From the Emergency Services edition of November 8, 2026
Freiburg randomized trial: alerting cardiac-arrest volunteers by predicted arrival time beat a 600 m radius but not a 2,500 m radius
Artemed St. Josefskrankenhaus Freiburg (reported by Healio from an AHA Resuscitation Science Symposium late-breaking abstract) · EMS dispatch / out-of-hospital cardiac arrest volunteer responders · Freiburg, Germany
- Publisher
- Healio
- Original publication
- Healio, Nov. 8, 2026 (Scott Buzby); presented Nov. 6-9, 2026
- Source retrieved
- 2026-11-09
- Event date
- 2026-11-08
What happened
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.
Why it matters
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 and measured results
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.
Limitations and uncertainty
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.
Put this evidence to work
Lighthouse Advisory interpretation, grounded in this source. Enriched 2026-11-09; this does not change the original publication date. Each role follows the same checklist so takeaways compare across sources.
Sales
Role takeaway
- Customer problem
- 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
- Discovery questions
- 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?
- Value hypothesis
- Arrival-time selection may keep early-arrival rates near a large radius while sending fewer futile alerts, as interpretation of one trial.
- Potential engagement
- Four-to-six-week baseline analysis of local cardiac-arrest calls comparing radius and arrival-time alerting rules.
- Unsupported claims
- That smart alerting improves patient survival
- That it outperforms a 2,500 m radius
- That results transfer to U.S. systems without local testing
Pre-sales engineering
Role takeaway
- Fit
- Relevant to dispatch centres already running or planning a smartphone responder alerting system.
- Architecture and integration
- 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.
- Proof of value
- 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
Role takeaway
- 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.
- Skills and adoption
- Dispatchers and coordinators need to understand why volunteers are rejected and how to override.
- Governance checkpoints
- Consent and data-protection review
- Pilot protocol approval
- Interim safety review of rejected alerts
- Acceptance criteria
- 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
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?
Needs live responder positions, a pre-alert step asking travel mode, route calculation and an ambulance ETA comparison inside the dispatch workflow.
Governance
Who approves, reviews and stays accountable for outcomes?
Selecting or rejecting volunteers algorithmically needs documented rules, volunteer consent and review of who is screened out.
Security and privacy
What data, permissions and controls need testing?
Continuous or on-alert location sharing by volunteers is personal data requiring consent, retention limits and access controls.
Accessibility and workforce
Who is affected, and what skills or accommodations follow?
Volunteer engagement is the stated motive: fewer futile dispatches may reduce alert fatigue, but this was not measured.
Procurement
What should contracts, pricing and exit terms secure?
Buyers should ask vendors for randomized or comparative results against a simple radius baseline, since the larger radius performed about as well here.
Operating model
Which teams own the service once it runs?
Changes who is alerted and when relative to the ambulance; dispatchers and volunteer coordinators need clear fallback when the algorithm rejects responders.
Publication history
- 2026-11-08Emergency Services · Issue 634 resources
Stable resource ID: healio-freiburg-smart-alerting-volunteer-cpr-randomized-20261108