Record linkage under suboptimal conditions for data-intensive evaluation of primary care in Rio de Janeiro, Brazil

Abstract

Background Linking Brazilian databases demands the development of algorithms and processes to deal with various challenges including the large size of the databases, the low number and poor quality of personal identifiers available to be compared (national security number not mandatory), and some characteristics of Brazilian names that make the linkage process prone to errors. This study aims to describe and evaluate the quality of the processes used to create an individual-linked database for data-intensive research on the impacts on health indicators of the expansion of primary care in Rio de Janeiro City, Brazil. Methods We created an individual-level dataset linking social benefits recipients, primary health care, hospital admission and mortality data. The databases were pre-processed, and we adopted a multiple approach strategy combining deterministic and probabilistic record linkage techniques, and an extensive clerical review of the potential matches. Relying on manual review as the gold standard, we estimated the false match (false-positive) proportion of each approach (deterministic, probabilistic, clerical review) and the missed match proportion (false-negative) of the clerical review approach. To assess the sensitivity (recall) to identifying social benefits recipients’ deaths, we used their vital status registered on the primary care database as the gold standard. Results In all linkage processes, the deterministic approach identified most of the matches. However, the proportion of matches identified in each approach varied. The false match proportion was around 1% or less in almost all approaches. The missed match proportion in the clerical review approach of all linkage processes were under 3%. We estimated a recall of 93.6% (95% CI 92.8–94.3) for the linkage between social benefits recipients and mortality data. Conclusion The adoption of a linkage strategy combining pre-processing routines, deterministic, and probabilistic strategies, as well as an extensive clerical review approach minimized linkage errors in the context of suboptimal data quality.

Mortality according to gender identity and sexual orientation: Data relationship strategies for Rio de Janeiro, Brazil

“…By adopting preprocessing routines and considering the relationship time as a function of the number of true pairs detected, the recognition of the best blocking and processing strategies constitutes an advance for the systematic adoption of this method in the daily life of the services, especially when considering sexual orientation and gender identity as exposure variables in future analyses. These procedures resulted in a true-pair detection rate with proportions compatible with those found in other investigations whose outcome variable was the registration of death in SIM (21,35).…”

“…The adoption of scores ≥17.9 reduced 56.16% of the pairs to be reviewed, with 90.04% of the pairs being truly negative. In other words, with high specificity (>90.00%) and with the loss of only 25 true pairs erroneously classified as false (98.46% sensitivity), our strategy 1 demonstrated excellent properties and elements compatible with other linkage strategies with Brazilian datasets (21,35). In addition, when incorporating the deaths into the SINAN database, the degrees of agreement for the kappa indicator are high and close to 1 for all the variables of interest in this study, revealing that the adoption of a higher cutoff point (≥17.9) does not imply losses for future analyses.…”

Associations between primary healthcare and infant health outcomes: a cohort analysis of low-income mothers in Rio de Janeiro, Brazil

“…Coverage and data quality for the city of Rio de Janeiro is high (e.g., 99.7% of all births registered). 38 , 40 We identified all live births to mothers within the Cadastro Único including infants already registered in Cadastro Único and those who were not. Stillbirth records were not available for linkage.…”

“…Only infants within the Cadastro Único were linked to hospitalisation records as infant names are not recorded on birth certificates, inhibiting linkage. All datasets were linked via a combination of deterministic and probabilistic approaches (as published elsewhere 38 ) which involved matching name, date of birth and tax numbers using deterministic linkage, phonetic matching, and Levenshtein distance matching.…”

“…We also explore effects on antenatal care (ANC), birth outcomes, and infant hospitalisations to assess potential mechanisms and other important health outcomes. The city of Rio de Janeiro was chosen for this research given the city-wide expansion of the FHS programme and investments in frontline services ( Panel 1 ) during the study period, and the availability of linked data on a cohort of low-income individual covering roughly 25% of the city population 37 , 38 —a unique situation the country. Given the known benefits of PHC on infant health, we hypothesize that FHS utilisation may be associated with improved birth outcomes and infant health.…”