Evaluation of record linkage of two large administrative databases in a middle income country: stillbirths and notifications of dengue during pregnancy in Brazil
Evaluation of record linkage of two large administrative databases in a middle income country: stillbirths and notifications of dengue during pregnancy in Brazil
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DOI：
10.1186/s12911-017-0506-5
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发表时间：
2017-07-17
影响因子：
3.5
通讯作者：
Rodrigues, Laura C.
中科院分区：
文献类型：
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作者：
Paixao, Enny S.;Harron, Katie;Rodrigues, Laura C.
背景资料：由于不同电子数据集的个人信息越来越多，记录链接已成为一种有效和重要的研究工具。高质量的链接对于产生稳健的结果至关重要。本研究的目的是描述准备和连接巴西国家数据集的过程，并比较不同的链接方法的准确性，评估死产的风险，由于登革热在pregnancy.Methods：我们链接的母亲和死产在两个常规收集的数据集从巴西2009-2010年：登革热在怀孕期间，传染病的通知（希南）;死产死亡率（SIM）。由于没有唯一的标识符，我们使用基于母亲姓名，年龄和自治市的概率连锁。我们比较了两种概率方法，每种方法都有两个阈值：1）定制的连锁算法; 2）在巴西广泛使用的标准连锁软件（ReclinkIII），并使用人工审查来识别进一步的链接。敏感性和阳性预测值（PPV）是使用通过人工审查创建的金标准数据子集进行估计的。我们检查了假匹配和错配的特征，以确定任何偏差的来源。结果：从678,999例登革热病例和62,373例死胎的记录中，金标准连锁确定了191例病例。具有保守阈值的定制链接算法产生131个链接，灵敏度= 64.4%（68个错配）和PPV = 92.5%（8个假匹配）。人工审查不确定的链接确定了额外的37个链接，敏感性增加到83.7%。具有宽松阈值的定制算法识别了132个真实匹配（灵敏度= 69.1%），但引入了61个假匹配（PPV = 68.4%）。ReclinkIII产生的灵敏度和PPV低于定制的连接算法。连锁错误与任何记录的study variables.Conclusion：尽管缺乏独特的标识符连接母亲和死产，我们表现出高标准的连接从中等收入国家的大型常规数据库。概率联系和人工审查对于准确识别病例对照研究的病例至关重要，但这种方法对于较大的数据库或更常见结果的联系可能不可行。
Background: Due to the increasing availability of individual-level information across different electronic datasets, record linkage has become an efficient and important research tool. High quality linkage is essential for producing robust results. The objective of this study was to describe the process of preparing and linking national Brazilian datasets, and to compare the accuracy of different linkage methods for assessing the risk of stillbirth due to dengue in pregnancy.Methods: We linked mothers and stillbirths in two routinely collected datasets from Brazil for 2009-2010: for dengue in pregnancy, notifications of infectious diseases (SINAN); for stillbirths, mortality (SIM). Since there was no unique identifier, we used probabilistic linkage based on maternal name, age and municipality. We compared two probabilistic approaches, each with two thresholds: 1) a bespoke linkage algorithm; 2) a standard linkage software widely used in Brazil (ReclinkIII), and used manual review to identify further links. Sensitivity and positive predictive value (PPV) were estimated using a subset of gold-standard data created through manual review. We examined the characteristics of false-matches and missed-matches to identify any sources of bias.Results: From records of 678,999 dengue cases and 62,373 stillbirths, the gold-standard linkage identified 191 cases. The bespoke linkage algorithm with a conservative threshold produced 131 links, with sensitivity = 64.4% (68 missed-matches) and PPV = 92.5% (8 false-matches). Manual review of uncertain links identified an additional 37 links, increasing sensitivity to 83.7%. The bespoke algorithm with a relaxed threshold identified 132 true matches (sensitivity = 69.1%), but introduced 61 false-matches (PPV = 68.4%). ReclinkIII produced lower sensitivity and PPV than the bespoke linkage algorithm. Linkage error was not associated with any recorded study variables.Conclusion: Despite a lack of unique identifiers for linking mothers and stillbirths, we demonstrate a high standard of linkage of large routine databases from a middle income country. Probabilistic linkage and manual review were essential for accurately identifying cases for a case-control study, but this approach may not be feasible for larger databases or for linkage of more common outcomes.