Datasets:

YPL67
/

POU

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

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