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Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

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Data Quality in Rare Diseases Registries.

Yllka Kodra¹, Manuel Posada de la Paz², Alessio Coi³

¹Centro Nazionale Malattie Rare, Istituto Superiore di Sanità, Viale Regina Elena 299, CAP, 00161, Rome, Italy. yllka.kodra@iss.it.

Advances in Experimental Medicine and Biology

|December 8, 2017

Summary

This summary is machine-generated.

High-quality data is crucial for rare disease registries to support clinical research and patient care. This study introduces a template to help registry owners describe their data quality, ensuring its reliability and usefulness.

Keywords:

Clinical research registry Data quality indicators Public health registry Quality assurance plan Rare diseases registries Validity

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Area of Science:

Medical Informatics
Rare Disease Research
Data Management

Background:

Rare disease registries are vital for advancing clinical research, trial planning, patient care, and healthcare strategies.
High-quality data is a cornerstone for the establishment and effective maintenance of these registries.
Data quality encompasses features like completeness, validity, coherence, accessibility, usefulness, and timeliness.

Purpose of the Study:

To address the need for a standardized quality validation process for rare disease registries.
To provide a template to guide registry owners in describing their registries for data quality assessment.

Main Methods:

Defining data quality through key dimensions: completeness, validity, coherence, comparability, accessibility, usefulness, timeliness, and duplicate record prevention.
Identifying influencing factors such as standardized Case Report Forms and informatics infrastructure security.
Proposing a clear registry description as the initial step in data quality assessment.

Main Results:

A template is presented as a guide for registry owners to systematically describe their registries.
This description facilitates the assessment of data quality and the evaluation of the registry system.

Conclusions:

A structured approach to describing rare disease registries is essential for evaluating data quality.
The developed template aids in ensuring the reliability and utility of data for research and healthcare planning.