HHS-OIG Corporate Integrity Agreements (CIA)

What it is

1. 1A directory of every U.S. healthcare entity currently (as of the snapshot) under an active HHS-OIG Corporate Integrity Agreement (CIA) — the compliance contracts OIG imposes after a False Claims Act / fraud settlement — scraped from the OIG "browse CIAs" web page.
2. 2Each row is one entity with its OIG detail-page URL, location, CIA effective date, and the associated civil settlement amount (when OIG discloses one).
3. 3It lives in drug_silver because the largest CIAs are drug-pricing / kickback / pharmacy-distribution fraud (AmerisourceBergen $625M, Novartis $591M, Mylan $465M, Rite Aid $409M), making it the enforcement/integrity context layer for the drug-cost substrate.

Grain

How to read it

1. 1List the largest active HHS-OIG Corporate Integrity Agreements and their settlement amounts: SELECT entity_name, location_state, settlement_amount_usd, effective_date FROM drug_silver.dim_hhs_oig_cia WHERE is_current=true AND settlement_amount_usd IS NOT NULL ORDER BY settlement_amount_usd DESC LIMIT 20; — answers "which healthcare/pharma entities are currently under an OIG integrity agreement and how big was the settlement that triggered it" (top results: AmerisourceBergen $625M, Novartis $591M, Mylan $465M, Rite Aid $409M).

Traps

1. 1Always filter is_current=true. The table holds 704 rows across 2 snapshots; the older vintage_tag='hhs_oig_cia_2026-05-16' (is_current=false, 372 rows) is a DIRTY pre-dedup load where ~40 entity_slugs repeat 3x (same slug, 3 different sha256_content_hash, NULL bronze_object_key/s3_version_id). entity_slug is unique ONLY on the current snapshot (332 = 332).
2. 2settlement_amount_usd is NULL for 12 of 332 entities (and location_state NULL for 2). NULL means OIG published no settlement figure, NOT $0 — exclude nulls (or COUNT them separately) before SUM/AVG. Computed stats: min $31,818, max $625M, median ~$5.5M over the 320 with amounts.
3. 3entity_name is a raw OIG concatenation: 33 rows pack multiple co-signing legal entities into one string (semicolons / 120+ chars). One CIA row can represent a whole corporate family — do not parse entity_name as a single clean company; use entity_slug/detail_url as the identifier.
4. 4Three column pairs are effectively redundant or constant: effective_date == effective_period_start on every row; effective_period_end is ALWAYS the sentinel 2099-12-31 (open/active, not a real end date); observed_period == asserted_at == 2026-05-19 (the scrape date). The 'monthly' periodicity the profiler infers from effective_date is just CIA signing dates, not a refresh cadence.
5. 5This is OIG Corporate Integrity Agreement / fraud-enforcement data, NOT a price/rate table — settlement_amount_usd is a one-time fraud-settlement penalty, not a healthcare cost or drug price. It belongs in the drug substrate because the headline CIAs are drug/pharmacy fraud (AmerisourceBergen, Novartis, Mylan, Rite Aid). Join to drug/provider entities by NAME ONLY — there is no NPI/NDC/EIN key, and drug_source_version_id is null for every row.
6. 6lineage columns source_id, source_url, sha256_content_hash, s3_version_id, bronze_object_key, parser_artifact_hash, vintage_tag, cms_vintage_sequence, parse_revision are all SINGLE-VALUED on the current snapshot (one scraped corpus file -> all 332 rows), so none of them is a usable grain/key; only entity_slug (or detail_url) distinguishes rows.

Columns (22)

Query it

describe_data_source(source_fqn="drug_silver.dim_hhs_oig_cia")     # the card, live
query_substrate(sql="SELECT * FROM drug_silver.dim_hhs_oig_cia WHERE entity_slug = '<value>' LIMIT 100")