Objectives

Clinical decision-making and outcome research in Oncology requires timely access to fit-for-purpose, real-world data (RWD). RWD assessment frameworks for secondary use of healthcare data therefore need to include dimensions that evaluate data quality using fit-for-purpose evaluation criteria. This conceptual paper describes the Use-case specific Relevance and Quality Assessment (‘UReQA’, pronounced as ‘Eureka’) framework and its implementation for outcomes studies that estimate real-world Time to Treatment Discontinuation (TTD).

Methods

The UReQA framework consists of five interlinked, iterative process steps –

1. Pre-assessment to screen commercialized RWD sources on population coverage, timeliness, and use case experience
2. Data Elements Evaluation based on study-specific data elements and review of business rules specification
3. Cohort Identification to ensure a reasonably sized, viable cohort for the specific study
4. Verification to ensure internal validity of patient-level data elements of interest
5. Validation to examine external validity using metrics for longitudinality, conformity, plausibility and completeness

Various steps in the UReQA framework were applied to 10 large, commercial Oncology EHR cohorts in the US.

Results

UReQA framework implementation revealed important quality issues in RWD sources, with varied levels of potential impact on estimation of TTD. Data element evaluation revealed ambiguous coding of medication date for oral therapies. Internal validity checks revealed ambiguous biomarker results and testing dates. External validity checks revealed lower than expected drug exposure rates and mortality events.

Conclusion

The UReQA framework provides a mechanism for systematic examination of RWD sources to identify fit-for-purpose RWD for specific outcomes research needs. Framework implementation may enable improved cross-stakeholder collaboration to improve the quality and reliability of real-world data.