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Determining the Optimal Methodology for Identifying Incident Stroke Deaths Using Administrative Datasets Within Australia - 18/07/24

Doi : 10.1016/j.hlc.2024.01.020 
Anna H. Balabanski, MBBS, PhD a, b, , Lee Nedkoff, PhD c, Amanda G. Thrift, PhD a, Timothy J. Kleinig, MBBS, PhD d, e, Alex Brown, PhD e, f, Odette Pearson, PhD e, f, Steven Guthridge, FAFPHM g, Angela Dos Santos, MBBS b, h, Judith M. Katzenellenbogen, PhD c
a Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Vic, Australia 
b Department of Neuroscience, The Central Clinical School, Monash University & Alfred Health, Melbourne, Vic, Australia 
c Cardiovascular Epidemiology Research Centre, School of Population and Global Health, University of Western Australia, Perth, WA, Australia 
d Department of Neurology, Royal Adelaide Hospital, Adelaide, SA, Australia 
e Faculty of Health and Medical Science, University of Adelaide, SA, Australia 
f South Australian Health and Medical Research Institute, Adelaide, SA, Australia 
g Menzies School of Health Research, Charles Darwin University, Darwin, NT, Australia 
h South West Sydney Clinical School, University of New South Wales, Liverpool, Sydney, NSW, Australia 

Corresponding author at: Department of Neuroscience, Central Clinical School, Monash University, The Alfred Centre, Level 6, 99 Commercial Road, Melbourne, Vic 3004, AustraliaDepartment of NeuroscienceCentral Clinical SchoolMonash UniversityThe Alfred CentreLevel 699 Commercial RoadMelbourneVic3004Australia

Abstract

Background and Aim

Quantifying stroke incidence and mortality is crucial for disease surveillance and health system planning. Administrative data offer a cost-effective alternative to “gold standard” population-based studies. However, the optimal methodology for establishing stroke deaths from administrative data remains unclear. We aimed to determine the optimal method for identifying stroke-related deaths in administrative datasets as the fatal component of stroke incidence, comparing counts derived using underlying and all causes of death (CoD).

Method

Using whole-population multijurisdictional person-level linked data from hospital and death datasets from South Australia, the Northern Territory, and Western Australia, we identified first-ever stroke events between 2012 and 2015, using underlying CoD and all CoD to identify fatal stroke counts. We determined the 28-day case fatality for both counts and compared results with gold standard Australian population-based stroke incidence studies.

Results

The total number of incident stroke events was 16,150 using underlying CoD and 18,074 using all CoD. Case fatality was 24.7% and 32.7% using underlying and all CoD, respectively. Case fatality using underlying CoD was similar to that observed in four Australian "gold standard" population-based studies (20%–24%).

Conclusions

Underlying CoD generates fatal incident stroke estimates more consistent with population-based studies than estimates based on stroke deaths identified from all-cause fields in death registers.

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Keywords : Stroke, Mortality, Epidemiology, Methods, Incidence


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© 2024  The Author(s). Publicado por Elsevier Masson SAS. Todos los derechos reservados.
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Vol 33 - N° 7

P. 1046-1049 - juillet 2024 Regresar al número
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