Synthetic Healthcare Appointment No-Show Dataset for Predictive Modeling

A realistic synthetic dataset for predicting missed medical appointments. The dataset is hosted on Kaggle. The author, organization, and last update date are unknown.

Use Cases

• Train a binary classifier to predict appointment no-shows based on synthetic patient and appointment features.
• Benchmark machine learning algorithms for imbalanced classification tasks common in healthcare.
• Simulate healthcare scheduling scenarios for operational research without using real patient data.
• Analyze factors influencing appointment adherence using synthetic demographic and behavioral variables.

Strengths

• The dataset is described as 'realistic', suggesting careful generation for model training.
• It is designed for a specific, high-impact use case in healthcare operations.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Kaggle

Collection Method

Synthetically generated.