8 months. Using EMR data or applying this approach to patients with colorectal cancer yielded similar results.Conclusion Time estimates were improved by selecting codes not necessarily the same as those used to identify recurrence, combining time estimates from multiple code groups, and adjusting for systematic bias between code dates and recurrence dates. Improving the accuracy of time estimates for clinical events can facilitate research, quality measurement, and process improvement. (C) 2018 by American Society of Clinical Oncology