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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Main Authors: Amminadab L. Eliakundu MClinEpi, Karen Smith PhD, Monique F. Kilkenny PhD, MPH, Joosup Kim PhD, Kathleen L. Bagot PhD, Emily Andrew MBiostats, Shelley Cox PhD, Christopher F. Bladin PhD, MD, Dominique A. Cadilhac PhD, MPH
Format: Article
Language:English
Published: SAGE Publishing 2022-05-01
Series:Inquiry: The Journal of Health Care Organization, Provision, and Financing
Online Access:https://doi.org/10.1177/00469580221102200
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author Amminadab L. Eliakundu MClinEpi
Karen Smith PhD
Monique F. Kilkenny PhD, MPH
Joosup Kim PhD
Kathleen L. Bagot PhD
Emily Andrew MBiostats
Shelley Cox PhD
Christopher F. Bladin PhD, MD
Dominique A. Cadilhac PhD, MPH
author_facet Amminadab L. Eliakundu MClinEpi
Karen Smith PhD
Monique F. Kilkenny PhD, MPH
Joosup Kim PhD
Kathleen L. Bagot PhD
Emily Andrew MBiostats
Shelley Cox PhD
Christopher F. Bladin PhD, MD
Dominique A. Cadilhac PhD, MPH
author_sort Amminadab L. Eliakundu MClinEpi
collection DOAJ
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 doaj.art-0784690f9bb248e7ab8199e97b4761302022-12-22T00:26:07ZengSAGE PublishingInquiry: The Journal of Health Care Organization, Provision, and Financing0046-95801945-72432022-05-015910.1177/00469580221102200Linking Data From the Australian Stroke Clinical Registry With Ambulance and Emergency Administrative Data in VictoriaAmminadab L. Eliakundu MClinEpiKaren Smith PhDMonique F. Kilkenny PhD, MPHJoosup Kim PhDKathleen L. Bagot PhDEmily Andrew MBiostatsShelley Cox PhDChristopher F. Bladin PhD, MDDominique A. Cadilhac PhD, MPHObjective : 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.https://doi.org/10.1177/00469580221102200
spellingShingle Amminadab L. Eliakundu MClinEpi
Karen Smith PhD
Monique F. Kilkenny PhD, MPH
Joosup Kim PhD
Kathleen L. Bagot PhD
Emily Andrew MBiostats
Shelley Cox PhD
Christopher F. Bladin PhD, MD
Dominique A. Cadilhac PhD, MPH
Linking Data From the Australian Stroke Clinical Registry With Ambulance and Emergency Administrative Data in Victoria
Inquiry: The Journal of Health Care Organization, Provision, and Financing
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
url https://doi.org/10.1177/00469580221102200
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