7 Informatics Challenges for Mastering Clinical Data Registries: Schema Volatility

This series outlines the Seven Informatics Challenges for Clinical Data Registries (CDRs), 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 #2: Schema Volatility 

Here volatility refers to both instrument and operational schemas change over time, e.g., new instruments are added, old instruments are modified, or operational processes evolve. This challenge is especially acute in multidisciplinary behavioral and mental health research, where columns can be in the tens of thousands, new data models for experimental measures can require many related tables, and models change in the course of a typical project. Of critical importance is to consider how the registry system will evolve and adapt to the metadata changes. 

Questions you should ask before building your CDR

  • What mechanisms will be available in the system to allow users to handle high levels of volatility when data models evolve rapidly with new variables, tables, and relationships added over time

  • Does the system provide a clear strategy for versioning of data collection instruments and for combining data across versions

  • Does the system provide a clear strategy for versioning of study protocols and for linking research results to specific versions

RexStudy is designed to address Variety and Volatility

Instrument definitions must be configurable by local research staff to support the high levels of metadata variety and volatility found in research systems and must include a systematic approach to instrument versioning and to data merging across versions. RexStudy uses the research instrument open standard (RIOS) definition model and supports versioning of both instruments and study protocols. Instrument versions are automatically merged into database tables for analysis when constructing data marts. Further, RexStudy provides a declarative, idempotent mechanism for extending the relational schema, allowing the CDR to add new complex data types.

Don’t miss the first part of this series:

Part 1: Metadata Variety