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Evaluating the risk of patient re-identification from adverse drug event reports

机译:从不良药物事件报告中评估患者重新识别的风险

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摘要

Abstract Background Our objective was to develop a model for measuring re-identification risk that more closely mimics the behaviour of an adversary by accounting for repeated attempts at matching and verification of matches, and apply it to evaluate the risk of re-identification for Canada’s post-marketing adverse drug event database (ADE).Re-identification is only demonstrably plausible for deaths in ADE. A matching experiment between ADE records and virtual obituaries constructed from Statistics Canada vital statistics was simulated. A new re-identification risk is considered, it assumes that after gathering all the potential matches for a patient record (all records in the obituaries that are potential matches for an ADE record), an adversary tries to verify these potential matches. Two adversary scenarios were considered: (a) a mildly motivated adversary who will stop after one verification attempt, and (b) a highly motivated adversary who will attempt to verify all the potential matches and is only limited by practical or financial considerations. Methods The mean percentage of records in ADE that had a high probability of being re-identified was computed. Results Under scenario (a), the risk of re-identification from disclosing the province, age at death, gender, and exact date of the report is quite high, but the removal of province brings down the risk significantly. By only generalizing the date of reporting to month and year and including all other variables, the risk is always low. All ADE records have a high risk of re-identification under scenario (b), but the plausibility of that scenario is limited because of the financial and practical deterrent even for highly motivated adversaries. Conclusions It is possible to disclose Canada’s adverse drug event database while ensuring that plausible re-identification risks are acceptably low. Our new re-identification risk model is suitable for such risk assessments.
机译:摘要背景我们的目的是通过考虑重复尝试匹配和验证匹配的行为,开发一种更准确地模拟对手行为的衡量重新识别风险的模型,并将其应用于评估加拿大职位的重新识别风险-销售不良药品事件数据库(ADE)。只有在ADE中死亡才可以重新识别。模拟了ADE记录和根据加拿大统计局生命统计数据构建的虚拟ob告之间的匹配实验。考虑了一种新的重新识别风险,它假设在收集了患者记录的所有潜在匹配项(the告中所有与ADE记录潜在匹配的记录)之后,对手试图验证这些潜在匹配项。考虑了两个对手方案:(a)一个动机较弱的对手,将在一次验证尝试后停止;以及(b)一个动机极高的对手,将尝试验证所有可能的匹配,并且仅受实际或财务考虑。方法计算ADE中被重新识别的可能性很高的记录的平均百分比。结果在方案(a)下,披露省份,死亡年龄,性别和报告的确切日期所带来的重新识别风险很高,但是撤除省份则大大降低了风险。通过仅将报告日期概括为月份和年份,并包括所有其他变量,风险总是很低的。在情况(b)下,所有ADE记录都具有重新识别的高风险,但是该情况的合理性受到限制,因为即使对于积极进取的对手也有财务和实际的威慑作用。结论可以披露加拿大的不良药物事件数据库,同时确保合理的重新识别风险较低。我们新的重新识别风险模型适用于此类风险评估。

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