评估药物对医院化验结果的影响。

Q2 Computer Science
Victorine P Muse, Amalie D Haue, Cristina L Rodríguez, Alejandro A Orozco, Jorge H Biel, Søren Brunak
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引用次数: 0

摘要

多药治疗方案中出现药物不良事件(ADE)的患者对现代医疗保健提出了巨大挑战。虽然计算的努力可能会减少这些不良事件的发生率,但目前的策略通常不能推广到标准的医疗保健系统。为了解决这个问题,我们进行了一项回顾性研究,旨在开发一种统计方法来检测和量化潜在的ade。该数据基础包括2011年至2016年期间来自丹麦两个卫生区域的近200万患者及其药物和实验室数据。我们开发了一系列多状态Cox模型来计算药物暴露前后实验室测试结果变化的风险比。通过将结果与药物-药物相互作用数据库的数据联系起来,我们发现这些模型显示了医疗安全机构应用的潜力,并提高了药物审批流程的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessment of Drug Impact on Laboratory Test Results in Hospital Settings.

Patients experiencing adverse drug events (ADE) from polypharmaceutical regimens present a huge challenge to modern healthcare. While computational efforts may reduce the incidence of these ADEs, current strategies are typically non-generalizable for standard healthcare systems. To address this, we carried out a retrospective study aimed at developing a statistical approach to detect and quantify potential ADEs. The data foundation comprised of almost 2 million patients from two health regions in Denmark and their drug and laboratory data during the years 2011 to 2016. We developed a series of multistate Cox models to compute hazard ratios for changes in laboratory test results before and after drug exposure. By linking the results to data from a drug-drug interaction database, we found that the models showed potential for applications for medical safety agencies and improved efficiency for drug approval pipelines.

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