PHI Isolation Requirements for Healthcare AI Workloads

PHI isolation requirements for healthcare AI workloads are the tenancy, memory, dump, log, and retrieval controls that keep identifiable health data from other tenants, extra admins, and unauthorized apps. Encryption at rest is necessary and not sufficient. A live GPU holds plaintext tensors. A RAG index can retrieve a note the caller should never see.

This is a requirements list for infrastructure buyers, not legal advice, and not a claim that OneSource Cloud is HIPAA certified. HIPAA-ready means the environment can be designed for regulated workloads. Isolation is what reviewers ask for after the slogan.

What must be isolated

De-identified research can sometimes share a partition. Identifiable inference usually cannot. Split data classes. Do not park PHI on the cheap shared SKU because training was cheaper there last month.

Requirements you can put in an RFP

Named exclusive tenancy. No silent replicas of volumes abroad. Break-glass support that is logged and time-bound. Retrieval filters on document ACLs before generation. A delete proof for vectors. A BAA conversation if the vendor is a business associate. Evidence export for who accessed the workspace. If the vendor cannot fill those cells, you do not have isolation. You have a GPU.

OneSource Cloud’s healthcare AI infrastructure is exclusive private environments designed for that list, on private AI infrastructure. Keep language at HIPAA-ready. OnePlus, OneSource Cloud’s AI orchestration platform, keeps clinical workspaces off research fair-share. AI storage holds embeddings in the same boundary. Covered entities still own process and BAAs with other parties.

FAQ

What isolation does PHI on GPU workloads require?

Exclusive tenancy for identifiable jobs, dump and image control, log and prompt ACLs, retrieval filters, and a delete path for vectors and checkpoints. Encryption at rest does not isolate live memory. A shared GPU with a HIPAA sentence fails this list even if the disk is encrypted.

Is MIG enough to isolate PHI?

MIG can split a device for small jobs. It does not isolate dumps, NICs, or a shared tracing project. Use it as packing on an already exclusive clinical partition if the program wants it. Do not use it as the only PHI boundary on a multi-tenant cloud GPU.

Do embeddings of clinical notes count as PHI?

Treat them as in-scope until counsel says otherwise. They can be joined or inverted in messy systems. Store them with the same residency, ACL, and delete rules as the source notes. A vector SaaS in another region is a new copy.

Can de-identified training skip exclusive GPUs?

Sometimes, if de-identification is real and the review allows it. Re-identification joins and logs bring PHI back. When in doubt, keep clinical work on exclusive partitions. Saving GPU dollars is a weak isolation argument.

Does exclusive hardware make the workload HIPAA compliant?

No. It makes isolation evidence easier. Compliance stays with the covered entity. Vendors should stay at HIPAA-ready unless a signed package documents more.

Summary

PHI isolation is tenancy, dumps, logs, retrieval, and copies, not a label on a shared GPU. Put the list in the RFP. For exclusive U.S. environments designed for healthcare AI, review OneSource Cloud’s healthcare path on private AI infrastructure and keep identifiable jobs off mixed queues.