RubyIntelligence/fda-warning-letter-escalation

FDA Warning Letter Escalation Dataset

Version: 1.0.0 | Records: 14,810 | Price: $2,000 | Source: FDA (public domain)

Dataset Summary

The dataset's core signal — whether an inspection escalated to a Warning Letter — is validated against FDA's own severity classifications: OAI inspections escalate at 64% versus 1.7% for NAI, a 39× relationship that confirms the data reflects real regulatory behavior.

The 14,810 inspections that escalated to enforcement — every inspection followed by a Warning Letter, Injunction, or Seizure — with full citation context and exact timing (days from inspection to action, and 90/180/365-day windows). Pure signal: the dataset of what FDA findings actually precede enforcement. Built for RA/QA risk modelling and enforcement-pattern analysis.

Current through 2026 — the dataset includes FDA inspections from the most recent regulatory cycles (covering 5,713 facilities inspected in 2026 and 14,845 in 2025), not a historical snapshot. Quarterly refreshes keep it current.

What This Replaces

Comparable facility-level FDA regulatory intelligence from incumbent enterprise platforms requires annual contracts and enterprise procurement. This dataset delivers the same enforcement-escalation intelligence as a one-time, analysis-ready download — no contract, no seat licenses, no platform lock-in.

Source

All data derives from U.S. FDA public records:

• FDA Data Dashboard API — inspections, inspection citations, inspection classifications, compliance actions (Warning Letters / Injunctions / Seizures), and import refusals.
• openFDA — 510(k) device clearances, establishment registrations, device & drug recall enforcement reports, and device classification.
• All sources are U.S. Government works in the public domain (CC0). No PII is included (no patient, reporter, or individual-inspector identities).

The Premium Fields

The premium fields are the escalation linkage — computed by matching each inspection to the nearest subsequent enforcement action at the same facility:

• days_inspection_to_warning_letter — exact day gap from the inspection's end to the nearest subsequent Warning Letter / Injunction / Seizure. Always positive (directionality enforced); null if no action followed. The raw day count is provided so you can set your own thresholds.
• escalated_within_90d / _180d / _365d / escalated_ever — convenience booleans derived from the day gap.
• escalated_warning_letter_action_type — which action followed (Warning Letter, Injunction, or Seizure), so you can restrict to Warning-Letter-only escalation if you wish.
• citation_count / cfr_codes_cited / citation_descriptions — the inspection's full citation context, so the finding and its consequence sit in one row.

Methodology

• Entity resolution. Records are joined on the FDA FEINumber (Facility Establishment Identifier), normalized to a trimmed string across every source. 510(k) clearances and import refusals carry an FEI directly.

• Escalation matching. For each inspection, the dataset finds compliance actions at the same FEI whose action date is strictly after the inspection end date, and keeps the nearest one (smallest positive day gap). Directionality is enforced in the join itself, so a Warning Letter that predates an inspection can never be counted as escalation. Escalation actions are Warning Letters (the canonical case) plus the stronger judicial actions Injunction and Seizure; the action type is retained so you can restrict to Warning-Letter-only.

• Risk score. Computed from each facility's history with a published formula:

  facility_risk_score = min(100,
      oai_count                              × 15
    + warning_letter_count                   × 20
    + recall_count                           × 10
    + min(import_refusal_count × 2, 20)           (import-refusal contribution capped at 20)
    + (repeat_citation_flag ? 10 : 0)
    + (most_recent_classification == OAI ? 15 : 0)
    + recency_factor)
  
  recency_factor (awarded only when the most recent inspection outcome was OAI or VAI):
    +10 if that inspection was within 1 year, +5 if within 3 years, +2 if within 5 years
    (evaluated as of the 2026-06-23 build date)
  

• Recall attribution. Recall enforcement reports carry no FEI, so recalls are matched to facilities by normalized firm name (uppercased, punctuation and common legal suffixes removed). The match is deliberately restricted to unambiguous 1:1 names — a normalized name owned by exactly one facility — to prevent a multi-site chain's recalls from being falsely attributed to every location that shares its name.

