Evidence map›Paper›PMID 41550612›Full record

ArticleThe Lancet regional health. Western Pacific2026

Can administrative data be used for a national register of hospitalised stroke patients? A New Zealand validation study.

Marine Corbin, Hayley J Denison, Jeroen Douwes, Mina Whyte, Stephanie G Thompson, Matire Harwood, Alan Davis, John N Fink, P Alan Barber, John H Gommans and 6 more

Abstract read
In one paragraph

Article in The Lancet regional health. Western Pacific, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Marine CorbinResearch Centre for Hauora and Heath, Massey University, New Zealand.
Hayley J DenisonResearch Centre for Hauora and Heath, Massey University, New Zealand.
Jeroen DouwesResearch Centre for Hauora and Heath, Massey University, New Zealand.
Mina WhyteDepartment of Medicine, University of Otago Wellington, New Zealand.
Stephanie G ThompsonDepartment of Medicine, University of Otago Wellington, New Zealand.
Matire HarwoodDepartment of General Practice and Primary Health Care, University of Auckland, New Zealand.
Alan DavisDepartment of Medicine, Whangarei Hospital, New Zealand.
John N FinkDepartment of Neurology, Christchurch Hospital, New Zealand.
P Alan BarberDepartment of General Practice and Primary Health Care, University of Auckland, New Zealand.
John H GommansDepartment of Medicine, Hawke's Bay Hospital, New Zealand.
Dominique A CadilhacDepartment of Medicine, School of Clinical Sciences, Monash University, Clayton, VIC, Australia.
William M LevackDepartment of Medicine, University of Otago Wellington, New Zealand.
Harry McNaughtonMedical Research Institute of New Zealand, New Zealand.
Joosup KimDepartment of Medicine, School of Clinical Sciences, Monash University, Clayton, VIC, Australia.
Valery L FeiginNational Institute for Stroke and Applied Neurosciences, School of Clinical Sciences, Auckland University of Technology, New Zealand.
Anna RantaDepartment of Medicine, University of Otago Wellington, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Using community-based incidence studies and clinical registries to assess stroke care and outcomes is resource intensive and often geographically limited. Linked administrative data are lower-cost and wider-reaching, but potentially less accurate and complete. This study compared administrative data to national hospital-based study data to assess whether administrative data represents a valid alternative. Methods: We linked and compared data from the REGIONS Care Study, a New Zealand nationwide observational study, with administrative data from Statistics New Zealand's Integrated Data Infrastructure (IDI). Sensitivity, specificity, positive predictive value, and Cohen's kappa coefficient were used to assess case identification, risk factors, post-stroke outcomes, and interventions as applicable. Additional audits explored the validity of IDI 'true false positives.' Findings: From May to July 2018, 1719 patients with stroke were captured in REGIONS Care and 1833 in the IDI. Using REGIONS Care as the reference standard, the sensitivity of the IDI for stroke case identification was 83% and the positive predictive value 77%. There were 300 false-negatives and 414 false positives. The audit of two hospitals showed that some cases identified in IDI but excluded by REGIONS were actual strokes. For stroke risk factors, the IDI showed high sensitivity and specificity for diabetes (93% and 91%, respectively), atrial fibrillation (87% and 90%), and smoking (71% and 97%) but lower specificity for hypertension (61%), and dyslipidaemia (52%). A derived IDI favourable outcome measure showed good agreement with the modified Rankin Scale (sensitivity 88%, specificity 82%, kappa 0.67). The IDI accurately identified post-stroke medication use (sensitivities 81%-94%, specificities 78%-91%) and thrombectomy interventions (sensitivity 88%, kappa 0.91). Interpretation: The use of administrative data to ascertain stroke cases, risk factors, interventions and outcomes was feasible and compared well with manual hospital data collection making an administrative data based national stroke register possible, although supplementary data collection for comprehensive care evaluation may be required. Funding: The study was funded by the NZ Health Research Council (HRC 17/037).

Indexed as

Genetic panelsHereditary cancer predisposition syndromesPersonalized medicine

Identifiers

PMID41550612
PMCPMC12809099

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.