Evidence map›Paper›PMID 30595684›Full record

ArticleJournal of Korean medical science2018

Building Linked Big Data for Stroke in Korea: Linkage of Stroke Registry and National Health Insurance Claims Data.

Tae Jung Kim, Ji Sung Lee, Ji-Woo Kim, Mi Sun Oh, Heejung Mo, Chan-Hyuk Lee, Han-Young Jeong, Keun-Hwa Jung, Jae-Sung Lim, Sang-Bae Ko and 3 more

Abstract read
In one paragraph

Article in Journal of Korean medical science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

13 authors.

Tae Jung KimDepartment of Neurology, Seoul National University Hospital, Seoul, Korea.ORCID https://orcid.org/0000-0003-3616-5627
Ji Sung LeeClinical Research Center, Asan Medical Center, University of Ulsan, Seoul, Korea.ORCID https://orcid.org/0000-0001-8194-3462
Ji-Woo KimDepartment of Bigdata, Health Insurance Review and Assessment Service, Wonju, Korea.ORCID https://orcid.org/0000-0002-4070-3021
Mi Sun OhDepartment of Neurology, Hallym University Sacred Heart Hospital, Anyang, Korea.ORCID https://orcid.org/0000-0002-6741-0464
Heejung MoDepartment of Neurology, Seoul National University Hospital, Seoul, Korea.ORCID https://orcid.org/0000-0001-7810-035X
Chan-Hyuk LeeDepartment of Neurology, Seoul National University Hospital, Seoul, Korea.ORCID https://orcid.org/0000-0002-3421-0909
Han-Young JeongDepartment of Neurology, Seoul National University Hospital, Seoul, Korea.ORCID https://orcid.org/0000-0002-3373-118X
Keun-Hwa JungDepartment of Neurology, Seoul National University Hospital, Seoul, Korea.ORCID https://orcid.org/0000-0003-1433-8005
Jae-Sung LimDepartment of Neurology, Hallym University Sacred Heart Hospital, Anyang, Korea.ORCID https://orcid.org/0000-0001-6157-2908
Sang-Bae KoDepartment of Neurology, Seoul National University Hospital, Seoul, Korea.ORCID https://orcid.org/0000-0002-9429-9597
Kyung-Ho YuDepartment of Neurology, Hallym University Sacred Heart Hospital, Anyang, Korea.ORCID https://orcid.org/0000-0002-8997-5626
Byung-Chul LeeDepartment of Neurology, Hallym University Sacred Heart Hospital, Anyang, Korea.ORCID https://orcid.org/0000-0002-3885-981X
Byung-Woo YoonDepartment of Neurology, Seoul National University Hospital, Seoul, Korea.ORCID https://orcid.org/0000-0002-8597-807X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLinkage of public healthcare data is useful in stroke research because patients may visit different sectors of the health system before, during, and after stroke. Therefore, we aimed to establish high-quality big data on stroke in Korea by linking acute stroke registry and national health claim databases.

methodsAcute stroke patients (n = 65,311) with claim data suitable for linkage were included in the Clinical Research Center for Stroke (CRCS) registry during 2006-2014. We linked the CRCS registry with national health claim databases in the Health Insurance Review and Assessment Service (HIRA). Linkage was performed using 6 common variables: birth date, gender, provider identification, receiving year and number, and statement serial number in the benefit claim statement. For matched records, linkage accuracy was evaluated using differences between hospital visiting date in the CRCS registry and the commencement date for health insurance care in HIRA.

resultsOf 65,311 CRCS cases, 64,634 were matched to HIRA cases (match rate, 99.0%). The proportion of true matches was 94.4% (n = 61,017) in the matched data. Among true matches (mean age 66.4 years; men 58.4%), the median National Institutes of Health Stroke Scale score was 3 (interquartile range 1-7). When comparing baseline characteristics between true matches and false matches, no substantial difference was observed for any variable.

conclusionWe could establish big data on stroke by linking CRCS registry and HIRA records, using claims data without personal identifiers. We plan to conduct national stroke research and improve stroke care using the linked big database.

Indexed as

Databases, FactualInformation Storage and RetrievalAcute DiseaseAgedBig DataFemaleHumansInsurance Claim ReviewMaleMiddle AgedRegistriesStrokeBig DataData LinkageNational Health Claim DataStroke Registry

Identifiers

PMID30595684
PMCPMC6306322

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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.