Related Experiment Video
Updated: Jun 7, 2026

A Novel Method for Involving Women of Color at High Risk for Preterm Birth in Research Priority Setting
Published on: January 12, 2018
A Collection of Data Quality Indicators for Health Research: Rationale for an Update
Jürgen Stausberg1, Sonja Harkener1, Solveig Bünz1
1Institute for Medical Informatics, Biometry and Epidemiology, Faculty of Medicine, University Duisburg-Essen, Essen, Germany.
Abstract:
Structured data are the capital of empirical health research. The value of these data relates to their quality and to their fit for use. A German guideline for the management of data quality in registries and cohort studies lists 51 quality indicators organized into the categories organization, integrity, and trueness. An update of the guideline will take into account the current view on dimensions of data, the appropriate structure for the definition of an indicator, and the collection of quality indicators itself. In the next version, the collection will explicitly address measures of metadata quality. The first step of a literature review revealed a high number of potential sources of evidence. These will be categorized into the topics dimensions, structure, and indicators respectively. Special attention will be paid to new challenges of data quality control arising from big data and artificial intelligence.
More Related Videos
07:50A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
06:05The Participant-Reported Implementation Update and Score (PRIUS): A Novel Method for Capturing Implementation-Related Data Over Time
Published on: February 19, 2021
Related Concept Videos
Data Collection I
Data Validation
Nursing assessment guides are generally based on holistic models rather than medical...
Purpose of Health Records I
Here's a breakdown of how health records serve these purposes:
Health Information Technology and Healthcare Information System
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
Data Validation
Key parameters for method validation include:
Principles of Disease Surveillance