Creating a Learning Health System in a Cancer Center: Generalizability of an Electronic Health Record Phenotype for Advanced Solid Cancer.

IF 4.7 3区 医学 Q1 ONCOLOGY
Anne M Walling, Karl A Lorenz, Anita Yuan, Claire E O'Hanlon, Michael McClean, Benjamin Fayyazuddin Ljungberg, Karleen F Giannitrapani, Selen Bozkurt, Sidharth Anand, John Glaspy, Neil S Wenger, Charlotta Lindvall
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Abstract

Purpose: To test the generalizability of an electronic health record (EHR) phenotype for patients with advanced solid cancer, which was previously developed in a single cancer center.

Methods: We compared an algorithm to identify patients with advanced solid cancer from a random sample of patients with active cancer in the Veterans Health Administration (VA) and an academic cancer center with a human-coded reference standard between January 1, 2016, and December 31, 2019.

Results: Compared with the human-coded reference standard, the algorithm had high specificity (93%; 95% CI, 87 to 99 and 97%; 95% CI, 93 to 100) and reasonable sensitivity (85%; 95% CI, 76 to 94 and 87%; 95% CI, 77 to 97) in the VA and academic cancer center populations, respectively. Patients with advanced cancer (compared with those with active nonadvanced cancer) had higher mortality at the VA and academic cancer center (29.2% and 17.0% 6-month mortality v 6.8% and 3.5%), respectively.

Conclusion: This EHR phenotype can be used to measure and improve the quality of palliative care for patients with advanced cancer within and across health care settings.

在癌症中心创建学习型医疗系统:晚期实体癌电子健康记录表型的推广性。
目的:测试晚期实体癌患者电子健康记录(EHR)表型的通用性:我们比较了退伍军人健康管理局(VA)和一家学术癌症中心在 2016 年 1 月 1 日至 2019 年 12 月 31 日期间从活动性癌症患者随机抽样中识别晚期实体癌患者的算法与人工编码参考标准:与人类编码参考标准相比,该算法在退伍军人健康管理局和学术癌症中心人群中分别具有较高的特异性(93%;95% CI,87 至 99 和 97%;95% CI,93 至 100)和合理的灵敏度(85%;95% CI,76 至 94 和 87%;95% CI,77 至 97)。在退伍军人事务部和学术癌症中心,晚期癌症患者(与活动性非晚期癌症患者相比)的死亡率较高(6 个月死亡率分别为 29.2% 和 17.0% 对 6.8% 和 3.5%):这种电子病历表型可用于衡量和改善医疗机构内部和医疗机构之间晚期癌症患者姑息治疗的质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.40
自引率
7.50%
发文量
518
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