From the Emergency Services edition of September 12, 2026
New York EMS advisory makes AI use in clinical decisions part of the patient record
New York State Department of Health and State Emergency Medical Services Council · EMS clinical governance · New York, United States
- Publisher
- New York State Department of Health
- Original publication
- March 31, 2026
- Source retrieved
- 2026-09-13
What happened
The advisory says providers must document how consulted AI informed care and remain responsible for clinical decisions and documentation.
Why it matters
Directly applicable to New York EMS governance; other jurisdictions require their own policy review.
Evidence and measured results
This is guidance, not an outcome evaluation. It addresses consent for recordings, security review, appropriate business associate agreements, fact-checking and withdrawal of inadequately validated tools. No sample, comparator or measured benefit is supplied.
Limitations and uncertainty
Advisory scope is New York EMS. It does not certify any product or establish compliance through a hosting choice.
Put this evidence to work
Lighthouse Advisory interpretation, grounded in this source. Enriched 2026-09-13; this does not change the original publication date. Labels below come from the analysis itself.
Sales
Role takeaway
Discuss undocumented AI use with the EMS chief, medical director, privacy lead and ePCR administrator. Ask whether staff can identify where assistance influenced care and how recordings reach third parties. Offer a bounded workflow assessment and synthetic-record demonstration. The value hypothesis is more traceable documentation with a manageable review burden; measure that burden against current practice. Do not promise clinical gains, guaranteed savings or product compliance. Include frontline clinicians in deciding whether a proposed documentation step is usable during transport. A separate local policy assessment is needed outside New York.
Pre-sales engineering
Role takeaway
Prototype an ePCR extension that records the tool version, relevant source inputs and clinician disposition without letting the assistant sign or finalize records. Prerequisites include supported interfaces, an approved field mapping and privacy-reviewed test data. Test omitted facts, invented observations, contradictions and unavailable inference services. A useful proof of value measures material errors and total correction time against clinician-authored records. Restrict service credentials and audit exports. The advisory supplies no acceptable error threshold, so medical leadership must define the pilot limits before testing. Developer agents have limited relevance beyond controlled implementation work.
Delivery
Role takeaway
Clinical quality should own rollout with IT, privacy staff and clinician trainers. Map the encounter-to-record process, approve data handling, run synthetic tests and then seek the agency's normal clinical pilot authorization. Dependencies include review capacity and vendor interface support. Proposed acceptance criteria include traceable AI use for every assisted test record, no automatic finalization, successful fallback and prespecified limits on material errors. Train staff to report concerns and exercise a suspension procedure. Monitor accessibility of review controls and whether corrections add work during busy shifts. These are proposed criteria, not measured results.
Implementation considerations
Lighthouse Advisory interpretation across the operating dimensions a public-sector buyer must settle before this evidence becomes a design. Each note answers the question under its heading for this specific source.
Architecture and integration
What must connect, and where does the AI sit in the workflow?
Add a reviewable AI-use field to the clinical workflow and separate draft generation from record finalization. Evaluate cloud, local and hybrid processing against approved data boundaries.
Governance
Who approves, reviews and stays accountable for outcomes?
Assign approval and suspension authority before pilot access is enabled.
Security and privacy
What data, permissions and controls need testing?
Trace recording, transcription, inference and retention separately; use synthetic records until data handling is approved.
Accessibility and workforce
Who is affected, and what skills or accommodations follow?
Evaluate review controls with mobile users and clinicians needing assistive technology; include training and correction time in workload estimates.
Procurement
What should contracts, pricing and exit terms secure?
Require exportable audit data, declared subprocessors and change-notification terms as reviewable deliverables.
Operating model
Which teams own the service once it runs?
Medical leadership owns permitted use; IT owns continuity; clinicians own encounter accuracy.
What changed
Newly catalogued historical advisory, absent from the 247-resource archive inspected. Adds a state-specific AI-use documentation obligation beyond the archived NASEMSO guidance; no September 12 policy change claimed.
Publication history
- 2026-09-12Emergency Services · Issue 073 resources
Stable resource ID: ny-ems-genai-advisory-26-01