Clustered 2 filings across 2 jurisdictions · filing window May 13, 2016 → May 17, 2016. View entity profile → Other incidents for this victim →
incident inc_1c1fd42ea1c54f01 · merge_method deterministic · confidence 100%
Time between earliest and latest filing
Not recorded for this incident
Discovery variance · Leak precedence · Materiality delta · SEC filing delay — no leak-site claim in this cluster; no SEC 8-K in this cluster; needs two dated filings.
Health (basic) · Identity (basic)
MT NM
HHS OCR · State AG
Earliest sighting first · deep chronology in Litigation Timeline
Mar 18, 2016
When the intrusion reportedly occurred, per the linked filings
San Juan County, New Mexico reported a data breach to the Montana Attorney General. The breach was reported on 2016-05-13. The breach occurred on 3/18/2016. 2 Montana residents were affected.
Affected (this filing): 2
San Juan County New Mexico (a Healthcare Provider/government entity in NM) reported to HHS OCR on 2016-05-17 a Hacking/IT Incident affecting approximately 12,500 individuals. An unauthorized user obtained remote access to a workstation. PHI exposed included names, addresses, health assessments, and clinical information. The CE improved safeguards, updated policies and procedures, offered free credit monitoring, and notified HHS, affected individuals, and media. OCR obtained assurances of corrective action implementation.
Affected (this filing): 12,500
About this clustering
DisclosureLens links filings into incidents through layered matchers: deterministic rules (same source document, multistate filings of one breach, tight-window same-victim pairs), a weighted-similarity scorer for cross-source candidates, and an operator review queue for everything uncertain. Each link records its own method and confidence — shown per filing in the timeline below. The system defaults to NOT merging when uncertain, because a false merge (collapsing two unrelated breaches) is more harmful than a false split (showing related filings separately); uncertain pairs route to human review instead of auto-merging. Filing summaries shown in the timeline are AI-generated extracts — verify each against its linked source.