Substance abuse treatment programs have a matching profile shaped by 42 CFR Part 2 as much as by HIPAA. A patient enrolled in opioid use disorder treatment may have a chart in the general medical record system and a separate record in the SUD program's system, and the two cannot be merged without explicit consent. An MPI solution that fits this setting has to manage identity without forcing the records into a single combined view.
This walks through the MPI solutions that come up most in 2026 SUD program conversations. For the rest of the FHIR series the broader catalog has the surrounding context.
The architectural framing lives in the complete guide to MPI for behavioral health networks in 2026.
What SUD Programs Add to the MPI Brief
The expectations come down to five capabilities:
- Identity linking without record merging, so 42 CFR Part 2 records stay separated even when the identity is the same.
- Probabilistic matching that handles the unstable address data SUD populations often have.
- An audit log that distinguishes "identity link" from "record merge" events.
- Stewardship that lets a non-engineer resolve ambiguous matches without violating Part 2.
- A consent record attached to any identity link that crosses the Part 2 boundary.
Most general-purpose MPIs handle the second capability well. The other four are where SUD-specific work has to happen.
The MPI Solutions Worth Knowing
- MDMbox. A FHIR-native MPI that treats identity linking as separate from record access; useful when the policy is "match the patient, do not necessarily merge the records."
- NextGate. Enterprise MPI with mature stewardship tooling that supports the kind of granular permission model SUD programs need.
- Verato. Referential-matching service used as the identity layer with a separate access-control layer enforcing Part 2.
- Mirth Match. Practical mid-network MPI with the integration story most SUD programs running on Mirth Connect already know.
- OpenEMPI variants. Open-source matching engines for programs with platform-engineering capacity and a strong opinion about on-premises data residency.
What Tips the Choice in SUD Programs
Three operational factors decide:
- Part 2 posture. Tools that treat identity linking and record access as separable concerns reduce policy risk; tools that conflate them push the policy work to a separate access-control layer.
- Address tolerance. SUD populations include patients in housing-insecure situations; address-strict matching produces a high duplicate rate.
- Stewardship boundaries. Stewards reviewing ambiguous matches need to see only the identity metadata, not the Part 2 record content; tools that enforce that separation save a policy review.
For multi-site counseling more generally, Top 5 MPI tools for multi-site counseling practices in 2026 covers the broader brief. For the algorithmic-matching axis (deterministic vs probabilistic), Deterministic vs probabilistic patient matching for behavioral health lays out the trade-offs.
How to Pilot Cleanly
Pick three SUD-specific scenarios: a patient with the same identity in the general medical chart and the SUD program record, a patient in unstable housing with three slightly different addresses, and a steward resolving an ambiguous match across both systems. Run each candidate solution, watch the identity-linking behavior, and check that the steward never sees Part 2-protected content they should not see. Solutions that hold up across all three are the ones worth pricing.
Sources
- Confidentiality of SUD Patient Records final rule - Federal Register rule, SAMHSA + HHS OCR, 2024
- FHIR Granular Sensitive Data Segmentation - Peer-reviewed study, JAMIA via PMC, 2025
- Identity Matching IG Patient Matching chapter - HL7 IG, HL7 Patient Administration WG, 2025
