7 Challenges of Mastering Clinical Data Registries: Maintainability and Longevity

7 Challenges of Mastering Clinical Data Registries: Maintainability and Longevity

This series outlines the Seven Informatics Challenges for Clinical Data Registries, the questions you should ask when addressing research data management, and how our RexStudy platform is engineered to ensure your research teams generate high-quality, reliable, and statistically sound data.

Building CDRs that support acquisition, curation, and dissemination of clinical research data poses a number of unique challenges. For example, a center-level CDR system needs to accumulate data across multiple studies, time points, and data-types. At the same time, it needs to support research operations workflows that are heterogeneous across projects. CDRs must operate within a complex ecology of data sources, consumers, and governance. The complex ecology poses a number of informatics challenges to delivering CDRs.

Informatics Challenge #7: Maintainability and Longevity

Systems that support complex research activities must be maintainable, often over decades, in several ways. They must be relatively easy to adapt to expected, and unexpected changes to the environment; they must be capable of being maintained by in-house or third party staff, in case the original delivery team becomes unavailable; they must also store data in a manner that assures the longevity of the valuable research assets, despite unknowable future technological changes.

Questions you should ask before building your CDR 

  • Is the data storage layer sufficiently transparent and portable to ensure data longevity?

  • Is the technology stack constructed to be maintainable by an in-house or third-party team?

  • Will the software license allow you to modify the technology down the road?

  • To distribute the modifications to collaborators?

  • What is the contingency plan for avoiding proprietary lock-in to vendor-specific technologies?

RexStudy is built to maximize Maintainability and Data Longevity

Relational databases are the best way to organize structured data for future long-term use. They are a proven technology that should be used as the default storage model for structured data because it maximizes interoperability and data longevity. RexStudy uses a popular open-source Relational Database Management System (PostgreSQL) for data storage.

Desktop client installation should not be required to access the system: client applications should run on modern web browsers. RexStudy is a modern web application with research staff, administrative users, and data managers able to access system functions via a web browser. RexStudy uses a popular and well-supported open-source UI toolkit (Facebook’s React) for user interface construction and extensions.

Open source technologies should be used to preserve transparency, portability, and maintainability of mission-critical research systems over time. All components of the run-time environment for RexStudy are available under open source license approved by the Open Source Initiative. For more information, visit https://bitbucket.org/rexdb/rex.study

Don’t miss the first six parts of this series:

Part 1: Metadata Variety

Part 2: Schema Volatility

Part 3: Workflow Variability

Part 4: Complex Data Provenance

Part 5: Security and Privacy

Part 6: Interoperability and Data Repurposing

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