Enhancing Registry Data Quality: Key Measures and Strategies

Registries play a central role in real-world evidence (RWE) studies by providing comprehensive, real-world data (RWD) on patient populations, treatments, and outcomes outside of controlled clinical trial settings. This data is invaluable for assessing disease progression, the effectiveness, safety, and utilization of medical interventions in everyday clinical practice, guiding healthcare decisions, and informing regulatory decisions. However, ensuring high-quality registry data for supporting regulatory assessments is still a widely discussed concern.

When selecting a fit-for-purpose data source, data quality is paramount as it guarantees a powerful study and instills confidence in regulators regarding the accuracy of data used for both pre- and post-authorization evaluations of medicines.

To understand how quality measures can ensure registries acceptance, comprehending the workflow of registries is vital, as data quality not only pertains to the registries themselves but also to the various data providers involved, such as hospitals, private care providers, national institutes responsible for death certificates, and claims institutes.

Most registries have implemented validation checks, including automatic checks embedded within the database, such as drop-down lists, lookup tables, alerts for mandatory fields, and assessments for consistency and completeness of values. Additionally, manual validation through primary source verifications is common to confirm data accuracy or identify missing information. Some registries also offer the flexibility to establish ad-hoc links to gather supplementary data as needed. However, not all registries might have the required expertise or experience to support all the relevant steps of the process to guarantee the highest data quality, moreover, when selecting the fit-for-purpose data sources needed for a specific study, it is still critical to perform a feasibility assessment to ensure that the data source selected can provide the desired evidence. Therefore, quality measures actions must be planned at all levels of data provision, coordination, collection, transfer, upload, and analysis. This collective effort ensures the integrity and reliability of registry data, thus enhancing their utility in regulatory decision-making processes.

To facilitate the implementation of quality measures, the European Network for Health Technology Assessment (EUnetHTA)* developed The Registry Evaluation and Quality Standards Tool (REQueST) aiming at guiding and evaluating registries for effective usage in HTA. The tool has been developed to be a comprehensive resource that covers all important aspects relating to the quality of registries. The standards set out in the tool are universal and essential elements of good practice and evidence quality that are, therefore, relevant for different types of registries.

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If you are not already familiar with the tool you can access it here: link.

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Accompanying the tool there is also a ‘vision paper’ which explores the options for the long-term delivery, use and sustainability of REQueST.

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*EUnetHTA was established to create an effective and sustainable network for HTA across Europe and to help develop reliable, timely, transparent, and transferable information to contribute to HTA in European countries.The overall strategic objective of the network is to connect public national/regional HTA agencies, research institutions and health ministries, enabling an effective exchange of information and support to policy decisions by the Member States. EUnetHTA consists of a total of 83 organisations from 27 EU member states plus Norway, Switzerland, Ukraine, and the UK.

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