Datasets:

YPL67
/

POU

@@ -1,62 +1,22 @@
-# OMOP POU Data Card
-----------------------------------
-## Publication
-Naderalvojoud, Behzad, et al.
-"Towards global model generalizability: independent cross-site feature evaluation for patient-level risk prediction models using the OHDSI network."
-*Journal of the American Medical Informatics Association* 31.5 (2024): 1051–1061.
-Please refer to the publication for full details on cohort construction and model development.
----
-## Dataset Specification
-- **Source of Data**: STARR OMOP
-- **Prediction outcome**: Prolonged opioid use
-  - 1: Prolonged
-  - 0: Non-prolonged
-- **Covariate count**: 10,636
-- **Total cohort size (original)**: 41,929 patients
-- **Final modeling cohort**: 41,507 patients
-- **Training set size**: 33,206
-- **Test set size**: 8,301
 ---
-## Note on Data Availability
-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.
----
-## File Descriptions
-### `cohort_subset.csv`
-Contains 10 example (synthetic) patients with:
-- `rowId`: patient identifier
-- `outcome`: prolonged opioid use label
-### `data_subset.csv`
-Represents the model input matrix:
-- Each row corresponds to a patient
-- Each column corresponds to a covariate (by covariateId)
-- `rowId` links to `cohort_subset.csv`
-### `covariate_subset.csv`
-Covariate dictionary containing:
-- `covariateId`
-- `covariateName`
 ---
-## Support
-Please contact Dr. Behzad Naderalvojoud at behzadn@stanford.edu for any questions or clarifications regarding this dataset.

 ---
+configs:
+- config_name: cohort
+  data_files:
+  - split: train
+    path: cohort_subset.csv
+- config_name: covariates
+  data_files:
+  - split: train
+    path: covariate_subset.csv
+- config_name: data
+  data_files:
+  - split: train
+    path: data_subset.csv
 ---
+# POU
+Three separate CSV tables:
+- cohort
+- covariates
+- data