Synthetic EHR data is artificially generated health-record data designed to reproduce selected structures and patterns found in electronic health records without directly copying real patient records. It may include simulated diagnoses, medications, laboratory results, encounters, procedures, and timelines. Some datasets are exported in healthcare formats such as FHIR or C-CDA so developers and researchers can test systems that expect structured clinical records.
For example, a development team might use synthetic patient histories to test whether an application correctly handles a sequence of visits and prescriptions without placing real patient records in the test environment. Synthetic EHR data is a specialized form of synthetic data, but the label does not guarantee privacy, clinical accuracy, or fitness for a particular task. Those properties depend on the generation method, source data, validation process, and intended use. Teams should evaluate whether the dataset preserves the relationships and distributions relevant to their work while avoiding unsupported conclusions about real patients or clinical outcomes.