Evidence map›Paper›PMID 41063166›Full record

ArticleBMC medical informatics and decision making2025

Development of a big data platform for collecting and utilizing clinical information from the Korea Biobank Network.

Yun Seon Im, Seol Whan Oh, Ki Hoon Kim, Wona Choi, In Young Choi

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2025. 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

5 authors.

Yun Seon ImDepartment of Medical Sciences, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.ORCID 0000-0002-2510-1380
Seol Whan OhDepartment of Medical Sciences, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.ORCID 0000-0002-0328-9634
Ki Hoon KimDepartment of Medical Sciences, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.ORCID 0009-0005-7426-0723
Wona ChoiDepartment of Medical Informatics, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea. choiwona@gmail.com.ORCID 0000-0003-0269-6374
In Young ChoiDepartment of Medical Informatics, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea. iychoi@catholic.ac.kr.ORCID 0000-0002-2860-9411

Funding

the National Institute of Health(NIH) research project 2024-ER0502-00#
6 · The paper itself

Abstract

backgroundAdvanced biobanks increasingly focus on supporting biomedical research through the collection and integration of large-scale biological and clinical datasets. This study aimed to develop a big data platform that enables institutions within the Korea Biobank Network (KBN) to efficiently collect and utilize clinical information using a standardized common data model.

methodsThe KBN Biobank Research Information and Digital Image Exchange (BRIDGE) platform was developed to allow 43 biobanks to systemically collect and upload electronic medical records and clinical data. This platform was designed to incorporate automated quality verification and basic statistical preprocessing functionalities, allowing users to analyze data efficiently without complex queries. Additionally, a survey was conducted to evaluate user satisfaction with the platform.

resultsThrough the KBN BRIDGE platform, institutions collected and integrated clinical information on 39 diseases. A total of 136,473 patients' clinical data, collected by institutions between 2021 and 2023, were uploaded to the KBN common data model, including 43,330 serum samples, 33,352 plasma samples, and 22,279 buffy coat samples. A satisfaction survey conducted among 35 institutional data managers reported an average score of 3.5 out of 5 for the platform.

conclusionsThis study developed and demonstrated that the KBN BRIDGE platform enables institutions to systematically collect, integrate, and manage large-scale clinical information across multiple biobanks. Furthermore, through data quality management and preprocessing statistical functions, the platform has shown potential for several research applications. Future improvements in system functionality and clinical information utilization can further enhance the platform's utility across various research fields.

Indexed as

Big DataBiological Specimen BanksBiomedical ResearchElectronic Health RecordsHumansRepublic of KoreaBiobankBiorepositoryDatabase management systemsData processingElectronic health recordInformation managementSurvey

Identifiers

PMID41063166
PMCPMC12505599

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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.