Real-World Data: FDA's final Guidance on the Use of eHRs in Clinical Studies

The U.S. Food and Drug Administration (FDA) has published the final guidance on Real-World Data (RWD) as part of its Real-World Evidence (RWE) program. The guidance is intended to provide sponsors and other interested parties with information on the use electronic health records (eHRs) or medical claims data in clinical studies to support a regulatory decision for effectiveness or safety. The document finalizes the draft guidance of the same title issued in September 2021.

Real-World Data Sources and AI

Examples of RWD include data derived from:

  • eHRs,
  • Medical claims data,
  • Data from product and disease registries,
  • Patient-generated data including from in-home use settings,
  • Data gathered from other sources that can inform on health status, such as digital health technologies.

EHRs and medical claims data are types of electronic health care data that contain patient health information, and these data are widely used in safety studies and increasingly being proposed for use in effectiveness studies. EHRs and medical claims data can be considered as data sources in various clinical study designs.

Technological advances in the field of artificial intelligence (AI) may permit more rapid processing of unstructured electronic health care data. Advances include natural language processing, machine learning, and particularly deep learning to:

  • Extract data elements from unstructured text in eHRs;
  • Develop computer algorithms that identify outcomes;
  • Evaluate images or laboratory results.

If the protocol proposes to use AI or other derivation methods, the protocol should specify the assumptions and parameters of the computer algorithms used, the data source from which the information was used to build the algorithm, whether the algorithm was supervised (i.e., using input and review by experts) or unsupervised, and the metrics associated with validation of the methods.

More information is available in FDA's guidance on Real-World Data: Assessing Electronic Health Records and Medical Claims Data To Support Regulatory Decision-Making for Drug and Biological Products.

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