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Linkage of Australian national registry data using a statistical linkage key

BACKGROUND: Data from clinical registries may be linked to gain additional insights into disease processes, risk factors and outcomes. Identifying information varies from full names, addresses and unique identification codes to statistical linkage keys to no direct identifying information at all. A...

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Autores principales: Coulson, Tim G., Bailey, Michael, Reid, Chris, Shardey, Gil, Williams-Spence, Jenni, Huckson, Sue, Chavan, Shaila, Pilcher, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7856707/
https://www.ncbi.nlm.nih.gov/pubmed/33531002
http://dx.doi.org/10.1186/s12911-021-01393-1
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author Coulson, Tim G.
Bailey, Michael
Reid, Chris
Shardey, Gil
Williams-Spence, Jenni
Huckson, Sue
Chavan, Shaila
Pilcher, David
author_facet Coulson, Tim G.
Bailey, Michael
Reid, Chris
Shardey, Gil
Williams-Spence, Jenni
Huckson, Sue
Chavan, Shaila
Pilcher, David
author_sort Coulson, Tim G.
collection PubMed
description BACKGROUND: Data from clinical registries may be linked to gain additional insights into disease processes, risk factors and outcomes. Identifying information varies from full names, addresses and unique identification codes to statistical linkage keys to no direct identifying information at all. A number of databases in Australia contain the statistical linkage key 581 (SLK-581). Our aim was to investigate the ability to link data using SLK-581 between two national databases, and to compare this linkage to that achieved with direct identifiers or other non-identifying variables. METHODS: The Australian and New Zealand Society of Cardiothoracic Surgeons database (ANZSCTS-CSD) contains fully identified data. The Australian and New Zealand Intensive Care Society database (ANZICS-APD) contains non-identified data together with SLK-581. Identifying data is removed at participating hospitals prior to central collation and storage. We used the local hospital ANZICS-APD data at a large single tertiary centre prior to deidentification and linked this to ANZSCTS-CSD data. We compared linkage using SLK-581 to linkage using non-identifying variables (dates of admission and discharge, age and sex) and linkage using a complete set of unique identifiers. We compared the rate of match, rate of mismatch and clinical characteristics between unmatched patients using the different methods. RESULTS: There were 1283 patients eligible for matching in the ANZSCTS-CSD. 1242 were matched using unique identifiers. Using non-identifying variables 1151/1242 (92.6%) patients were matched. Using SLK-581, 1202/1242 (96.7%) patients were matched. The addition of non-identifying data to SLK-581 provided few additional patients (1211/1242, 97.5%). Patients who did not match were younger, had a higher mortality risk and more non-standard procedures vs matched patients. The differences between unmatched patients using different matching strategies were small. CONCLUSION: All strategies provided an acceptable linkage. SLK-581 improved the linkage compared to non-identifying variables, but was not as successful as direct identifiers. SLK-581 may be used to improve linkage between national registries where identifying information is not available or cannot be released.
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spelling pubmed-78567072021-02-04 Linkage of Australian national registry data using a statistical linkage key Coulson, Tim G. Bailey, Michael Reid, Chris Shardey, Gil Williams-Spence, Jenni Huckson, Sue Chavan, Shaila Pilcher, David BMC Med Inform Decis Mak Research Article BACKGROUND: Data from clinical registries may be linked to gain additional insights into disease processes, risk factors and outcomes. Identifying information varies from full names, addresses and unique identification codes to statistical linkage keys to no direct identifying information at all. A number of databases in Australia contain the statistical linkage key 581 (SLK-581). Our aim was to investigate the ability to link data using SLK-581 between two national databases, and to compare this linkage to that achieved with direct identifiers or other non-identifying variables. METHODS: The Australian and New Zealand Society of Cardiothoracic Surgeons database (ANZSCTS-CSD) contains fully identified data. The Australian and New Zealand Intensive Care Society database (ANZICS-APD) contains non-identified data together with SLK-581. Identifying data is removed at participating hospitals prior to central collation and storage. We used the local hospital ANZICS-APD data at a large single tertiary centre prior to deidentification and linked this to ANZSCTS-CSD data. We compared linkage using SLK-581 to linkage using non-identifying variables (dates of admission and discharge, age and sex) and linkage using a complete set of unique identifiers. We compared the rate of match, rate of mismatch and clinical characteristics between unmatched patients using the different methods. RESULTS: There were 1283 patients eligible for matching in the ANZSCTS-CSD. 1242 were matched using unique identifiers. Using non-identifying variables 1151/1242 (92.6%) patients were matched. Using SLK-581, 1202/1242 (96.7%) patients were matched. The addition of non-identifying data to SLK-581 provided few additional patients (1211/1242, 97.5%). Patients who did not match were younger, had a higher mortality risk and more non-standard procedures vs matched patients. The differences between unmatched patients using different matching strategies were small. CONCLUSION: All strategies provided an acceptable linkage. SLK-581 improved the linkage compared to non-identifying variables, but was not as successful as direct identifiers. SLK-581 may be used to improve linkage between national registries where identifying information is not available or cannot be released. BioMed Central 2021-02-02 /pmc/articles/PMC7856707/ /pubmed/33531002 http://dx.doi.org/10.1186/s12911-021-01393-1 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Coulson, Tim G.
Bailey, Michael
Reid, Chris
Shardey, Gil
Williams-Spence, Jenni
Huckson, Sue
Chavan, Shaila
Pilcher, David
Linkage of Australian national registry data using a statistical linkage key
title Linkage of Australian national registry data using a statistical linkage key
title_full Linkage of Australian national registry data using a statistical linkage key
title_fullStr Linkage of Australian national registry data using a statistical linkage key
title_full_unstemmed Linkage of Australian national registry data using a statistical linkage key
title_short Linkage of Australian national registry data using a statistical linkage key
title_sort linkage of australian national registry data using a statistical linkage key
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7856707/
https://www.ncbi.nlm.nih.gov/pubmed/33531002
http://dx.doi.org/10.1186/s12911-021-01393-1
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