Predicting Patient Stay Durations in the ER with Safe Synthetic Data

A major hospital system used Gretel, an AI platform, to generate synthetic medical data for forecasting staffing and resource needs in their emergency care unit and identifying emerging trends in outbreaks. Synthetic data offers several advantages over traditional approaches to maintaining data privacy, including provable anonymity, portability and shareability, and flexibility for exploratory data analysis. The hospital used Gretel's synthetic data models to create artificial versions of their training data with various levels of privacy protections. Comparing the performance of a model trained on synthetic data versus real-world data showed that synthetic data created by Gretel ACTGAN outperformed real world data in predicting the length of a patient's emergency room stay based on their initial diagnosis.

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