A three-layer framework for pre-hospital triage to reduce non-urgent emergency use in Germany
- 1International Public Health Management, University of Europe for Applied Sciences, Iserlohn, Germany
Abstract
Background: Emergency departments in Germany and across Europe continue to experience inappropriate utilisation by non-urgent cases despite established primary care pathways. This reflects persistent gaps in patient navigation and decision-making before care-seeking. AI-supported triage has emerged as a potential upstream intervention but lacks structured integration into public health systems.
Objectives: To develop a system-level framework for integrating AI-supported pre-hospital triage into healthcare access pathways to reduce non-urgent emergency department utilisation.
Methods: A policy and systems analysis was conducted, combining evidence synthesis with structured mapping of patient care pathways within the German health system. A three-layer integration framework was developed: (1) access (digital entry-point triage), (2) routing (linkage to primary care and telehealth), and (3) system feedback (data integration into planning and resource allocation). The framework was assessed across feasibility, safety, and equity.
Results: The framework identifies leverage points to redirect patients before emergency department entry. Key success factors include interoperability, clear escalation protocols, and risk stratification safeguards, including thresholds for high-risk cases. A central trade-off is identified: while AI-supported triage may improve efficiency, it risks reinforcing inequities and misclassification if digital exclusion and governance challenges are not addressed. Hybrid models combining digital tools with human support are critical.
Conclusions: AI-supported pre-hospital triage represents a feasible systems-level intervention to improve care navigation and reduce unnecessary emergency use. Embedding such tools within existing structures—while addressing equity, safety, and governance—will determine their impact and transferability across European health systems.
Key messages: • A structured three-layer approach can improve patient navigation and reduce system inefficiencies by shifting decision-making before emergency care use.
• Without safeguards, AI triage may misclassify high-risk patients and exclude digitally disadvantaged groups, potentially worsening inequities in access to care.
Related
- Evaluating a Large Language Model for Emergency Triage Using Synthetic Clinical Dialogues: Toward a Multimodal Clinical Safety Framework
- Initial Emergency Department Triage Narratives for Predicting Hospital Admission and Early Critical Outcomes: A Retrospective Chronological Split Study
- Emergency Severity Index Stratified by Post-Triage Lactate: Association with In-Hospital Mortality in Admitted Patients.
- Development and internal validation of triage-stage prediction models for short-term critical outcomes among adult emergency department patients entering observation or hospital-based care: a retrospective study.
- Ethnoracial disparities in emergency department triage are more pronounced in lower-risk visits: a multicenter study
BibTeX
@article{moturi2026threelayer,
title = {{A three-layer framework for pre-hospital triage to reduce non-urgent emergency use in Germany}},
author = {SS Moturi},
journal = {The European Journal of Public Health},
year = {2026},
month = oct,
doi = {10.1093/eurpub/ckag169.874},
url = {https://doi.org/10.1093/eurpub/ckag169.874},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - A three-layer framework for pre-hospital triage to reduce non-urgent emergency use in Germany
AU - SS Moturi
PY - 2026
DA - 2026/10/01
JO - The European Journal of Public Health
DO - 10.1093/eurpub/ckag169.874
UR - https://doi.org/10.1093/eurpub/ckag169.874
AB - Background: Emergency departments in Germany and across Europe continue to experience inappropriate utilisation by non-urgent cases despite established primary care pathways. This reflects persistent gaps in patient navigation and decision-making before care-seeking. AI-supported triage has emerged as a potential upstream intervention but lacks structured integration into public health systems. Objectives: To develop a system-level framework for integrating AI-supported pre-hospital triage into healthcare access pathways to reduce non-urgent emergency department utilisation. Methods: A policy and systems analysis was conducted, combining evidence synthesis with structured mapping of patient care pathways within the German health system. A three-layer integration framework was developed: (1) access (digital entry-point triage), (2) routing (linkage to primary care and telehealth), and (3) system feedback (data integration into planning and resource allocation). The framework was assessed across feasibility, safety, and equity. Results: The framework identifies leverage points to redirect patients before emergency department entry. Key success factors include interoperability, clear escalation protocols, and risk stratification safeguards, including thresholds for high-risk cases. A central trade-off is identified: while AI-supported triage may improve efficiency, it risks reinforcing inequities and misclassification if digital exclusion and governance challenges are not addressed. Hybrid models combining digital tools with human support are critical. Conclusions: AI-supported pre-hospital triage represents a feasible systems-level intervention to improve care navigation and reduce unnecessary emergency use. Embedding such tools within existing structures—while addressing equity, safety, and governance—will determine their impact and transferability across European health systems. Key messages: • A structured three-layer approach can improve patient navigation and reduce system inefficiencies by shifting decision-making before emergency care use. • Without safeguards, AI triage may misclassify high-risk patients and exclude digitally disadvantaged groups, potentially worsening inequities in access to care.
SN - 1101-1262
SN - 1464-360X
ER -