Building a Foundation for High-Quality Health Data: Multihospital Case Study in Belgium.

Autor:	Declerck J; Department of Public Health and Primary Care, Unit of Medical Informatics and Statistics, Ghent University, Ghent, Belgium.; The European Institute for Innovation through Health Data, Ghent, Belgium., Vandenberk B; Department of Cardiovascular Sciences, University Hospitals Leuven, Leuven, Belgium., Deschepper M; Data Science Institute, Ghent University Hospital, Ghent, Belgium., Colpaert K; Data Science Institute, Ghent University Hospital, Ghent, Belgium., Cool L; Data Science, Algemeen Ziekenhuis Groeninge, Kortrijk, Belgium., Goemaere J; Data Science, Algemeen Ziekenhuis Groeninge, Kortrijk, Belgium., Bové M; Department of Quality and Process Managenemt, Onze-Lieve-Vrouw Hospital, Aalst, Belgium., Staelens F; Department of Quality and Process Managenemt, Onze-Lieve-Vrouw Hospital, Aalst, Belgium., De Meester K; Cell Business Intelligence, Algemeen Ziekenhuis Sint-Lucas, Ghent, Belgium., Verbeke E; Cell Business Intelligence, Algemeen Ziekenhuis Sint-Lucas, Ghent, Belgium., Smits E; Clinical Research Center, Antwerp University Hospital, Antwerp, Belgium.; University of Antwerp, Antwerp, Belgium., De Decker C; Clinical Research Center, Antwerp University Hospital, Antwerp, Belgium., Van Der Vekens N; Clinical Data Manager, General Hospital Maria Middelares, Ghent, Belgium., Pauwels E; Quality Department, General Hospital Maria Middelares, Ghent, Belgium., Vander Stichele R; Faculty of Medicine and Health Sciences, Heymans Institute of Pharmacology, Ghent, Belgium., Kalra D; Department of Public Health and Primary Care, Unit of Medical Informatics and Statistics, Ghent University, Ghent, Belgium.; The European Institute for Innovation through Health Data, Ghent, Belgium., Coorevits P; Department of Public Health and Primary Care, Unit of Medical Informatics and Statistics, Ghent University, Ghent, Belgium.
Jazyk:	angličtina
Zdroj:	JMIR medical informatics [JMIR Med Inform] 2024 Dec 20; Vol. 12, pp. e60244. Date of Electronic Publication: 2024 Dec 20.
DOI:	10.2196/60244
Abstrakt:	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. (© Jens Declerck, Bert Vandenberk, Mieke Deschepper, Kirsten Colpaert, Lieselot Cool, Jens Goemaere, Mona Bové, Frank Staelens, Koen De Meester, Eva Verbeke, Elke Smits, Cami De Decker, Nicky Van Der Vekens, Elin Pauwels, Robert Vander Stichele, Dipak Kalra, Pascal Coorevits. Originally published in JMIR Medical Informatics (https://medinform.jmir.org).)
Databáze:	MEDLINE
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