Challenges in administrative data linkage for research

dc.creatorHarron, Katie
dc.creatorDibben, Chris
dc.creatorBoyd, James
dc.creatorHjern, Anders
dc.creatorAzimaee, Mahmoud
dc.creatorBarreto, Maurício Lima
dc.creatorGoldstein, Harvey
dc.date2018-05-25T14:19:11Z
dc.date2018-05-25T14:19:11Z
dc.date2017
dc.date.accessioned2023-09-26T23:47:48Z
dc.date.available2023-09-26T23:47:48Z
dc.identifierHARRON, Katie et al. Challenges in administrative data linkage for research. Big Data & Society, p. 1–12, 2017.
dc.identifier2053-9517
dc.identifierhttps://www.arca.fiocruz.br/handle/icict/26646
dc.identifier10.1177/2053951717745678
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8894306
dc.descriptionWellcome Trust [número de concessão 103975 / Z / 14 / Z]
dc.descriptionLinkage of population-based administrative data is a valuable tool for combining detailed individual-level information from different sources for research. While not a substitute for classical studies based on primary data collection, analyses of linked administrative data can answer questions that require large sample sizes or detailed data on hard-to-reach populations, and generate evidence with a high level of external validity and applicability for policy making. There are unique challenges in the appropriate research use of linked administrative data, for example with respect to bias from linkage errors where records cannot be linked or are linked together incorrectly. For confidentiality and other reasons, the separation of data linkage processes and analysis of linked data is generally regarded as best practice. However, the ‘black box’ of data linkage can make it difficult for researchers to judge the reliability of the resulting linked data for their required purposes. This article aims to provide an overview of challenges in linking administrative data for research. We aim to increase understanding of the implications of (i) the data linkage environment and privacy preservation; (ii) the linkage process itself (including data preparation, and deterministic and probabilistic linkage methods) and (iii) linkage quality and potential bias in linked data. We draw on examples from a number of countries to illustrate a range of approaches for data linkage in different contexts.
dc.formatapplication/pdf
dc.languageeng
dc.publisherSAGE Publications
dc.rightsopen access
dc.subjectLigação de dados
dc.subjectVinculação de registros
dc.subjectEstudos epidemiológicos
dc.subjectErro de medição
dc.subjectViés de seleção
dc.subjectDados administrativos de precisão de dados
dc.subjectData linkage
dc.subjectRecord linkage
dc.subjectEpidemiological studies
dc.subjectMeasurement error
dc.subjectSelection bias
dc.subjectData accuracy administrative data
dc.titleChallenges in administrative data linkage for research
dc.typeArticle


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