Clustered 5 filings across 4 jurisdictions · filing window Sep 20, 2025 → May 1, 2026. View entity profile → Other incidents for this victim →
incident inc_6edfbb965e39466c · merge_method human · confidence 100%
Discovered → first regulatory filing
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.
MA MI NH
Leak Site · HHS OCR · State AG
Earliest sighting first · deep chronology in Litigation Timeline
Sep 20, 2025
When the intrusion reportedly occurred, per the linked filings
Hematology Oncology Consultants Michigan Hematology Oncology is a private practice dedicated to providing the highest level of quality care in a healing environment for the mind, body and spirit of patients dealing with cancer and blood disorders.
Hematology Oncology Consultants Michigan Hematology Oncology is a private practice dedicated to providing the highest level of quality care in a healing environment for the mind, body and spirit of patients dealing with cancer and blood disorders.
Feb 12, 2026
Reported by NEW HAMPSHIRE AG filing
Hematology Oncology Consultants reported to HHS on 2026-04-24 a Hacking/IT Incident affecting 62972 individuals. Breached information located on Network Server.
Hematology Oncology Consultants (HOC), a Michigan healthcare provider, notified the New Hampshire Attorney General of a data event affecting 2 NH residents. Unauthorized access occurred on the network around September 20, 2025, but was discovered on February 12, 2026. Affected data included names, SSNs, and PHI. HOC engaged cyber specialists, enhanced network security, and offered 12 months of credit monitoring.
Affected (this filing):
Massachusetts Attorney General's office received a breach notification from Hematology Oncology Consultants (Ref: 2026-676). The source document provided is empty, containing no details regarding the incident type, data affected, or individuals impacted.
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): 62,972