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在台湾建立一个积极的医疗产品安全监测系统:将美国 Sentinel 系统通用数据模型结构改编到台湾的全民健康保险研究数据库。

Building an active medical product safety surveillance system in Taiwan: Adaptation of the U.S. Sentinel System common data model structure to the National Health Insurance Research Database in Taiwan.

机构信息

School of Pharmacy, College of Medicine, National Taiwan University, Taipei, Taiwan.

Graduate Institute of Clinical Pharmacy, College of Medicine, National Taiwan University, Taipei, Taiwan.

出版信息

Pharmacoepidemiol Drug Saf. 2021 Jan;30(1):97-101. doi: 10.1002/pds.5168. Epub 2020 Nov 11.

Abstract

PURPOSE

Using real-world data to support regulatory decision has become a global movement. However, a robust platform for active surveillance of medical product safety has not been established in Taiwan.

METHODS

Following the common data model structure of the U.S. Food and Drug Administration's Sentinel System, we built the Taiwan Sentinel Data Model (TSDM) using the National Health Insurance Research Database with longitudinal claims data from 23 million individuals, linked death and cause of death data from a national registry, and linked electronic health record data from a delivery system. We examined the conversion of the TSDM using the Sentinel Data Quality Review and Characterization Programs in a sample of sex- and age-stratified cohort of 3 million individuals.

RESULTS

The TSDM fulfilled the requirements of data quality assurance. Only about 6% of sex and 0.0007% of birth year were missing, and <0.001% of date data had illogical values.

CONCLUSIONS

The TSDM-converted database could be a valuable data resource for domestic pharmacovigilance analysis in Taiwan and cross-country evaluation.

摘要

目的

利用真实世界的数据来支持监管决策已成为全球趋势。然而,在台湾尚未建立起用于医疗产品安全主动监测的稳健平台。

方法

我们遵循美国食品和药物管理局(FDA)Sentinel 系统的通用数据模型结构,使用纵向理赔数据来自 2300 万个人的全民健康保险研究数据库、来自国家登记处的死亡和死因数据以及来自一个交付系统的电子健康记录数据,构建了台湾哨兵数据模型(TSDM)。我们在 300 万个人的按性别和年龄分层的样本中,使用 Sentinel 数据质量审查和特征描述程序来检查 TSDM 的转换情况。

结果

TSDM 满足数据质量保证的要求。仅约 6%的性别和 0.0007%的出生年份存在缺失,<0.001%的日期数据具有不合理的值。

结论

转换后的 TSDM 数据库可成为台湾国内药物警戒分析和跨国评估的有价值的数据资源。

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