DBbun/100K_Cerebral_Palsy_v1.0

Synthetic ROCS Dataset (100K Patients)

Overview

This dataset is a fully synthetic reproduction of the patient cohort described in A Big Data Approach to Evaluate Receipt of Optimal Care in Childhood Cerebral Palsy.

It simulates the Receipt of Optimal Care Score (ROCS) framework across 100K synthetic patients, modeling event sequences, adherence probabilities, and component-level quality-of-care scores.

All data were algorithmically generated — no real patient data are included.

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Motivation

The purpose of this dataset is to provide a privacy-free reference cohort for:

• Testing analytic pipelines on pediatric rehabilitation data,
• Practicing longitudinal cohort analysis (PM&R, PT, OT, Spasticity management),
• Teaching or demonstrating real-world evidence (RWE) methodologies,
• Benchmarking ROCS-style scoring frameworks.

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Files

File	Description
patients.csv	Patient-level attributes (sex, race, ethnicity, GMFCS, phenotype, spasticity flags, and ROCS summary scores).
events.csv	Longitudinal event records for PMR, PT, OT, and Spasticity components; each row = one care event.
scores.csv	Component-level and adjusted ROCS scores per patient.

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Reference

Mitelpunkt A, Stodola MA, Vargus-Adams J, Kurowski BG, Greve K, Bhatnagar S, Aronow B, Zahner J, Bailes AF. A big data approach to evaluate receipt of optimal care in childhood cerebral palsy. Disabil Rehabil. 2024 Feb;46(4):723-730. doi: 10.1080/09638288.2023.2175919. Epub 2023 Feb 8. PMID: 36755522; PMCID: PMC10406971.

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