{"resourceId":"htn-secamb-para-ai-paramedic-attitudes-ai-20261109","versions":[{"version":"external-7efc54f054a84ba30b20dd1ce4dabff5f3d0c355f9da65520e64084100c91ee7","resource":{"id":"htn-secamb-para-ai-paramedic-attitudes-ai-20261109","title":"SECAmb PARA-AI: paramedics back AI in clinical care only with safeguards and want final responsibility kept with clinicians","organization":"South East Coast Ambulance Service NHS Foundation Trust (reported by HTN Health Tech News)","sector":"EMS / ambulance service workforce","geography":"United Kingdom (England)","publishedAt":"2026-11-09","publicationDate":"2026-11-09","eventDate":null,"sourceName":"HTN Health Tech News","sourceLabel":"Trade-press report of a service-run survey and interview study","sourceUrl":"https://htn.co.uk/2026/11/09/south-east-coast-ambulance-service-presents-findings-from-para-ai-project-exploring-attitudes-toward-ai-in-pre-hospital-care/","evidenceClass":"independent-reporting","outcomeClass":"mixed","topics":["accessibility-workforce","governance-procurement"],"finding":"HTN reports that SECAmb presented findings from its ten-month, mixed-methods PARA-AI project at a clinical research summit: 171 survey responses plus 14 in-depth paramedic interviews. Of respondents, 83% would use AI in clinical practice if safeguards were in place, 80% stressed clear governance, audit and accountability, 92% wanted paramedics involved in design and testing, 96% said ultimate clinical responsibility should stay with paramedics, and 83% worried about over-reliance. The trust says it turned the findings into a roadmap for the safe introduction of AI in ambulance services.","sledRelevance":"This is workforce-attitude evidence, not a performance evaluation of any AI tool. It informs EMS and dispatch agencies planning adoption: staff acceptance is conditional on governance, audit and retained human responsibility. Applicability to U.S. fire/EMS is limited by the UK NHS setting and a self-selected sample.","evidence":"Survey (171 responses) and 14 interviews with SECAmb paramedics over ten months, presented at an internal summit and reported by trade press. Percentages are as reported by HTN; the article gives no response rate, sampling method or questionnaire. The roadmap itself was not published in the article.","architectureImplications":"No technical architecture is evaluated. Interpretation: respondents' emphasis on audit and accountability implies adopters should plan logging of AI outputs and clinician overrides from the start.","governanceImplications":"Staff expect clear governance, audit processes and accountability (80%) and retained clinician responsibility (96%). Interpretation: include paramedic representatives in design, testing and approval gates.","securityPrivacyImplications":"Not discussed in the article. Related AT PACE work on AI-assisted ePCR documentation (simulated scenarios, 50 participants) is announced, not reported.","caveats":"Attitudes are not outcomes. The sample is 171 paramedics in one UK trust, with no reported response rate or selection method; results come second-hand via trade press from a summit presentation, not a peer-reviewed paper. Transferability to U.S. fire/EMS agencies is uncertain.","streamIds":["emergency-services"],"roles":{"sales":"Frame this as an adoption-readiness signal, not proof of benefit. One UK ambulance trust's survey suggests clinicians accept AI when safeguards, audit and clinician accountability are explicit, and many fear over-reliance. For U.S. EMS and fire agencies, that supports leading conversations with governance, training and change management before tooling. Do not cite the percentages as evidence that AI improves response or patient outcomes; they measure attitudes in one trust, reported second-hand.","engineering":"No system was tested, so there is no architecture finding. The practical takeaway for pre-sales is that clinician acceptance depends on visible audit trails and the ability to override. Scope proofs of value to include logging of AI suggestions and human decisions, and to involve paramedics in test design, as 92% of respondents wanted. Treat the survey as requirements input, not validation of any product's accuracy.","delivery":"Delivery should treat clinician engagement as a workstream: paramedic involvement in design and testing, a governance and audit process, and explicit statements that clinicians retain final responsibility. The trust's roadmap is a reported starting framework but was not available in the source. Plan training on over-reliance, since 83% of respondents raised it, and measure adoption and override behaviour after go-live rather than assuming acceptance persists."},"roleDetails":{"sales":{"customerProblem":"EMS leaders must introduce AI without losing clinician trust or clinical accountability.","stakeholders":["EMS chief or ambulance CEO","Medical director","Paramedic and union representatives","Clinical governance lead","Dispatch center manager"],"discoveryQuestions":["Which clinician groups have been consulted on AI use so far?","What audit and accountability process would you require before a pilot?","How would you detect over-reliance on AI suggestions?"],"valueHypothesis":"A clinician-engagement and governance workshop may reduce adoption friction before any tool pilot; this survey supports the need but not a measured benefit.","potentialEngagement":"Bounded AI-readiness and governance workshop with paramedic representation, producing a safeguards checklist and pilot criteria.","unsupportedClaims":["That AI improves patient outcomes or response times","That U.S. clinicians hold the same views as the SECAmb sample","That stated willingness translates into sustained use"]},"engineering":{"fit":"Limited: attitude evidence that informs requirements rather than architecture.","architectureIntegration":"Design for logging of AI outputs, clinician accept/override actions and traceability into the patient record or CAD.","prerequisites":["Defined clinical decision-support use case","Audit log retention policy","Clinician testing cohort"],"constraints":["No validation of any AI model","UK NHS setting; U.S. protocols and liability differ"],"security":"Not addressed in the article; any pilot needs standard patient-data governance review.","proofOfValue":["Pilot in which paramedics co-design the test and review override rates","Clinician trust survey before and after a bounded pilot"]},"delivery":{"work":"Run clinician-led design and testing, stand up governance and audit, and train staff on AI limits and over-reliance.","dependencies":["Medical director sponsorship","Clinician time for co-design","Audit data pipeline"],"ownership":"EMS medical director with the clinical governance lead.","skillsAdoption":"Training on appropriate reliance and on documenting overrides; paramedic champions.","governanceCheckpoints":["Clinical safety review before pilot","Written statement that clinicians retain final decisions","Periodic audit review"],"acceptanceCriteria":["Proposed: paramedic representatives sign off the test plan","Proposed: all AI suggestions and overrides logged","Proposed: follow-up survey tracks over-reliance concerns"],"risks":["Over-reliance on AI","Survey enthusiasm not matching real use","Roadmap not available for reuse"]}},"retrievedAt":"2026-11-11T04:02:04Z","enrichedAt":"2026-11-11T04:02:04Z","enrichmentBasis":"retrieved source","accessibilityWorkforceImplications":"Central finding: paramedic buy-in depends on involvement in design and testing (92%) and on keeping clinical responsibility with paramedics (96%). Over-reliance worries (83%) point to a training need.","procurementImplications":"Interpretation: require vendors to support clinician co-design, audit logging and override reporting as procurement criteria.","operatingModelImplications":"The trust reports converting findings into a roadmap for safe introduction; operating-model details were not published in the article.","peerReview":"unknown","sourceVerification":{"openedUrl":"https://htn.co.uk/2026/11/09/south-east-coast-ambulance-service-presents-findings-from-para-ai-project-exploring-attitudes-toward-ai-in-pre-hospital-care/","referenceExcerpt":"83 percent of respondents said they would be willing to use AI technologies in clinical practice, so long as the appropriate safeguards were in place","promptVersion":"sled-research-v4.0","model":null,"basis":"agent-reported inspection"}}}]}