Black Hills Regional Eye Institute https://www.blackhillseyes.com/ is a USA based medical group practice located in Rapid City, SD that specializes in Ophthalmology and Optometry. The network of this medical group had been breached and encr ...
Clustered 2 filings across 2 jurisdictions · filing window Jan 8, 2025 → Mar 31, 2025. View entity profile → Other incidents for this victim →
incident inc_238a1869fc6b4c0d · merge_method deterministic · confidence 100%
Gap between first leak claim and first regulatory filing
Time between earliest and latest filing
Not recorded for this incident
Discovery variance · Materiality delta · SEC filing delay — no SEC 8-K in this cluster; needs two dated filings.
SD
Leak Site · HHS OCR
Earliest sighting first · deep chronology in Litigation Timeline
Black Hills Regional Eye Institute https://www.blackhillseyes.com/ is a USA based medical group practice located in Rapid City, SD that specializes in Ophthalmology and Optometry. The network of this medical group had been breached and encr ...
Black Hills Regional Eye Institute reported to HHS on 2025-03-31 a Hacking/IT Incident affecting 106,763 individuals. Breached information located on Network Server. The PHI involved included clinical, demographic, and financial information. The CE implemented additional administrative, technical, and security safeguards.
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.
Affected (this filing): 106,763