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主动医疗器械产品安全监测系统的设计考虑因素。

Design considerations in an active medical product safety monitoring system.

机构信息

Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02120, USA.

出版信息

Pharmacoepidemiol Drug Saf. 2012 Jan;21 Suppl 1:32-40. doi: 10.1002/pds.2316.

Abstract

Active medical product monitoring systems, such as the Sentinel System, will utilize electronic healthcare data captured during routine health care. Safety signals that arise from these data may be spurious because of chance or bias, particularly confounding bias, given the observational nature of the data. Applying appropriate monitoring designs can filter out many false-positive and false-negative associations from the outset. Designs can be classified by whether they produce estimates based on between-person or within-person comparisons. In deciding which approach is more suitable for a given monitoring scenario, stakeholders must consider the characteristics of the monitored product, characteristics of the health outcome of interest (HOI), and characteristics of the potential link between these. Specifically, three factors drive design decisions: (i) strength of within-person and between-person confounding; (ii) whether circumstances exist that may predispose to misclassification of exposure or misclassification of the timing of the HOI; and (iii) whether the exposure of interest is predominantly transient or sustained. Additional design considerations include whether to focus on new users, the availability of appropriate active comparators, the presence of an exposure time trend, and the measure of association of interest. When the key assumptions of self-controlled designs are fulfilled (i.e., lack of within-person, time-varying confounding; abrupt HOI onset; and transient exposure), within-person comparisons are preferred because they inherently avoid confounding by fixed factors. The cohort approach generally is preferred in other situations and particularly when timing of exposure or outcome is uncertain because cohort approaches are less vulnerable to biases resulting from misclassification.

摘要

主动式医疗产品监测系统,如 Sentinel 系统,将利用在常规医疗保健过程中捕获的电子医疗数据。由于数据的观察性质,这些数据中出现的安全信号可能是虚假的,因为这是偶然的或存在偏倚,特别是混杂偏倚。应用适当的监测设计可以从一开始就过滤掉许多假阳性和假阴性关联。设计可以根据它们基于个体间还是个体内比较来进行分类。在决定哪种方法更适合给定的监测情况时,利益相关者必须考虑被监测产品的特征、感兴趣的健康结果(HOI)的特征以及它们之间潜在联系的特征。具体而言,有三个因素推动设计决策:(i)个体内和个体间混杂的强度;(ii)是否存在可能导致暴露或 HOI 时间分类错误的情况;以及(iii)感兴趣的暴露是否主要是短暂的还是持续的。其他设计考虑因素包括是否专注于新用户、是否有适当的活性对照剂、是否存在暴露时间趋势以及感兴趣的关联度量。当自我对照设计的关键假设得到满足(即不存在个体内、随时间变化的混杂;HOI 突然发作;以及短暂的暴露)时,个体内比较是首选,因为它们固有地避免了固定因素引起的混杂。在其他情况下,特别是当暴露或结果的时间不确定时,通常会优先选择队列方法,因为队列方法不太容易受到由于分类错误而导致的偏倚的影响。

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