{"resourceId":"healio-freiburg-smart-alerting-volunteer-cpr-randomized-20261108","versions":[{"version":"external-8db0d339a73a855ad4b5ec19033169012c222f429dbb39eebaea0a9b0eac4d23","resource":{"id":"healio-freiburg-smart-alerting-volunteer-cpr-randomized-20261108","title":"Freiburg randomized trial: alerting cardiac-arrest volunteers by predicted arrival time beat a 600 m radius but not a 2,500 m radius","organization":"Artemed St. Josefskrankenhaus Freiburg (reported by Healio from an AHA Resuscitation Science Symposium late-breaking abstract)","sector":"EMS dispatch / out-of-hospital cardiac arrest volunteer responders","geography":"Freiburg, Germany","publishedAt":"Healio, Nov. 8, 2026 (Scott Buzby); presented Nov. 6-9, 2026","publicationDate":"2026-11-08","eventDate":"2026-11-08","sourceName":"Healio","sourceLabel":"‘Smart alerts’ boost volunteer arrivals for suspected cardiac arrest","sourceUrl":"https://www.healio.com/news/cardiology/20261108/smart-alerts-boost-volunteer-arrivals-for-suspected-cardiac-arrest","evidenceClass":"independent-reporting","outcomeClass":"mixed","topics":["operating-model","infrastructure"],"finding":"Healio reports a prospective randomized trial in Freiburg (January to July 2024) that sent 1,482 volunteers to 823 suspected cardiac arrests across three arms. A \"smart alerting\" algorithm that selects volunteers by estimated travel time and screens out those predicted to arrive after the ambulance was compared with fixed 600 m and 2,500 m radius alerting. Volunteers arrived before EMS 58% of the time with smart alerts, 57% with 2,500 m and 31% with 600 m. Smart alerting beat 600 m (risk difference 27 percentage points, 95% CI 19-34, P < .001) but did not differ significantly from 2,500 m. AED arrival before the ambulance was 27% (smart), 28% (2,500 m) and 11% (600 m) among volunteers reaching the scene. The system rejected 31% of responders as likely to arrive later than the ambulance, which the researchers say may reduce futile dispatches.","sledRelevance":"A transferable dispatch-layer question for U.S. EMS agencies running smartphone responder apps: whether predicted-arrival selection adds value over a simply larger alert radius. The algorithm is travel-time routing rather than generative AI, so relevance to AI programs is partial.","evidence":"Opened the Healio article via HTTPS curl (User-Agent SLED-research-bot/1.0) and saved the text; quoted figures come from the conference presentation as reported by Healio. The abstract itself was not opened.","architectureImplications":"Needs live responder positions, a pre-alert step asking travel mode, route calculation and an ambulance ETA comparison inside the dispatch workflow.","governanceImplications":"Selecting or rejecting volunteers algorithmically needs documented rules, volunteer consent and review of who is screened out.","securityPrivacyImplications":"Continuous or on-alert location sharing by volunteers is personal data requiring consent, retention limits and access controls.","caveats":"Conference presentation reported by a trade outlet, not a peer-reviewed paper; only system performance was measured, not patient survival; randomization was by day of week rather than emergency type; German setting; no significant advantage over the 2,500 m radius.","streamIds":["emergency-services"],"roles":{"sales":"Sales framing: the Freiburg trial gives responder-app buyers a sharper question than \"do alerts help?\" Predicted-arrival alerting beat a small radius but only matched a larger one, so value lies in fewer wasted dispatches, not more early arrivals. Position a bounded baseline comparison before any procurement. Do not claim improved survival, shorter time to first compression or guaranteed volunteer retention; the source measured only arrival before the ambulance, and the 31% rejection benefit is the researchers’ expectation.","engineering":"Engineering view: the approach needs live volunteer positions, a pre-alert asking how each person is travelling, route estimation and an ambulance ETA to compare against. Check integration points with CAD and the responder app, and latency from call recognition to alert. Proof of value should replay local cardiac-arrest calls against fixed-radius and arrival-time rules before live use. The algorithm is routing logic rather than generative AI, and the source gives no model details.","delivery":"Delivery plan: run a shadow comparison of radius versus arrival-time selection on historical calls, then a randomized or alternating-day pilot like Freiburg’s. Dependencies are the app vendor, the dispatch centre medical director and volunteer coordinators. Acceptance should include arrival-before-EMS rate, AED-on-scene rate and volunteer opt-out rate. Main risks are consent for location data, screening out eligible volunteers and treating arrival metrics as survival evidence."