NHID-Clinical
NHID-Clinical v1.1
Non-Human Identity Disclosure Standard for Healthcare Voice Workflows
Abstract
NHID-Clinical defines a minimum control baseline for non-human identity disclosure in B2B healthcare voice interactions.
The standard addresses a documented gap between existing consumer-protection laws, healthcare privacy regulations, and real-world payer–provider administrative workflows. It specifically targets “Impersonation Latency”—the operational waste and security risk caused when a human provider cannot immediately distinguish an AI agent from a human counterpart.
Note: This standard is scoped strictly for B2B Administrative Workflows (Provider-to-Payer, Business Associate-to-Payer). It does not currently cover direct-to-consumer or patient-facing clinical triage.
Problem Statement
In current healthcare operations, AI voice agents are commonly deployed for eligibility checks, claim status inquiries, and administrative routing. In many implementations:
- AI agents do not disclose non-human identity unless explicitly challenged.
- Disclosure is reactive rather than proactive.
- Providers spend billable time determining whether they are interacting with a human.
This creates Impersonation Latency: time lost due to uncertainty about the nature of the counterparty.
Positioning
NHID-Clinical is a voluntary governance standard that operationalizes transparency requirements.
- Beyond Minimums: It aligns with the intent of HIPAA (access control), NIST (measurability), and the California B.O.T. Act (disclosure timing), while establishing strict operational boundaries that may exceed baseline legal requirements.
- Operational Focus: Unlike broad ethical frameworks, it provides binary, testable logic gates (e.g., “Pre-Data Exchange”) for engineering and QA teams.
- Risk Reduction: Designed to reduce “Impersonation Latency”—a specific operational risk not fully addressed by general privacy laws.
Regulatory Context & Compatibility
NHID-Clinical operates at the operational layer, complementing existing legal frameworks without conflict:
- HIPAA: NHID-Clinical focuses on the identity of the actor, ensuring that the “Minimum Necessary” standard is applied to the correct entity type (human vs. machine).
- TCPA / FCC: While these govern outbound consent, NHID-Clinical manages the content of the inbound handshake to prevent deceptive practices in exempt B2B calls.
- California B.O.T. Act: Extends the spirit of disclosure to private healthcare administrative channels not explicitly covered by public-facing consumer laws.
The Standard
1. Proactive Identity Assertion (PIA)
The Rule: All non-human voice agents must proactively disclose their non-human identity during the initial greeting and prior to the solicitation or intake of any operational data (e.g., NPI, Member ID, Claim Number).
Timing & Latency: Disclosure must occur before any request for operational data exchange. This “Pre-Data Exchange” requirement accounts for VoIP/SIP latency and variable greeting lengths while maintaining a clear, auditable boundary.
Compliant Example:
“Hello, I am an automated assistant for [Payer Name] Claims. I can help you with status and eligibility. To begin, please say the NPI.”
Non-Compliant Example:
“Hello, this is Sarah. Can I get the NPI?” (Violation: Uses a human name without qualification; requests data before disclosure.)
2. Prohibition of Deceptive Artifacts (“The Turing Boundary”)
The Rule: Agents must not employ synthetic audio artifacts that serve no communicative function other than to imply biological presence or mask processing latency.
Prohibited “Masking” Techniques:
- Simulated Physical Actions: Sound effects of keyboard typing, mouse clicking, or paper shuffling.
- Simulated Biological Functions: Synthetic breathing sounds, clearing of the throat, or coughing.
- Deceptive Latency Masking: Using scripted “thinking” sounds (e.g., “Umm…”, “Let me see…”) implies a human cognitive process. Agents should instead use functional status updates (e.g., “One moment while I search that record…”).
Note: Natural prosody, inflection, and conversational pacing required for clear communication are permitted and encouraged.
3. Escalation & Safe Failover
The Rule: When a human stakeholder explicitly requests a transfer or indicates the agent is failing to understand:
- Acknowledgement: The agent must immediately acknowledge the request (e.g., “I understand you need to speak to a specialist”).
- Context Preservation: The agent should generate a reference number or interaction ID to prevent data reentry.
- Safe Failover:
- If human staff is available: Transfer immediately.
- If human staff is unavailable (e.g., after hours): The agent must explicitly state hours of operation and offer a voicemail or callback option rather than looping or disconnecting.
Audit & Evidence Requirements
To ensure compliance without imposing undue technical burdens, implementations must maintain Interaction Logs.
Minimum Required Evidence (Tier 1):
- Transaction Log: A text-based log entry timestamping the “Identity Assertion” event relative to the “Call Connected” event.
- Script Versioning: Documentation of the active call script proving the disclosure verbiage was present in the production flow.
Recommended Evidence (Tier 2):
- Audio Artifact: A recording of the first 30 seconds of the interaction (subject to organizational data retention policies).
Metrics
Suggested indicators for measuring success:
- Disclosure Failure Rate (DFR): % of calls where data exchange was attempted before identity disclosure.
- Escalation Loop Count: Frequency of callers repeating “Agent” or “Representative” more than twice (indicating failed escalation logic).
- Administrative Velocity: Reduction in total call handle time (AHT) due to the elimination of “Are you a robot?” verification loops.
NIST AI RMF Alignment
NHID-Clinical operationalizes the NIST AI Risk Management Framework (AI RMF 1.0):
| AI RMF Function | Category | NHID-Clinical Alignment |
|---|---|---|
| GOVERN | GOV 1.5 – Risk Management | Defines “impersonation” as a specific operational risk to be governed. |
| MAP | MAP 3.4 – Human-AI Interaction | Establishes the boundary where synthetic voice output must not deceive human actors. |
| MEASURE | MEAS 2.6 – Transparency | Introduces quantifiable metrics (DFR) to evaluate disclosure effectiveness. |
| MANAGE | MAN 4.1 – Post-Deployment Monitoring | Requires audit artifacts and disclosure logs for ongoing oversight of agent identity behavior. |
Known Gaps & Future Scope
This v1.1 candidate does not currently address:
- Patient-facing workflows: Direct-to-consumer or clinical triage interactions.
- Outbound calls: Payer-initiated or proactive agent calls.
- International compliance: GDPR or non-U.S. regulatory contexts.
- Accessibility: Multilingual support, deaf/hard-of-hearing accommodations, or cultural communication variations.
- Multi-entity integrations: Scenarios where AI handles data across multiple payers or vendors dynamically.
- Enforcement mechanisms: Certification, audit standards, or adoption incentives.
These are candidates for v1.2 and beyond, contingent on community feedback.
License
This work is licensed under the Creative Commons Attribution 4.0 International License (CC-BY 4.0).
Author: Brianna Baynard
Repository: github.com/thankcheeses/NHID-Clinical
Feedback & Next Steps
This is a v1.1 Candidate released for public comment. We invite:
- Technical feedback on the Pre-Data Exchange requirement and audit logging feasibility.
- Compliance input from HIPAA officers, healthcare IT architects, and payer/provider operations teams.
- Implementation experience from organizations piloting similar controls.
Please open an issue or discussion in this repository to contribute.
Changelog
v1.1 (Candidate)
- Shifted timing requirement from “3-second window” to “Pre-Data Exchange gate” for improved auditability and latency-agnostic compliance.
- Added “Known Gaps & Future Scope” section for transparency about coverage limitations.
- Refined positioning language to emphasize governance best practice over regulatory equivalence.
- Clarified distinction between permitted natural prosody and prohibited deceptive artifacts.
v1.0
- Initial draft with temporal disclosure requirements and NIST/HIPAA alignment mapping.