JMIR Publications

ABSTRACT

Background:

Data quality is fundamental to maintain the trust and reliability of health data for both primary and secondary purposes. However, before 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 seven Belgian hospitals 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 three distinct departments – surgical, geriatrics, and paediatrics – in each of the seven 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 healthcare organizations by sharing knowledge and good practices, establishing a foundation for future, similar research.