Linkage of Australian national registry data using a statistical linkage key
Abstract 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...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2021-02-01
|
| Series: | BMC Medical Informatics and Decision Making |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12911-021-01393-1 |
| _version_ | 1829532413797072896 |
|---|---|
| author | Tim G. Coulson Michael Bailey Chris Reid Gil Shardey Jenni Williams-Spence Sue Huckson Shaila Chavan David Pilcher |
| author_facet | Tim G. Coulson Michael Bailey Chris Reid Gil Shardey Jenni Williams-Spence Sue Huckson Shaila Chavan David Pilcher |
| author_sort | Tim G. Coulson |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-12-16T18:38:47Z |
| format | Article |
| id | doaj.art-33b02b8ba5314a329570a4dee4273e98 |
| institution | Directory Open Access Journal |
| issn | 1472-6947 |
| language | English |
| last_indexed | 2024-12-16T18:38:47Z |
| publishDate | 2021-02-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Informatics and Decision Making |
| spelling | doaj.art-33b02b8ba5314a329570a4dee4273e982022-12-21T22:21:07ZengBMCBMC Medical Informatics and Decision Making1472-69472021-02-012111910.1186/s12911-021-01393-1Linkage of Australian national registry data using a statistical linkage keyTim G. Coulson0Michael Bailey1Chris Reid2Gil Shardey3Jenni Williams-Spence4Sue Huckson5Shaila Chavan6David Pilcher7Department of Epidemiology and Preventive Medicine, Monash UniversityDepartment of Epidemiology and Preventive Medicine, Monash UniversityDepartment of Epidemiology and Preventive Medicine, Monash UniversityDepartment of Epidemiology and Preventive Medicine, Monash UniversityDepartment of Epidemiology and Preventive Medicine, Monash UniversityThe Australian and New Zealand Intensive Care Society (ANZICS) Centre for Outcome and Resource Evaluation (CORE)The Australian and New Zealand Intensive Care Society (ANZICS) Centre for Outcome and Resource Evaluation (CORE)Department of Epidemiology and Preventive Medicine, Monash UniversityAbstract 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.https://doi.org/10.1186/s12911-021-01393-1LinkageSLK-581Registry |
| spellingShingle | Tim G. Coulson Michael Bailey Chris Reid Gil Shardey Jenni Williams-Spence Sue Huckson Shaila Chavan David Pilcher Linkage of Australian national registry data using a statistical linkage key BMC Medical Informatics and Decision Making Linkage SLK-581 Registry |
| 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 | Linkage SLK-581 Registry |
| url | https://doi.org/10.1186/s12911-021-01393-1 |
| work_keys_str_mv | AT timgcoulson linkageofaustraliannationalregistrydatausingastatisticallinkagekey AT michaelbailey linkageofaustraliannationalregistrydatausingastatisticallinkagekey AT chrisreid linkageofaustraliannationalregistrydatausingastatisticallinkagekey AT gilshardey linkageofaustraliannationalregistrydatausingastatisticallinkagekey AT jenniwilliamsspence linkageofaustraliannationalregistrydatausingastatisticallinkagekey AT suehuckson linkageofaustraliannationalregistrydatausingastatisticallinkagekey AT shailachavan linkageofaustraliannationalregistrydatausingastatisticallinkagekey AT davidpilcher linkageofaustraliannationalregistrydatausingastatisticallinkagekey |