Validation

• Escalation signal validated. OAI (Official Action Indicated) inspections escalate to Warning Letters at 64% versus 1.7% for NAI (No Action Indicated) inspections — a monotone, ~39× relationship confirming the computed escalation fields correlate correctly with inspection severity. (If escalation were a join artifact, NAI and OAI would escalate at similar rates.)
• Directionality enforced. Zero inspections have a negative inspection→action day gap; every Warning Letter counted as escalation post-dates its inspection.
• No orphaned escalations. Every recorded escalation action type exists in the source compliance-action data.
• Recall attribution restricted to unambiguous 1:1 facility-name matches to prevent false attribution (see Methodology).
• Completeness. Row counts reconcile exactly to the validated master tables.

Known Limitations

• Citation coverage. Inspection citations cover electronically generated, finalized inspections; some manually prepared Form 483s are not present in the FDA citations dataset.
• Recall attribution (~35%). Only recalls with an unambiguous 1:1 firm-name match are attributed; multi-site chains that share a normalized name are deliberately excluded to avoid false attribution, so recall counts are conservative (under- rather than over-counted).
• Inspector-level detail not included. The FDA citations API does not expose individual inspector identity, so inspector-level fields are out of scope for this version.
• Risk score is a heuristic. facility_risk_score is a transparent composite indicator, not an official FDA designation or prediction. All underlying counts are included so you can recompute it with your own weights.
• Warning Letter coverage. Warning Letters are attributed to facilities that appear in the inspection record; Warning Letters issued to firms without an inspection in the dataset are not rolled into a facility row.
• Escalation timing always populated here. Because this dataset is filtered to inspections that escalated, days_inspection_to_warning_letter and escalated_warning_letter_action_type are populated on every row. In the full inspection dataset these fields are null by design for the large majority of inspections that never escalate, reflecting that most FDA inspections do not lead to enforcement.
• Null-by-design citation context. The citation fields (citation_count, cfr_codes_cited, citation_descriptions) can be empty/null for escalated inspections with no posted citations on record. This is accurate — some inspections result in enforcement without posted 483 citations, and many inspections classified NAI carry no citations at all. The posted_citations flag is included so this is transparent.

Field Definitions

Field	Type	Description
fei_number	string	FDA Facility Establishment Identifier (FEI) of the inspected facility.
inspection_id	string	FDA Data Dashboard inspection identifier (not unique per row — an inspection may span multiple product/program rows).
legal_name	string	Inspected facility legal name.
inspection_end_date	date	Date the inspection ended.
fiscal_year	string	FDA fiscal year of the inspection.
classification	string	Inspection outcome classification (full text).
classification_code	string	Inspection outcome code: NAI (No Action), VAI (Voluntary Action), OAI (Official Action).
project_area	string	FDA project area for the inspection.
product_type	string	Product area covered by this inspection row (Drugs, Devices, Foods, etc.).
posted_citations	string	FDA flag indicating whether citations were posted for this inspection.
city	string	Facility city.
state	string	Facility state/province.
state_code	string	Facility state code.
country	string	Facility country.
firm_profile	string	URL to the facility's FDA FirmProfile page.
citation_count	integer	Number of citations (483 observations) recorded for this inspection.
cfr_codes_cited	list	Distinct CFR codes cited in this inspection.
citation_descriptions	list	Short descriptions of the citations issued in this inspection.
days_inspection_to_warning_letter	integer	Days from this inspection's end to the NEAREST subsequent escalation action at the same facility (Warning Letter / Injunction / Seizure). Populated on every row in this escalation-filtered dataset (null by design only in the full inspection dataset, when no escalation followed). Always positive — directionality is enforced (the action must post-date the inspection).
escalated_warning_letter_action_type	string	ActionType of the nearest subsequent escalation (Warning Letter, Injunction, or Seizure); populated on every row in this escalation-filtered dataset.
escalated_within_90d	boolean	True if an escalation action followed within 90 days of the inspection.
escalated_within_180d	boolean	True if an escalation action followed within 180 days.
escalated_within_365d	boolean	True if an escalation action followed within 365 days.
escalated_ever	boolean	True if an escalation action followed at any time after the inspection.

Update Cadence

Quarterly, tracking FDA Data Dashboard refreshes.

License

Derived entirely from U.S. federal government public records (FDA Data Dashboard, openFDA), which are in the public domain. This structured, enriched version is provided under CC BY 4.0 — attribution required.

How to Access the Full Dataset

Full dataset available at Ruby Intelligence on Gumroad.