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

Abstract

Background: Advanced 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.

Methods: The 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.

Results: Through 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.

Conclusions: This 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.