The FDA outlines a three-phase life cycle for data from electronic health records (EHRs): data accrual, curation, and transformation. This means gathering, processing, and preparing data for analysis. In its guidance titled “Real-World Data: Assessing Electronic Health Records and Medical Claims Data To Support Regulatory Decision-Making for Drug and Biological Products,” the FDA emphasizes the importance of maintaining data quality and reliability at each phase.
Curation is crucial. It involves cleaning data, fixing errors, and ensuring that information can be easily shared and understood. This process aims to keep the original clinical meaning intact while making data usable for analysis. However, various data managers—from hospitals to researchers—often have different methods for curating data. This lack of standardization can create challenges, making it harder for regulators to evaluate the data’s utility for drug approvals and safety assessments.
A recent analysis highlighted that effective data curation could significantly impact patient outcomes. For instance, a study found that well-curated real-world data can identify drug side effects that controlled trials might miss, because they focus on more limited populations. In fact, nearly 80% of healthcare professionals believe that better data curation will improve patient safety.
Experts warn that without consistent protocols, the credibility of EHR-sourced data suffers. There is currently no agreement among data holders on how to align their practices with FDA guidelines. This inconsistency could reduce the regulatory impact and hinder the ability to monitor health outcomes effectively.
To address these issues, we explore three key areas for refining EHR data curation:
- Clear Definitions: Establishing a common understanding of what curation entails can help unify practices across sectors.
- Real-World Best Practices: Implementing proven techniques, such as standardized processes and documentation, can enhance transparency in data handling.
- Embracing Technology: Incorporating artificial intelligence in data curation can streamline processes, but experts stress the need for robust guidelines to ensure reliability and ethical use.
As AI tools enter the health sector, they must be integrated thoughtfully to address emerging regulatory concerns. Experts agree that collaboration across disciplines is vital to improving curation methods and ensuring that EHR data remains a reliable resource for healthcare decision-making.
For a deeper dive into these topics, check out the FDA’s guidance here.
