TY  - JOUR
AU  - Declerck, Jens
AU  - Vandenberk, Bert
AU  - Deschepper, Mieke
AU  - Colpaert, Kirsten
AU  - Cool, Lieselot
AU  - Goemaere, Jens
AU  - Bové, Mona
AU  - Staelens, Frank
AU  - De Meester, Koen
AU  - Verbeke, Eva
AU  - Smits, Elke
AU  - De Decker, Cami
AU  - Van Der Vekens, Nicky
AU  - Pauwels, Elin
AU  - Vander Stichele, Robert
AU  - Kalra, Dipak
AU  - Coorevits, Pascal
PY  - 2024
DA  - 2024/12/20
TI  - Building a Foundation for High-Quality Health Data: Multihospital Case Study in Belgium
JO  - JMIR Med Inform
SP  - e60244
VL  - 12
KW  - EHR
KW  - electronic health records
KW  - health data
KW  - data quality dimensions
KW  - data quality assessment
KW  - secondary use
KW  - data quality framework
KW  - fit for purpose
KW  - Belgium
KW  - data quality
KW  - framework
KW  - case study
KW  - hospital
KW  - variability
AB  - 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. 
SN  - 2291-9694
UR  - https://medinform.jmir.org/2024/1/e60244
UR  - https://doi.org/10.2196/60244
DO  - 10.2196/60244
ID  - info:doi/10.2196/60244
ER  -