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README.md
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path: data_subset.csv
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---
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# POU
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path: data_subset.csv
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---
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# OMOP POU Data Card
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----------------------------------
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## Publication
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Naderalvojoud, Behzad, et al.
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"Towards global model generalizability: independent cross-site feature evaluation for patient-level risk prediction models using the OHDSI network."
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*Journal of the American Medical Informatics Association* 31.5 (2024): 1051–1061.
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Please refer to the publication for full details on cohort construction and model development.
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---
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## Dataset Specification
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- **Source of Data**: STARR OMOP
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- **Prediction outcome**: Prolonged opioid use
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- 1: Prolonged
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- 0: Non-prolonged
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- **Covariate count**: 10,636
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- **Total cohort size (original)**: 41,929 patients
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- **Final modeling cohort**: 41,507 patients
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- **Training set size**: 33,206
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- **Test set size**: 8,301
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---
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## Note on Data Availability
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Due to PHI restrictions, the full dataset cannot be publicly released. The files provided here are **small subset examples with synthetic patients**, intended only to demonstrate the **structure and format** of the dataset.
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---
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## File Descriptions
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### `cohort_subset.csv`
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Contains 10 example (synthetic) patients with:
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- `rowId`: patient identifier
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- `outcome`: prolonged opioid use label
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---
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### `data_subset.csv`
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Represents the model input matrix:
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- Each row corresponds to a patient
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- Each column corresponds to a covariate (by covariateId)
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- `rowId` links to `cohort_subset.csv`
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---
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### `covariate_subset.csv`
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Covariate dictionary containing:
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- `covariateId`
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- `covariateName`
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---
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## Support
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Please contact Dr. Behzad Naderalvojoud at behzadn@stanford.edu for any questions or clarifications regarding this dataset.
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