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Linking Data From the Australian Stroke Clinical Registry With Ambulance and Emergency Administrative Data in Victoria

Objective: In Australia, approximately 3 in 4 people with acute stroke use an ambulance. Few examples of merging ambulance clinical records, hospital government data, and national registry data for stroke exist. We sought to understand the advantages of using linked datasets for describing the full...

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Autores principales: Eliakundu, Amminadab L., Smith, Karen, Kilkenny, Monique F., Kim, Joosup, Bagot, Kathleen L., Andrew, Emily, Cox, Shelley, Bladin, Christopher F., Cadilhac, Dominique A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9127850/
https://www.ncbi.nlm.nih.gov/pubmed/35593081
http://dx.doi.org/10.1177/00469580221102200
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author Eliakundu, Amminadab L.
Smith, Karen
Kilkenny, Monique F.
Kim, Joosup
Bagot, Kathleen L.
Andrew, Emily
Cox, Shelley
Bladin, Christopher F.
Cadilhac, Dominique A.
author_facet Eliakundu, Amminadab L.
Smith, Karen
Kilkenny, Monique F.
Kim, Joosup
Bagot, Kathleen L.
Andrew, Emily
Cox, Shelley
Bladin, Christopher F.
Cadilhac, Dominique A.
author_sort Eliakundu, Amminadab L.
collection PubMed
description Objective: In Australia, approximately 3 in 4 people with acute stroke use an ambulance. Few examples of merging ambulance clinical records, hospital government data, and national registry data for stroke exist. We sought to understand the advantages of using linked datasets for describing the full clinical journey of people with stroke and the possibility of investigating their long-term outcomes based on pre-hospital management of stroke. Method: Patient-level data from the Australian Stroke Clinical Registry (AuSCR) (January 2013-October 2017) were linked with Ambulance Victoria (AV) records and Victorian Emergency Minimum Dataset (VEMD). Probabilistic iterative matching on personal identifiers were used and records merged with a project specific identification number. Results: Of the 7,373 episodes in the AuSCR and 6,001 in the AV dataset; 4,569 (62%) were matched. Unmatched records that were positive for “arrival by ambulance” in the AuSCR and VEMD (no corresponding record in AV) were submitted to AV. AV were able to identify 148/435 additional records related to these episodes. The final cohort included 4,717 records (median age: 73 years, female 42%, ischemic stroke 66%). Conclusion: The results of the data linkage provides greater confidence for use of these data for future research related to pre-hospital management of stroke.
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spelling pubmed-91278502022-05-25 Linking Data From the Australian Stroke Clinical Registry With Ambulance and Emergency Administrative Data in Victoria Eliakundu, Amminadab L. Smith, Karen Kilkenny, Monique F. Kim, Joosup Bagot, Kathleen L. Andrew, Emily Cox, Shelley Bladin, Christopher F. Cadilhac, Dominique A. Inquiry Brief-Report Objective: In Australia, approximately 3 in 4 people with acute stroke use an ambulance. Few examples of merging ambulance clinical records, hospital government data, and national registry data for stroke exist. We sought to understand the advantages of using linked datasets for describing the full clinical journey of people with stroke and the possibility of investigating their long-term outcomes based on pre-hospital management of stroke. Method: Patient-level data from the Australian Stroke Clinical Registry (AuSCR) (January 2013-October 2017) were linked with Ambulance Victoria (AV) records and Victorian Emergency Minimum Dataset (VEMD). Probabilistic iterative matching on personal identifiers were used and records merged with a project specific identification number. Results: Of the 7,373 episodes in the AuSCR and 6,001 in the AV dataset; 4,569 (62%) were matched. Unmatched records that were positive for “arrival by ambulance” in the AuSCR and VEMD (no corresponding record in AV) were submitted to AV. AV were able to identify 148/435 additional records related to these episodes. The final cohort included 4,717 records (median age: 73 years, female 42%, ischemic stroke 66%). Conclusion: The results of the data linkage provides greater confidence for use of these data for future research related to pre-hospital management of stroke. SAGE Publications 2022-05-20 /pmc/articles/PMC9127850/ /pubmed/35593081 http://dx.doi.org/10.1177/00469580221102200 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Brief-Report
Eliakundu, Amminadab L.
Smith, Karen
Kilkenny, Monique F.
Kim, Joosup
Bagot, Kathleen L.
Andrew, Emily
Cox, Shelley
Bladin, Christopher F.
Cadilhac, Dominique A.
Linking Data From the Australian Stroke Clinical Registry With Ambulance and Emergency Administrative Data in Victoria
title Linking Data From the Australian Stroke Clinical Registry With Ambulance and Emergency Administrative Data in Victoria
title_full Linking Data From the Australian Stroke Clinical Registry With Ambulance and Emergency Administrative Data in Victoria
title_fullStr Linking Data From the Australian Stroke Clinical Registry With Ambulance and Emergency Administrative Data in Victoria
title_full_unstemmed Linking Data From the Australian Stroke Clinical Registry With Ambulance and Emergency Administrative Data in Victoria
title_short Linking Data From the Australian Stroke Clinical Registry With Ambulance and Emergency Administrative Data in Victoria
title_sort linking data from the australian stroke clinical registry with ambulance and emergency administrative data in victoria
topic Brief-Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9127850/
https://www.ncbi.nlm.nih.gov/pubmed/35593081
http://dx.doi.org/10.1177/00469580221102200
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