Data Quality Assessment for Observational Medical Outcomes Partnership Common Data Model of Multi-Center

Seol Whan Oh; Soo Jeong Ko; Yun Seon Im; Surin Jung; Bo Yeon Choi; Jae Yoon Kim; Wona Choi; In Young Choi

doi:10.3233/SHTI230127

Data Quality Assessment for Observational Medical Outcomes Partnership Common Data Model of Multi-Center

Seol Whan Oh, Soo Jeong Ko, Yun Seon Im, Surin Jung, Bo Yeon Choi, Jae Yoon Kim, Wona Choi, In Young Choi

Department of Medical Informatics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023
Editors	Maria Hagglund, Madeleine Blusi, Stefano Bonacina, Lina Nilsson, Inge Cort Madsen, Sylvia Pelayo, Anne Moen, Arriel Benis, Lars Lindskold, Parisis Gallos
Publisher	IOS Press BV
Pages	322-326
Number of pages	5
ISBN (Electronic)	9781643683881
DOIs	https://doi.org/10.3233/SHTI230127
State	Published - 18 May 2023
Event	33rd Medical Informatics Europe Conference: Caring is Sharing - Exploiting the Value in Data for Health and Innovation, MIE2023 - Gothenburg, Sweden Duration: 22 May 2023 → 25 May 2023

Publication series

Name	Studies in Health Technology and Informatics
Volume	302
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Conference

Conference	33rd Medical Informatics Europe Conference: Caring is Sharing - Exploiting the Value in Data for Health and Innovation, MIE2023
Country/Territory	Sweden
City	Gothenburg
Period	22/05/23 → 25/05/23

Bibliographical note

Publisher Copyright:
© 2023 European Federation for Medical Informatics (EFMI) and IOS Press.

Keywords

Common Data Model
Data Quality
Data Quality Management System

Access to Document

10.3233/SHTI230127

Cite this

Oh, S. W., Ko, S. J., Im, Y. S., Jung, S., Choi, B. Y., Kim, J. Y., Choi, W., & Choi, I. Y. (2023). Data Quality Assessment for Observational Medical Outcomes Partnership Common Data Model of Multi-Center. In M. Hagglund, M. Blusi, S. Bonacina, L. Nilsson, I. C. Madsen, S. Pelayo, A. Moen, A. Benis, L. Lindskold, & P. Gallos (Eds.), Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023 (pp. 322-326). (Studies in Health Technology and Informatics; Vol. 302). IOS Press BV. https://doi.org/10.3233/SHTI230127

Oh, Seol Whan ; Ko, Soo Jeong ; Im, Yun Seon et al. / Data Quality Assessment for Observational Medical Outcomes Partnership Common Data Model of Multi-Center. Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023. editor / Maria Hagglund ; Madeleine Blusi ; Stefano Bonacina ; Lina Nilsson ; Inge Cort Madsen ; Sylvia Pelayo ; Anne Moen ; Arriel Benis ; Lars Lindskold ; Parisis Gallos. IOS Press BV, 2023. pp. 322-326 (Studies in Health Technology and Informatics).

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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.",

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Oh, SW, Ko, SJ, Im, YS, Jung, S, Choi, BY, Kim, JY, Choi, W & Choi, IY 2023, Data Quality Assessment for Observational Medical Outcomes Partnership Common Data Model of Multi-Center. in M Hagglund, M Blusi, S Bonacina, L Nilsson, IC Madsen, S Pelayo, A Moen, A Benis, L Lindskold & P Gallos (eds), Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023. Studies in Health Technology and Informatics, vol. 302, IOS Press BV, pp. 322-326, 33rd Medical Informatics Europe Conference: Caring is Sharing - Exploiting the Value in Data for Health and Innovation, MIE2023, Gothenburg, Sweden, 22/05/23. https://doi.org/10.3233/SHTI230127

Data Quality Assessment for Observational Medical Outcomes Partnership Common Data Model of Multi-Center. / Oh, Seol Whan; Ko, Soo Jeong; Im, Yun Seon et al.
Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023. ed. / Maria Hagglund; Madeleine Blusi; Stefano Bonacina; Lina Nilsson; Inge Cort Madsen; Sylvia Pelayo; Anne Moen; Arriel Benis; Lars Lindskold; Parisis Gallos. IOS Press BV, 2023. p. 322-326 (Studies in Health Technology and Informatics; Vol. 302).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Oh, Seol Whan

AU - Ko, Soo Jeong

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AU - Jung, Surin

AU - Choi, Bo Yeon

AU - Kim, Jae Yoon

AU - Choi, Wona

AU - Choi, In Young

PY - 2023/5/18

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N2 - 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.

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Oh SW, Ko SJ, Im YS, Jung S, Choi BY, Kim JY et al. Data Quality Assessment for Observational Medical Outcomes Partnership Common Data Model of Multi-Center. In Hagglund M, Blusi M, Bonacina S, Nilsson L, Madsen IC, Pelayo S, Moen A, Benis A, Lindskold L, Gallos P, editors, Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023. IOS Press BV. 2023. p. 322-326. (Studies in Health Technology and Informatics). doi: 10.3233/SHTI230127

Data Quality Assessment for Observational Medical Outcomes Partnership Common Data Model of Multi-Center

Abstract

Publication series

Conference

Bibliographical note

Keywords

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Catholic University of Korea Reports Findings in Data Modeling (Data Quality Assessment for Observational Medical Outcomes Partnership Common Data Model of Multi-Center)

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Data Quality Assessment for Observational Medical Outcomes Partnership Common Data Model of Multi-Center

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Press/Media

Catholic University of Korea Reports Findings in Data Modeling (Data Quality Assessment for Observational Medical Outcomes Partnership Common Data Model of Multi-Center)

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