{"resourceId":"seattle-corti-ems-documentation-pia-2026","versions":[{"version":"external-076c71df414b2e7ec1b2bbddea1e0afab4711ba18f203bf1ea0d84d1671da8c7","resource":{"id":"seattle-corti-ems-documentation-pia-2026","title":"Seattle Fire Corti EMS documentation pilot emphasizes HITL review and patient notice","organization":"City of Seattle / Seattle Fire Department","sector":"Municipal fire/EMS / city privacy governance","geography":"United States (Seattle, Washington)","publishedAt":"2026-08-31","publicationDate":"2026-08-31","eventDate":"2026-08-01","sourceName":"City of Seattle Privacy and AI Impact Assessment","sourceLabel":"Government privacy and AI impact assessment PDF","sourceUrl":"https://www.seattle.gov/documents/Departments/Tech/Privacy/PIA_2026/2026%20Privacy%20and%20AI%20Impact%20Assessment_Corti_AI_8.31.2026.pdf","evidenceClass":"standards-guidance","outcomeClass":"emerging","topics":["knowledge-work","data-security","governance-procurement","accessibility-workforce","operating-model"],"finding":"Seattle's Aug 31, 2026 Privacy/AI Impact Assessment describes a multi-month Corti Assistant pilot in which transcription and an in-app LLM surface medically relevant fields for EMT/paramedic review before manual paste into ESO, with patient notice, opt-out, no ESO integration, stated no vendor training on Seattle data, and multiple human validation steps—documentation support, not autonomous triage.","sledRelevance":"Why now: newly relevant after September 2026 public scrutiny (already archived) of Seattle Fire AI on 911 medical calls; this PIA is a distinct, previously unarchived governance artifact for a field-documentation pilot that makes notice and HITL controls explicit, informing SLED delivery patterns for EMS AI.","evidence":"PIA sections detail scope (handwritten/typed notes vs transcription+LLM surfacing), validation sequence, consent/notice language, HIPAA/RCW framing, cloud processing claims, retention alignment, and explicit statement that the system produces recommendations and cannot act without human intervention. Anticipated benefits are not measured in the document.","architectureImplications":"Keep documentation AI on managed devices with manual EHR paste (no silent integration) until accuracy and retention are proven; separate this stack from live 911 audio-prompting systems architecturally and contractually.","governanceImplications":"Require published PIAs, patient notice/opt-out where feasible, clinician attestation before chart finalization, and clear distinction between documentation assistance and triage/diversion AI.","securityPrivacyImplications":"PHI in vendor cloud demands BAAs, access logging, deletion assurances, and limits on employee access; verify no-training-on-customer-data contractually and technically.","caveats":"Self-assessment not independent audit; benefits unverified; does not evaluate Corti live triage prompting; pilot parameters may change.","streamIds":["emergency-services"],"roles":{"sales":"Lead with EMS charting burden and timestamp or spelling error risk, then show how Seattle's PIA structures patient notice and multi-step human review before chart entry. Do not conflate this documentation pilot with 911 triage diversion products discussed in other Seattle reporting. Offer a privacy-impact-ready field documentation pilot with an explicit no-triage-scope clause. Unsupported claims include measured time savings at the prospect, clinical outcome improvement, or that this PIA evaluates live triage AI.","engineering":"Fit is on-device or app transcription plus constrained LLM field-surfacing with mandatory clinician edit before EHR entry. No direct ePCR writeback appears in the described Seattle pilot architecture. Prerequisites include managed devices only, a business associate agreement, retention timers, and QA sampling of transcript-to-chart fidelity. Proof of value is timed documentation workflows and clinician correction rates under local protocols—not hospital marketing analogies alone.","delivery":"Implement a small-unit pilot: configure devices, script patient notice and opt-out logging, train on review and edit steps, sample charts weekly, and stop if PHI handling or accuracy fails gates. Ownership belongs with EMS medical leadership plus city privacy reviewers, while the vendor owns platform controls under contract. Risks include hallucinated medications entering charts, scope creep into triage prompting, and public distrust if notice is skipped in the field."