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Maximising data value and avoiding data waste : A validation study in stroke research
Kilkenny, Monique F. Kim, Joosup Andrew, Nadine E. Sundararajan, Vijaya Thrift, Amanda G. Katzenellenbogen, Judith M. Flack, Felicity Gattellari, Melina Boyd, James H. Anderson, Phil
Kilkenny, Monique F.
Kim, Joosup
Andrew, Nadine E.
Sundararajan, Vijaya
Thrift, Amanda G.
Katzenellenbogen, Judith M.
Flack, Felicity
Gattellari, Melina
Boyd, James H.
Anderson, Phil
Author
Kilkenny, Monique F.
Kim, Joosup
Andrew, Nadine E.
Sundararajan, Vijaya
Thrift, Amanda G.
Katzenellenbogen, Judith M.
Flack, Felicity
Gattellari, Melina
Boyd, James H.
Anderson, Phil
Lannin, Natasha
Sipthorp, Mark
Chen, Ying
Johnston, Trisha
Anderson, Craig S.
Middleton, Sandy
Donnan, Geoffrey A.
Cadihac, Dominique A.
Kim, Joosup
Andrew, Nadine E.
Sundararajan, Vijaya
Thrift, Amanda G.
Katzenellenbogen, Judith M.
Flack, Felicity
Gattellari, Melina
Boyd, James H.
Anderson, Phil
Lannin, Natasha
Sipthorp, Mark
Chen, Ying
Johnston, Trisha
Anderson, Craig S.
Middleton, Sandy
Donnan, Geoffrey A.
Cadihac, Dominique A.
Abstract
Objectives
To determine the feasibility of linking data from the Australian Stroke Clinical Registry (AuSCR), the National Death Index (NDI), and state-managed databases for hospital admissions and emergency presentations; to evaluate data completeness and concordance between datasets for common variables.
Design, setting, participants
Cohort design; probabilistic/deterministic data linkage of merged records for patients treated in hospital for stroke or transient ischaemic attack from New South Wales, Queensland, Victoria, and Western Australia.
Main outcome measures
Descriptive statistics for data matching success; concordance of demographic variables common to linked databases; sensitivity and specificity of AuSCR in-hospital death data for predicting NDI registrations.
Results
Data for 16 214 patients registered in the AuSCR during 2009–2013 were linked with one or more state datasets: 15 482 matches (95%) with hospital admissions data, and 12 902 matches (80%) with emergency department presentations data were made. Concordance of AuSCR and hospital admissions data exceeded 99% for sex, age, in-hospital death (each κ = 0.99), and Indigenous status (κ = 0.83). Of 1498 registrants identified in the AuSCR as dying in hospital, 1440 (96%) were also recorded by the NDI as dying in hospital. In-hospital death in AuSCR data had 98.7% sensitivity and 99.6% specificity for predicting in-hospital death in the NDI.
Conclusion
We report the first linkage of data from an Australian national clinical quality disease registry with routinely collected data from several national and state government health datasets. Data linkage enriches the clinical registry dataset and provides additional information beyond that for the acute care setting and quality of life at follow-up, allowing clinical outcomes for people with stroke (mortality and hospital contacts) to be more comprehensively assessed.
Keywords
data collection, stroke, health services research, registries, health status indicators
Date
2019
Type
Journal article
Journal
Medical Journal of Australia
Book
Volume
210
Issue
1
Page Range
27-31
Article Number
ACU Department
Nursing Research Institute
Faculty of Health Sciences
Faculty of Health Sciences
Collections
Relation URI
Source URL
Event URL
Open Access Status
License
All rights reserved
File Access
Controlled