Clustered 2 filings across 2 jurisdictions · filing window Aug 31, 2016 → Sep 1, 2016. View entity profile → Other incidents for this victim →
incident inc_ffbeb78551e945e6 · merge_method deterministic · confidence 100%
Discovered → first regulatory filing
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.
MT WA
HHS OCR · State AG
Earliest sighting first · deep chronology in Litigation Timeline
Apr 21, 2016
When the intrusion reportedly occurred, per the linked filings
Jun 13, 2016
Reported by HHS OCR filing
CHI Franciscan Healthcare Highline Medical Center (R-C Healthcare Management) reported a data breach to the Montana Attorney General. The breach was reported on 2016-08-31. The breach occurred from 4/21/2016 to 6/13/2016. 15 Montana residents were affected.
Affected (this filing): 15
CHI Franciscan Health Highline Medical Center (WA) reported to HHS OCR on 2016-09-01 an Unauthorized Access/Disclosure affecting 18,399 individuals. A business associate inadvertently left files containing patient ePHI publicly accessible via the internet from approximately mid-April 2016 to June 13, 2016. Breached information located on Network Server included patient names, dates of service, health insurance information, and Social Security numbers. Following the breach, the CE terminated the BA relationship and the BA deleted all patient files from its systems.
Affected (this filing):
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.