基于数据驱动的治疗负担测量方法：一项乳腺癌患者研究
Data Driven Approach to Burden of Treatment Measurement: A Study of Patients with Breast Cancer.
作者信息
Cheng Alex C, Levy Mia A
机构信息
Vanderbilt University, Nashville, TN.
出版信息
AMIA Annu Symp Proc. 2017 Feb 10;2016:1756-1763. eCollection 2016.
Abstract
Chronic disease affects patient quality of life through symptoms of the disease and the work of receiving treatment. While the effects of illness are well investigated, the burden of treatment is not commonly studied or monitored. We developed a method to quantify one dimension of the burden of treatment based on patient encounters with the healthcare system. We applied this method to a population of stage I-III breast cancer patients. As hypothesized and observed, stage IIIpatients had more appointments, spent more time in clinic, and spent more time admitted to the hospital in the first 18 months after diagnosis compared to stage I and II patients. Future work will evaluate the reproducibility and generalizability of this method for quantifying burden of treatment across other clinical settings and chronic diseases. This approach could enable identification of high-risk groups that could benefit from interventions to decrease patient work and improve outcomes.
摘要
慢性病通过疾病症状和接受治疗的过程影响患者的生活质量。虽然疾病的影响已得到充分研究，但治疗负担却鲜少被研究或监测。我们开发了一种基于患者与医疗系统接触情况来量化治疗负担一个维度的方法。我们将此方法应用于I - III期乳腺癌患者群体。正如假设和观察到的那样，与I期和II期患者相比，III期患者在诊断后的前18个月有更多的预约、在诊所花费更多时间以及住院时间更长。未来的工作将评估该方法在其他临床环境和慢性病中量化治疗负担的可重复性和普遍性。这种方法能够识别出可能从减少患者负担并改善治疗效果的干预措施中受益的高危群体。
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