oig-leie

A small, dependency-free Python client for screening against the public OIG LEIE (List of Excluded Individuals/Entities), the federal database of people and organizations excluded from Medicare, Medicaid, and all other federal healthcare programs.

What the LEIE is

The LEIE is published monthly by the U.S. Department of Health and Human Services, Office of Inspector General (OIG), as a downloadable CSV. Each row describes one excluded individual or entity. The official download page is:

https://oig.hhs.gov/exclusions/exclusions_list.asp

Related MCP server: mcp-sanctions-screening

Why it matters

Screening against the LEIE is a mandatory part of healthcare credentialing and provider enrollment. Federal healthcare programs do not pay for items or services furnished, ordered, or prescribed by an excluded individual or entity, and employing or contracting with an excluded party can expose an organization to civil monetary penalties. Most compliance programs check the LEIE on hire and on a recurring basis (commonly monthly) for staff, contractors, and vendors.

The human-verification caveat (read this first)

A name match, or even an NPI match, against the LEIE is not a confirmed exclusion. OIG requires verifying a potential match using additional identifiers such as a Social Security Number, date of birth, or other identifying data before any adverse action is taken.

This library reflects that posture deliberately. Lookups return possible matches that a human must verify. The library never returns a definitive "excluded = true" verdict. Sources surface candidates. A human makes the decision.

Install

pip install oig-leie

Optional MCP server support:

pip install "oig-leie[mcp]"

The core library has no runtime dependencies.

Usage

First, download the monthly LEIE CSV from the official page above and save it locally (for example as leie.csv). Then load it and run lookups.

from oig_leie import LeieClient

client = LeieClient.from_csv("leie.csv")

# Individual lookup by last name (first name optional, matched as a prefix).
possible = client.check_individual("Sampleton", "Roberta")
for record in possible:
    print(record.display_name, record.excltype, record.excldate)

# Business / entity lookup (case-insensitive, partial match).
client.check_business("home health")

# NPI lookup (only digits are compared, so formatting does not matter).
client.check_npi("1234567893")

Every returned item is a frozen Exclusion dataclass holding the raw CSV fields (lastname, firstname, midname, busname, general, specialty, npi, upin, dob, address fields, excltype, excldate, reindate, waiverdate, and more). Remember: a returned record is a candidate to verify, not a confirmed exclusion.

You can also load from an open file object or from a string:

with open("leie.csv", encoding="utf-8-sig") as fh:
    client = LeieClient.from_fileobj(fh)

client = LeieClient.from_string(csv_text)

Refreshing the local file (optional)

A helper is provided for callers who want to fetch the monthly CSV programmatically. It performs a real network request, so it is never called by the test suite or during normal use. Pass the official monthly CSV URL.

from oig_leie import download

download("https://oig.hhs.gov/exclusions/downloadables/UPDATED.csv", "leie.csv")

MCP server

With the mcp extra installed, the package ships an optional Model Context Protocol server exposing a single check_exclusion tool. Point it at a local LEIE CSV via the OIG_LEIE_CSV environment variable.

OIG_LEIE_CSV=/path/to/leie.csv oig-leie-mcp

Example MCP client configuration:

{
  "mcpServers": {
    "oig-leie": {
      "command": "oig-leie-mcp",
      "env": { "OIG_LEIE_CSV": "/path/to/leie.csv" }
    }
  }
}

The check_exclusion tool accepts last_name, first_name, and npi, and returns candidate matches plus an explicit requires_human_verification flag and disclaimer. It does not confirm exclusion.

Development

python -m venv .venv
. .venv/bin/activate        # Windows: .venv\Scripts\activate
pip install -e ".[dev]"
pytest -v

The test suite uses a small synthetic fixture CSV with made-up names and makes no network calls.

License

MIT. Copyright (c) 2026 Giles-Evan Mboumi. See LICENSE.

Disclaimer

This project is not affiliated with or endorsed by the HHS Office of Inspector General. It is a convenience client over publicly published data. Always follow OIG guidance and your own compliance program when screening and verifying matches.