Clustered 3 filings across 3 jurisdictions · filing window Feb 8, 2021 → Feb 12, 2021. View entity profile → Other incidents for this victim →
incident inc_73d37f4c778040f8 · 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.
Identity (basic) · Government ID · Health (basic)
IA ME MT
HHS OCR · State AG
Earliest sighting first · deep chronology in Litigation Timeline
Oct 19, 2020
When the intrusion reportedly occurred, per the linked filings
Oct 22, 2020
Reported by MAINE AG filing
Grand River Medical Group, P.C. reported a data breach to the Montana Attorney General. The breach was reported on 2021-02-08. The breach occurred from 10/19/2020 to 10/22/2020. 3 Montana residents were affected.
Affected (this filing): 3
Grand River Medical Group (Iowa) reported to HHS on 2021-02-12 a Hacking/IT Incident (email phishing) affecting 37,423 individuals. An employee was the victim of a phishing attack that compromised PHI including names, addresses, Social Security numbers, dates of birth, claims information, medications, and other treatment information. No business associate was involved. The CE notified HHS, individuals, and media; offered credit monitoring; strengthened technical safeguards; and retrained staff on email security. OCR provided HIPAA Security Rule technical assistance.
Affected (this filing): 37,423
Healthcare provider Grand River Medical Group, P.C. experienced an external system breach between October 19 and October 22, 2020. The incident was discovered on October 22, 2020, with potential data compromise confirmed by a forensic firm on December 15, 2020. The breach affected 37,858 individuals, who were notified in February 2021. The company offered 12 months of identity protection services to those affected.
Affected (this filing): 37,858
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.