Holbrook Anne, Grootendorst Paul, Willison Don, Goldsmith Charles, Sebaldt Rolf, Keshavjee Karim
Faculty of Pharmaceutical Sciences, University of Toronto.
AMIA Annu Symp Proc. 2005;2005:335-9.
Every health policy jurisdiction is endeavoring to enhance its ability to evaluate drug effectiveness, safety and cost in the real world (pharmacosurveillance).
A nominal group consensus conference of stakeholders finalized data items deemed necessary for pharmacosurveillance. Large administrative datasets (LADs), electronic health records (EHRs) and electronic patient registries (PRs), were investigated as sources of this information and for their vulnerability to methodologic bias. Health data privacy legislation and research guidelines were systematically reviewed for their constraint to linked data resource analyses.
More than 129 data items were strongly recommended for routine pharmacosurveillance. LADs had very complete information, but restricted to a small number of required data items. EHRs, especially with e-pharmacy links, offer by far the most complete set of health information domains but data entry completeness is highly variable. Adjustment methods for channeling bias are inadequate to mimic randomized trials. Anonymized, linked data held within a secure academic research environment, poses the least privacy concerns.
Notwithstanding major technical, methodologic and privacy challenges, individual-level linkage of health data resources poses the best option for pharmacosurveillance today. In future, drug regulators and reimbursement agencies should consider mandatory post-marketing randomized trials.
每个卫生政策辖区都在努力提高其在现实世界中评估药物有效性、安全性和成本的能力（药物监测）。
利益相关者名义群体共识会议最终确定了药物监测所需的数据项目。对大型行政数据集（LADs）、电子健康记录（EHRs）和电子患者登记册（PRs）作为该信息来源及其对方法学偏差的易感性进行了调查。系统审查了健康数据隐私立法和研究指南对关联数据资源分析的限制。
强烈建议超过129个数据项目用于常规药物监测。LADs拥有非常完整的信息，但仅限于少数所需数据项目。EHRs，尤其是与电子药房链接的EHRs，提供了迄今为止最完整的健康信息领域集，但数据录入完整性差异很大。用于疏导偏差的调整方法不足以模拟随机试验。在安全的学术研究环境中保存的匿名关联数据引发的隐私担忧最少。
尽管存在重大的技术、方法学和隐私挑战，但健康数据资源的个体层面关联是当今药物监测的最佳选择。未来，药物监管机构和报销机构应考虑强制进行上市后随机试验。
