DenialIQ: 120K Synthetic Medical Claims with X12 Denial Codes

120,000 synthetic medical claims with associated X12 denial codes, appeal labels, and payer rules for revenue cycle management. The dataset is hosted on Kaggle, but its author, organization, and creation date are unknown. The data is synthetic, meaning it was artificially generated rather than collected from real patient records.

Use Cases

• Train models to predict claim denials based on X12 denial codes and payer rules mentioned in the description.
• Develop classifiers for appeal success likelihood using the provided appeal labels.
• Analyze patterns in payer rules to optimize revenue cycle management workflows.
• Benchmark synthetic data generation techniques for healthcare financial data.

Strengths

• Contains 120,000 synthetic claim records, providing a substantial volume for model training.
• Includes multiple structured features relevant to RCM: X12 denial codes, appeal labels, and payer rules.

Limitations

• Data is synthetic, which may limit its realism and applicability to real-world claim processing systems.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

Kaggle

Collection Method

Synthetically generated