Data quality refers to the ability of a dataset to be used to research specific questions. High quality data is accurate, complete, and contains the data needed to answer a specific question or set of questions. High quality data is also verifiable, for example, a participant’s diagnosis can be confirmed.
For registries, high quality data can be achieved by focusing the information requested from the participant to the goal of the registry and monitoring the data for accuracy and completeness. Similarly, clinical studies and clinical trials monitor and collect data required to answer the study questions, such as does this treatment slow or stop the progression of a specific symptom. Low-quality data cannot be used by researchers or regulators.
Obtaining Data and Quality Assurance from “Registries for Evaluating Patient Outcomes: A User’s Guide” [4th Edition, 2020]
Rare Diseases Registry Program (RaDaR): Understand What Data Is
Rare Diseases Registry Program (RaDaR): Perform Data Quality Control