Enriching Real-World Data for deeper insights

Executive summary

Real-world data (RWD) is only as valuable as the context surrounding it. While raw RWD is often fragmented or inconsistent, enriching it through linkage, validation, contextualization, and patient-reported insights transforms it into high-quality evidence that supports clinical research and precision medicine. At BC Platforms, we believe enriched RWD is essential to understanding patient journeys, improving data reliability, and enabling more informed decisions across healthcare and life sciences.

Key insights

• RWD enrichment adds context and quality by linking datasets, validating information, and integrating clinical notes, imaging, etc.
• Multi-dimensional data reveals a truer patient picture, enabling more accurate research insights and clinical decisions.
• Advanced techniques such as NLP and external data linkage help transform unstructured and incomplete RWD into actionable evidence.
• Enriched RWD is foundational to precision medicine, improving predictions, personalizing care, and supporting regulatory-grade evidence.
• BC Platforms enables this transformation, unifying multimodal data securely and compliantly to generate meaningful, high-value insights.

What is RWD enrichment?

It is the process of augmenting raw RWD with additional data points to make it more meaningful, accurate and multi-dimensional. Some key enrichment techniques include:

• Linking data sets – Connecting distinct RWD sets, like clinical data with genomics data from the same patients provides a 360-degree view. One study linked molecular data to clinical outcomes data in ovarian cancer patients. [1]
• Adding clinical context – Incorporating free text clinician notes, pathology reports and radiology images better contextualizes cryptic ICD codes or laboratory values. Startups like Ocular Science are using NLP to extract insights from unstructured clinical notes. [2]
• Validating data – Cross-checking the accuracy of RWD against the source via methods like chart review. Researchers performed validation on data extracted from hematology-oncology EHRs to fix inaccuracies. [3] 
• Supplementing with patient-reported outcomes – Integrating PROs collected via surveys and wearables with clinical data captures the patient perspective on outcomes like quality of life. [4]
• Enhancing with external data – Matching RWD with contextual data like social determinants of health from other sources, provides a holistic view of patients’ environments. [5]

Enrichment helps make RWD more multi-dimensional, meaningful, and actionable. It provides a more holistic view of patients by connecting disparate data sources and adding critical context beyond what is captured in the raw data. Our view is that enriched RWD better informs clinical and research decisions, improves care quality, and ultimately leads to better health outcomes. Thoughtful curation and enrichment helps realize the full value of RWD for advancing healthcare and precision medicine.

References

1. JCO Precision Oncology, 2022
2. Medium, 2022 
3. JAMIA, 2022
4. Frontiers in Oncology, 2022
5. Applied Clinical Informatics, 2022