},"roleDetails":{"sales":{"customerProblem":"EMS clinicians lose time and accuracy when manually charting vitals and history under time pressure, but agencies face privacy and trust barriers to AI scribes.","stakeholders":["Fire/EMS medical director","Field EMTs/paramedics","City privacy/IT security","Receiving hospital/ePCR administrators"],"discoveryQuestions":["Will patients be notified and able to decline transcription?","Is writeback to the ePCR in or out of scope for the pilot?","Who attests the final chart if AI drafted fields?","What retention and non-training terms are in the vendor contract?"],"valueHypothesis":"A notice-enabled, HITL documentation assistant may improve chart completeness if correction burden stays low—without claiming Seattle has proven outcome gains.","potentialEngagement":"Privacy/AIA-aligned pilot design for one battalion with weekly fidelity audits and an explicit no-triage-scope clause.","unsupportedClaims":["Measured reduction in charting time at the prospect","Clinical outcome improvement from transcription AI","That this PIA authorizes or evaluates live 911 triage AI"]},"engineering":{"fit":"Field documentation transcription and LLM field-surfacing with human gatekeeping; not CAD triage or nurse-line diversion.","architectureIntegration":"Managed mobile app; vendor cloud STT/LLM; manual copy into existing ePCR (ESO-class); no automated integration in the described Seattle pilot.","prerequisites":["City-managed devices only","BAA and non-training contractual controls","Patient notice script and opt-out logging","QA sampling process for transcript errors"],"constraints":["Implied consent contexts for altered patients","Cloud processing of PHI","Pilot-only scope and retention rules"],"security":"Enforce role-based access, encryption, deletion after retention, and vendor employee access only with agency permission; verify controls beyond vendor assertions.","proofOfValue":["Clinician correction rate per chart","Time from patient contact to completed ePCR fields","Count of opt-outs and any PHI incidents"]},"delivery":{"work":"Configure app on unit devices, train notice and review workflow, run multi-month pilot sampling, and decide expand/stop with privacy and medical directors.","dependencies":["Vendor provisioning","City privacy review already exemplified by PIA","ePCR process owners","Field training time"],"ownership":"SFD/EMS clinical leadership owns chart quality; city privacy owns PIA compliance; vendor owns platform controls under contract.","skillsAdoption":"Train crews to treat AI output as draft text; practice declining use when patients object; escalate chart conflicts to lead clinician.","governanceCheckpoints":["PIA publication/update","Mid-pilot accuracy review","Scope check barring triage features","Retention/deletion verification"],"acceptanceCriteria":["Documented HITL attestation on sampled charts","Working opt-out logging","No unauthorized ePCR auto-write"],"risks":["Hallucinated meds/vitals entering charts","Scope creep into call triage","Public distrust if notice is skipped"]}},"retrievedAt":"2026-09-15T14:15:20Z","enrichedAt":"2026-09-15T14:19:37Z","enrichmentBasis":"retrieved source","accessibilityWorkforceImplications":"May reduce after-call documentation load if accurate; requires training so crews do not defer clinical judgment to surfaced fields; opt-out must work for patients who refuse recording-like tools.","procurementImplications":"Use the PIA as a template checklist: BAA, non-training, managed devices, no silent EHR integration, and published privacy assessment before go-live.","operatingModelImplications":"Separate documentation AI governance from any live 911 prompting program; keep clinician attestation as the chart source of truth.","sourceVerification":{"openedUrl":"https://www.seattle.gov/documents/Departments/Tech/Privacy/PIA_2026/2026%20Privacy%20and%20AI%20Impact%20Assessment_Corti_AI_8.31.2026.pdf","referenceExcerpt":"Humans (EMTs/Paramedics) are required to verify all transcribed data and attest to accuracy","promptVersion":"sled-research-v4.0","model":null,"basis":"agent-reported inspection"}}}]}