Validating linkage of multiple population-based administrative databases in Brazil

BACKGROUND: Linking routinely-collected data provides an opportunity to measure the effects of exposures that occur before birth on maternal, fetal and infant outcomes. High quality linkage is a prerequisite for producing reliable results, and there are specific challenges in mother-baby linkage. Using population-based administrative databases from Brazil, this study aimed to estimate the accuracy of linkage between maternal deaths and birth outcomes and dengue notifications, and to identify potential sources of bias when assessing the risk of maternal death due to dengue in pregnancy. METHODS: We identified women with dengue during pregnancy in a previously linked dataset of dengue notifications in women who had experienced a live birth or stillbirth during 2007-2012. We then linked this dataset with maternal death records probabilistically using maternal name, age and municipality. We estimated the accuracy of the linkage, and examined the characteristics of false-matches and missed-matches to identify any sources of bias. RESULTS: Of the 10,259 maternal deaths recorded in 2007-2012, 6717 were linked: 5444 to a live birth record, 1306 to a stillbirth record, and 33 to both a live and stillbirth record. After identifying 2620 missed-matches and 124 false-matches, our estimated sensitivity was 72%, specificity was 88%, and positive predictive value was 98%. Linkage errors were associated with maternal education and self-identified race; women with more than 7 years of education or who self-declared as Caucasian were more likely to link. Dengue status was not associated with linkage error. CONCLUSION: Despite not having unique identifiers to link mothers and birth outcomes, we demonstrated a high standard of linkage, with sensitivity and specificity values comparable to previous literature. Although there were no differences in the characteristics of dengue cases missed or included in our linked dataset, linkage error occurred disproportionally by some social-demographic characteristics, which should be taken into account in future analyses

Evaluation of record linkage of two large administrative databases in a middle income country: stillbirths and notifications of dengue during pregnancy in Brazil

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