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Building a foundation for high-quality health data : multihospital case study in Belgium

Jens Declerck (UGent) , Bert Vandenberk, Mieke Deschepper (UGent) , Kirsten Colpaert (UGent) , Lieselot Cool, Jens Goemaere, Frank Staelens (UGent) , Koen De Meester, Eva Verbeke, Elke Smits, et al.
(2024) JMIR MEDICAL INFORMATICS. 12.
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Abstract
Background: Data quality is fundamental to maintaining the trust and reliability of health data for both primary and secondary purposes. However, before the secondary use of health data, it is essential to assess the quality at the source and to develop systematic methods for the assessment of important data quality dimensions. Objective: This case study aims to offer a dual aim-to assess the data quality of height and weight measurements across 7 Belgian hospitals, focusing on the dimensions of completeness and consistency, and to outline the obstacles these hospitals face in sharing and improving data quality standards. Methods: Focusing on data quality dimensions completeness and consistency, this study examined height and weight data collected from 2021 to 2022 within 3 distinct departments-surgical, geriatrics, and pediatrics-in each of the 7 hospitals. Results: Variability was observed in the completeness scores for height across hospitals and departments, especially within surgical and geriatric wards. In contrast, weight data uniformly achieved high completeness scores. Notably, the consistency of height and weight data recording was uniformly high across all departments. Conclusions: A collective collaboration among Belgian hospitals, transcending network affiliations, was formed to conduct this data quality assessment. This study demonstrates the potential for improving data quality across health care organizations by sharing knowledge and good practices, establishing a foundation for future, similar research.
Keywords
EHR, electronic health records, health data, data quality dimensions, data quality assessment, secondary use, data quality framework, fit for purpose, Belgium, data quality, framework, case study, hospital, variability

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MLA
Declerck, Jens, et al. “Building a Foundation for High-Quality Health Data : Multihospital Case Study in Belgium.” JMIR MEDICAL INFORMATICS, vol. 12, 2024, doi:10.2196/60244.
APA
Declerck, J., Vandenberk, B., Deschepper, M., Colpaert, K., Cool, L., Goemaere, J., … Coorevits, P. (2024). Building a foundation for high-quality health data : multihospital case study in Belgium. JMIR MEDICAL INFORMATICS, 12. https://doi.org/10.2196/60244
Chicago author-date
Declerck, Jens, Bert Vandenberk, Mieke Deschepper, Kirsten Colpaert, Lieselot Cool, Jens Goemaere, Frank Staelens, et al. 2024. “Building a Foundation for High-Quality Health Data : Multihospital Case Study in Belgium.” JMIR MEDICAL INFORMATICS 12. https://doi.org/10.2196/60244.
Chicago author-date (all authors)
Declerck, Jens, Bert Vandenberk, Mieke Deschepper, Kirsten Colpaert, Lieselot Cool, Jens Goemaere, Frank Staelens, Koen De Meester, Eva Verbeke, Elke Smits, Cami De Decker, Nicky Van Der Vekens, Elin Pauwels, Robert Vander Stichele, Dipak Kalra, and Pascal Coorevits. 2024. “Building a Foundation for High-Quality Health Data : Multihospital Case Study in Belgium.” JMIR MEDICAL INFORMATICS 12. doi:10.2196/60244.
Vancouver
1.
Declerck J, Vandenberk B, Deschepper M, Colpaert K, Cool L, Goemaere J, et al. Building a foundation for high-quality health data : multihospital case study in Belgium. JMIR MEDICAL INFORMATICS. 2024;12.
IEEE
[1]
J. Declerck et al., “Building a foundation for high-quality health data : multihospital case study in Belgium,” JMIR MEDICAL INFORMATICS, vol. 12, 2024.
@article{01JJ1FY57ATYB9SZAXCSC0CDY2,
  abstract     = {{Background: Data quality is fundamental to maintaining the trust and reliability of health data for both primary and secondary purposes. However, before the secondary use of health data, it is essential to assess the quality at the source and to develop systematic methods for the assessment of important data quality dimensions. Objective: This case study aims to offer a dual aim-to assess the data quality of height and weight measurements across 7 Belgian hospitals, focusing on the dimensions of completeness and consistency, and to outline the obstacles these hospitals face in sharing and improving data quality standards. Methods: Focusing on data quality dimensions completeness and consistency, this study examined height and weight data collected from 2021 to 2022 within 3 distinct departments-surgical, geriatrics, and pediatrics-in each of the 7 hospitals. Results: Variability was observed in the completeness scores for height across hospitals and departments, especially within surgical and geriatric wards. In contrast, weight data uniformly achieved high completeness scores. Notably, the consistency of height and weight data recording was uniformly high across all departments. Conclusions: A collective collaboration among Belgian hospitals, transcending network affiliations, was formed to conduct this data quality assessment. This study demonstrates the potential for improving data quality across health care organizations by sharing knowledge and good practices, establishing a foundation for future, similar research.}},
  articleno    = {{e60244}},
  author       = {{Declerck, Jens and Vandenberk, Bert and Deschepper, Mieke and Colpaert, Kirsten and Cool, Lieselot and Goemaere, Jens and Staelens, Frank and De Meester, Koen and Verbeke, Eva and Smits, Elke and De Decker, Cami and Van Der Vekens, Nicky and Pauwels, Elin and Vander Stichele, Robert and Kalra, Dipak and Coorevits, Pascal}},
  issn         = {{2291-9694}},
  journal      = {{JMIR MEDICAL INFORMATICS}},
  keywords     = {{EHR,electronic health records,health data,data quality dimensions,data quality assessment,secondary use,data quality framework,fit for purpose,Belgium,data quality,framework,case study,hospital,variability}},
  language     = {{eng}},
  pages        = {{10}},
  title        = {{Building a foundation for high-quality health data : multihospital case study in Belgium}},
  url          = {{http://doi.org/10.2196/60244}},
  volume       = {{12}},
  year         = {{2024}},
}
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