| Author | Harron, Katie | |
| Author | Dibben, Chris | |
| Author | Boyd, James | |
| Author | Hjern, Anders | |
| Author | Azimaee, Mahmoud | |
| Author | Barreto, Maurício Lima | |
| Author | Goldstein, Harvey | |
| Access date | 2018-05-25T14:19:11Z | |
| Available date | 2018-05-25T14:19:11Z | |
| Document date | 2017 | |
| Citation | HARRON, Katie et al. Challenges in administrative data linkage for research. Big Data & Society, p. 1–12, 2017. | pt_BR |
| ISSN | 2053-9517 | pt_BR |
| URI | https://www.arca.fiocruz.br/handle/icict/26646 | |
| Sponsorship | Wellcome Trust [número de concessão 103975 / Z / 14 / Z] | pt_BR |
| Language | eng | pt_BR |
| Publisher | SAGE Publications | pt_BR |
| Rights | open access | pt_BR |
| Subject in Portuguese | Ligação de dados | pt_BR |
| Subject in Portuguese | Vinculação de registros | pt_BR |
| Subject in Portuguese | Estudos epidemiológicos | pt_BR |
| Subject in Portuguese | Erro de medição | pt_BR |
| Subject in Portuguese | Viés de seleção | pt_BR |
| Subject in Portuguese | Dados administrativos de precisão de dados | pt_BR |
| Title | Challenges in administrative data linkage for research | pt_BR |
| Type | Article | pt_BR |
| DOI | 10.1177/2053951717745678 | pt_BR |
| Abstract | Linkage 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. | pt_BR |
| Affilliation | London School of Hygiene & Tropical Medicine. Department of Health Services Research and Policy. London, UK. | pt_BR |
| Affilliation | University of Edinburgh. Institute of Geography and the Lived nvironment. Edinburgh, UK. | pt_BR |
| Affilliation | Curtin University. Centre for Population Health Research. Perth, Australia. | pt_BR |
| Affilliation | Stockholm University. CHESS Karolinska Institutet. Stockholm, Sweden. | pt_BR |
| Affilliation | Institute for Clinical Evaluative Sciences. Toronto, Canada. | pt_BR |
| Affilliation | Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimento para a Saúde. Salvador, BA, Brasil. | pt_BR |
| Affilliation | University of Bristol. Graduate School of Education. Bristol, UK / UCL Great Ormond Street Institute of Child Health. London, UK. | pt_BR |
| Subject | Data linkage | pt_BR |
| Subject | Record linkage | pt_BR |
| Subject | Epidemiological studies | pt_BR |
| Subject | Measurement error | pt_BR |
| Subject | Selection bias | pt_BR |
| Subject | Data accuracy administrative data | pt_BR |