},"roleDetails":{"sales":{"customerProblem":"EMS systems with volunteer responders want more helpers reaching cardiac arrests before the ambulance without burning out volunteers.","stakeholders":["EMS medical director","Dispatch centre manager","Volunteer responder coordinator","County or district EMS board"],"discoveryQuestions":["What radius do you use now and how often do volunteers arrive before EMS?","Do you track futile alerts or volunteer opt-outs?","Who approves how volunteer locations are used?"],"valueHypothesis":"Arrival-time selection may keep early-arrival rates near a large radius while sending fewer futile alerts, as interpretation of one trial.","potentialEngagement":"Four-to-six-week baseline analysis of local cardiac-arrest calls comparing radius and arrival-time alerting rules.","unsupportedClaims":["That smart alerting improves patient survival","That it outperforms a 2,500 m radius","That results transfer to U.S. systems without local testing"]},"engineering":{"fit":"Relevant to dispatch centres already running or planning a smartphone responder alerting system.","architectureIntegration":"Responder app and CAD feed incident location; service pre-alerts volunteers, asks travel mode, computes route and compares with ambulance ETA before dispatching.","prerequisites":["Responder app with live position","Ambulance ETA feed","Historical call data for replay"],"constraints":["Only system performance measured","Randomized by weekday not emergency type","German setting and road network"],"security":"Treat volunteer location and travel mode as personal data with consent, limited retention and role-based access.","proofOfValue":["Replay of past arrests under both rules","Pilot measuring arrival before EMS and AED on scene","Share of volunteers rejected and later outcomes of rejected alerts"]},"delivery":{"work":"Design and run a comparative pilot of alert-selection rules with clinical and operational review.","dependencies":["App vendor","CAD integration","Medical director approval","Volunteer consent process"],"ownership":"EMS medical director with dispatch centre manager.","skillsAdoption":"Dispatchers and coordinators need to understand why volunteers are rejected and how to override.","governanceCheckpoints":["Consent and data-protection review","Pilot protocol approval","Interim safety review of rejected alerts"],"acceptanceCriteria":["Arrival-before-EMS rate no lower than radius baseline","Reduction in futile alerts against baseline","Volunteer opt-out rate not increased"],"risks":["Location privacy complaints","Screening out helpers who would have arrived","Mistaking arrival metrics for survival"]}},"retrievedAt":"2026-11-09T03:58:59Z","enrichedAt":"2026-11-09T04:01:55Z","enrichmentBasis":"retrieved source","accessibilityWorkforceImplications":"Volunteer engagement is the stated motive: fewer futile dispatches may reduce alert fatigue, but this was not measured.","procurementImplications":"Buyers should ask vendors for randomized or comparative results against a simple radius baseline, since the larger radius performed about as well here.","operatingModelImplications":"Changes who is alerted and when relative to the ambulance; dispatchers and volunteer coordinators need clear fallback when the algorithm rejects responders.","peerReview":"unknown","sourceVerification":{"openedUrl":"https://www.healio.com/news/cardiology/20261108/smart-alerts-boost-volunteer-arrivals-for-suspected-cardiac-arrest","referenceExcerpt":"Smart alerts significantly increased pre-EMS arrival compared with the 600 m alert system","promptVersion":"sled-research-v4.0","model":null,"basis":"agent-reported inspection"}}}]}