7 Challenges for Mastering Clinical Data Registries: Workflow Variability

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 #3: Workflow Variability

Each research project may have a different way of acquiring, curating, and distributing research data. Even within a research center, standardizing on a single research workflow across different projects is often infeasible. The problem is multiplied when systems need to operate across centers or sites. The ability to customize workflows to meet local research needs, providing maximum flexibility and expandability, is essential.

Two major challenges for workflow variability are:

  • Storing tens of thousands of scientific variables
  • Operational workflows with dozens of tables with hundreds of columns

Questions you should ask before building your CDR

  • What is the speed and cost of adding new studies, forms, research assets (e.g., sample types, consent types, measure annotation types), sites, reports, and data marts to existing instances?

  • Once a platform is installed, what is the speed and cost of adding a new CDR instance (to support different research groups and domains)?

  • Along what dimension does the platform anticipate being extended with additional code?

  • How much of the configuration can be done by local IT staff as opposed to vendor IT staff?

  • Is there a way for internal staff to customize workflows to adapt to local needs across sites, projects, and research domains?

  • How much configuration can be done by local research staff as opposed to IT staff?

How RexStudy is built for Flexibility and Expandability

Research operations workflows must be configurable by research staff to handle the variability across studies, sites, and research domains. RexStudy allows non-technical personnel to configure studies and instruments. It also allows data managers to configure data model additions and screens to support variations in workflows, as well as data marts and query guides to support downstream data consumers.

The ability to add new data models and screens provides essential flexibility. Being open source provides extensibility along several well-defined dimensions. Some anticipated additions include data formatters for specialized data output (e.g., SPSS, R, plink); pre- and post- processing ETL scripts; custom “actions” that serve as configurable templates for new kinds of custom screens (e.g., a specialized plot display).

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

Part 1: Metadata Variety

Part 2: Schema Volatility

If you enjoyed this article, register to receive notification of our latest posts, webinars, white papers, and more using the form at the top of our DataBytes blog page here.