2026-08-10T05:53:17Z https://api.figshare.com/v2/oai

oai:figshare.com:article/30893798 2026-01-08T11:04:44Z category_24559 portal_549 item_type_3 month_year_01_2026

10.5522/04/30893798.v1 https://figshare.com/articles/dataset/Synthetic_Electronic_Health_Record_data_generated_at_UCLH_for_the_project_Pregnancy_Intention_and_Outcomes/30893798 https://ndownloader.figshare.com/files/60417863 https://ndownloader.figshare.com/files/60417887 https://ndownloader.figshare.com/files/60417890 https://ndownloader.figshare.com/files/60417893 https://ndownloader.figshare.com/files/60417896 https://ndownloader.figshare.com/files/60417899 https://ndownloader.figshare.com/files/60417902 https://ndownloader.figshare.com/files/60417905 Cartner, Duncan Duncan Cartner Clinical sciences not elsewhere classified Synthetic data EHR datasets OMOP-CDM 2026-01-08 2026-01-08 Dataset 2026 University College London Synthetic data generated to represent the structure of data extracted from the UCLH Electronic Health Record. They are selected tables and fields from the OMOP Common Data Model v5.4 with concept_name columns added for readability.
These synthetic data are based on the project Pregnancy Intention and Outcomes which is analysing the variation pregnancy planning based on the London Measure of Unplanned Pregnancy.
These are low fidelity synthetic data generated using datafaker. The columns are currently generated independently so any relationships between them may be nonsensical e.g. birth dates occurring after death dates.
These data are artificially generated, any resemblance to real patients is coincidental.

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