Data & Analytics
MedScheduler Python Library
Open-source Python library for generating realistic synthetic outpatient appointment datasets, designed for analytics, research, and teaching.
/ Overview
Practical application
Real-world healthcare scheduling data is often inaccessible due to privacy constraints or fragmentation across systems. Medscheduler addresses this by generating synthetic datasets that preserve realistic operational patterns, enabling safe experimentation, prototyping, and training.
Core features
- End-to-end scheduling simulation: Models the full appointment lifecycle, from slot creation to final attendance outcomes.
- Structured relational output : Generates three linked tables ( slots , appointments , patients ) as pandas DataFrames, ready for analysis or export
- Configurable simulation parameters :Control clinic capacity, booking behavior, attendance rates, and patient demographics
- Reproducible data generation: Deterministic outputs via seeded simulations
- Optional visualization module: Built-in plotting utilities for exploratory analysis and reporting
PROJECT IN DETAIL