From the Emergency Services edition of October 20, 2026
Jeju 119 says AI ECG reads relayed to physicians nearly doubled ambulance 12-lead ECG use and cut cardiac re-transfers to 0.6%
Jeju Special Self-Governing Province Fire Safety Headquarters (with Jeju National University Hospital and ARPI) · Emergency medical services · Jeju, Republic of Korea
- Publisher
- Seoul Shinmun
- Original publication
- 2026-10-20
- Source retrieved
- 2026-10-21
- Event date
- 2026-09-17
What happened
Seoul Shinmun (published 2026-10-20 10:00 KST) reports that Jeju Special Self-Governing Province's Fire Safety Headquarters won the top (presidential) prize at the 38th 119 Fire Policy Conference on Sept 17 for an AI-based severe cardiovascular emergency system built on ARPI's ECG Buddy AI ECG analysis. Built from 2024 with Jeju National University Hospital, the province and ARPI, it was piloted by 11 ambulance teams from January 2025 and has run across all 32 Jeju ambulance teams since March 2026. Paramedics record a 12-lead ECG and send the AI result and patient details to an online medical-direction physician, who decides the destination; the process went from seven steps to three. Per Jeju Fire and partners, 12-lead ECG use rose from 47.2% (2024) to 89.7%, hospital transmission reached 98.5%, direct transport to PCI-capable hospitals was 96% (March-May 2026), and re-transfer of suspected severe cardiac patients fell from 4.9% to 0.6% (one patient); 13 of 14 re-transfers in 2024 did not use ECG Buddy. A hospital team's 2025 pilot analysis found teams using it had 28.3% higher ECG use and 38.2% more medical-direction requests, 90% PCI within 90 minutes of arrival, and AUROC 0.94. A data platform linking EMS and hospital records is planned.
Why it matters
A rare EMS AI deployment reporting process and transport outcomes across an entire provincial fleet. U.S. EMS agencies and regional STEMI systems can use it to frame what to measure, while recognizing the numbers are operator-reported before-after figures.
Evidence and measured results
Newspaper report of operator, hospital and vendor figures plus a hospital pilot analysis summarized without methods; no independent evaluation.
Limitations and uncertainty
Figures are operator- and vendor-supplied (photos credited to ARPI; ARPI CEO quoted) and repeated in near-identical Digital Times coverage; before-after comparison against 2024 with no control and concurrent protocol changes (seven to three steps, medical direction, training); re-transfer rate rests on very small counts; AUROC target and denominators not given; no adverse events, false positives or survival outcomes reported; Korean-language source; single island province with one regional cardiac center.
Put this evidence to work
Lighthouse Advisory interpretation, grounded in this source. Enriched 2026-10-20; this does not change the original publication date. Each role follows the same checklist so takeaways compare across sources.
Sales
Role takeaway
- Customer problem
- Suspected heart-attack patients are taken to hospitals that cannot perform PCI, delaying treatment and requiring re-transfer.
- Stakeholders
- EMS medical director
- Fire/EMS chief
- Regional STEMI or cardiac center lead
- Online medical control physicians
- Discovery questions
- What share of chest-pain patients get a 12-lead in the field?
- How often are cardiac patients re-transferred?
- Who decides destination today?
- How are field ECGs transmitted?
- Value hypothesis
- An AI ECG read inside a physician-directed workflow could raise field ECG use and direct transport to PCI centers, if local validation holds.
- Potential engagement
- Prehospital STEMI pathway baseline and AI ECG pilot design with a regional cardiac center.
- Unsupported claims
- Improved survival
- Reduced re-transfer attributable to AI alone
- Transferability to U.S. EMS systems
- Low false-positive rate
Pre-sales engineering
Role takeaway
- Fit
- Decision support for prehospital 12-lead ECG interpretation within online medical direction.
- Architecture and integration
- Monitor ECG export to an AI service, relay of AI result and patient data to a physician, and destination decision recorded in the ePCR.
- Prerequisites
- 12-lead-capable monitors
- Reliable transmission
- Online medical control
- Local outcome data for validation
- Constraints
- Medical device regulation of AI ECG software
- Rural connectivity
- Single-region evidence
- Security
- Encrypt ECG and patient data in transit, define vendor retention and access, and audit data-platform use.
- Proof of value
- Agreement of AI reads with local cath-lab outcomes
- False-positive activations per month
- Transmission failure rate
- Re-transfer cases reviewed
Delivery
Role takeaway
- Work
- Implement an AI-supported prehospital STEMI pathway with simplified steps and physician direction.
- Dependencies
- Hospital cardiology
- Monitor and AI vendors
- Paramedic training
- Online medical control staffing
- Ownership
- EMS medical director with the regional cardiac center.
- Skills and adoption
- Paramedics record and transmit quality 12-leads routinely; physicians learn the AI tool's error modes.
- Governance checkpoints
- Local validation before go-live
- Case review of every re-transfer and missed STEMI
- Quarterly false-positive review
- Acceptance criteria
- Field 12-lead rate measured against a 12-month baseline
- Direct-to-PCI transport share reported monthly
- All re-transfers reviewed within 30 days
- Risks
- False-positive activations
- Over-reliance on AI read
- Attributing bundled process gains to AI alone
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?
12-lead ECG captured in the field, AI interpretation and patient data transmitted to an online medical-direction physician; planned integration of EMS and hospital clinical data.
Governance
Who approves, reviews and stays accountable for outcomes?
Physician medical direction keeps the destination decision with a clinician; agencies should define who acts on AI reads and how disagreements are logged.
Security and privacy
What data, permissions and controls need testing?
Transmits identifiable ECG and patient data to hospitals and a vendor service; the planned EMS-hospital data platform needs consent, retention and access rules.
Accessibility and workforce
Who is affected, and what skills or accommodations follow?
Requires paramedic training and staffed online medical direction; island patients benefited from direct helicopter transport in one cited case.
Procurement
What should contracts, pricing and exit terms secure?
Buyers should require local validation data and clarity on whether the AI is a regulated medical device.
Operating model
Which teams own the service once it runs?
AI read supports, and a physician makes, the destination decision; fewer handoff steps.
Publication history
- 2026-10-20Emergency Services · Issue 446 resources
Stable resource ID: seoul-shinmun-jeju-119-ai-ecg-buddy-ecg-rate-retransport-20261020