Augment Patient Level Prediction (PLP) to expose the differences of predictions, predictive power, and other fairness metrics of the predictive models it creates.

OHDSI / HealthEquityWG

We aim to engage critically and intentionally in all of our work, considering not only the results but the potential interpretation and impact of results, steering clear of work that reinforces health disparities and misinterpretations that generate stigma, and lifting up work which is likely to contribute to health equity.

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Augment Patient Level Prediction (PLP) to expose the differences of predictions, predictive power, and other fairness metrics of the predictive models it creates. #10

Open Jake-Gillberg opened 2 years ago

Jake-Gillberg commented 2 years ago

Ross Williams is working on PLP augmentation for automatic sub-group analyses based on customizable cohort definitions.

Juan Banda had a poster and talk at the OHDSI Symposium titled: Leveraging APHRODITE to identify bias in statistical phenotyping algorithms

Will discuss these works further on the 10/19 health equity workgroup meeting