Persius/hicric

HICRIC: A Dataset of Law, Policy, and Regulatory Guidance for Health Insurance Coverage Understanding

Health Insurance Coverage Rules Interpretation Corpus is a collection of unannotated text curated to support applications that require understanding of U.S. health insurance coverage rules.

It consists of a small, unlabeled corpus of authoritative and non-authoritative text related to law, insurance contracts, and medicine. The corpus is intended for use in pretraining language models and, independently, for use as a standalone knowledge base in retrieval pipelines.

This data repository houses the processed, unlabeled data referenced in a more general work documented here: https://github.com/TPAFS/hicric.

Redistribution

Please consult the licenses for all source data for yourself if you plan to redistribute any of it. To the best of our knowledge, our redistributions abide by all such licenses.

Risks

We believe there are numerous risks associated with our released data, which we've done our best to mitigate. Our main concerns involve:

• Potential for Propagation of Bias
• Potential for Misuse

Please see our forthcoming paper for a thorough discussion of these perceived risks.

Limitations

There are many limitations associated with our released data, and our advice is to consider and weigh these limitations carefully to inform resonsible and effective use. The main categories of limitation are:

• Task Shortcomings
• Simplicity of the Benchmark
• Corpus Deficiencies

Please see our forthcoming paper for a thorough discussion of these perceived risks.

Dataset Breakdown

Each document in our dataset comes equipped with a set of plain-text tags. In constructing the data we formulated a particular privileged set of partitioning tags: these are a set of tags with the property that each document in the dataset is associated with exactly one tag in the set, and none of the tags are unused.

The tags are the following:

• legal

• regulatory-guidance

• contract-coverage-rule-medical-policy

• opinion-policy-summary

• case-description

• clinical-guidelines

In addition to this set of partitioning tags, we intoduce another privileged tag:

• kb This tag indicates that a document is suitable for use in a knowledge base.

  This is a subjective determination, but the intent is to label text that comes from a reputable, definitive source. For example, a summary of Medicaid rules as stated by an employee of HHS during congressional testimony would not be labeled with the kb tag, because such testimony is not the definitive source for the ground truth of such rules. On the other hand, federal law describing those same rules would be labeled with the kb tag.

A high level characterization of the distribution of text in our corpus in terms of these privileged tags is shown in the table below.

Category	Num Documents	Words	Chars	Size (GB)
All Partition Parts	8,310	417,617,646	2,699,256,987	2.81
kb	1,434	170,717,368	1,120,961,295	1.13
legal	335	92,357,802	596,044,008	0.60
regulatory-guidance	1,110	5,536,585	38,607,587	0.04
contract-coverage-rule-medical-policy	7	196,156,813	1,228,184,524	1.31
opinion-policy-summary	2,094	19,462,399	133,049,956	0.14
case-description	2,629	214,267,074	1,351,074,791	1.45
clinical-guidelines	2,150	81,955,020	553,041,990	0.56

Contact

For questions or comments, please reach out to info@persius.org.