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Development of Integrated Data Quality Management System for Observational Medical Outcomes Partnership Common Data Model.

Authors :
Seol Whan OH
Soo Jeong KO
Yun Seon IM
Surin JUNG
Bo Yeon CHOI
Jae Yoon KIM
Sunghyeon PARK
Wona CHOI
In Young CHOI
Source :
Medinfo; 2023, Vol. 310, p349-353, 5p
Publication Year :
2023

Abstract

The amount of research on the gathering and handling of healthcare data keeps growing. To support multi-center research, numerous institutions have sought to create a common data model (CDM). However, data quality issues continue to be a major obstacle in the development of CDM. To address these limitations, a data quality assessment system was created based on the representative data model OMOP CDM v5.3.1. Additionally, 2,433 advanced evaluation rules were created and incorporated into the system by mapping the rules of existing OMOP CDM quality assessment systems. The data quality of six hospitals was verified using the developed system and an overall error rate of 0.197% was confirmed. Finally, we proposed a plan for high-quality data generation and the evaluation of multi-center CDM quality. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15696332
Volume :
310
Database :
Complementary Index
Journal :
Medinfo
Publication Type :
Conference
Accession number :
175124478
Full Text :
https://doi.org/10.3233/SHTI230985