Commentary: Digital cross-sectoral training with dynamic patient and situation simulation in the context of mass casualty incidents—insights from the research projects D2PuLs and D2PuLs PRO

Introduction

A commentary on Konrad R, Pfadenhauer T, Eckenweber L, Banahovschi A, Braun C, Reuter T, Popp S, Engelen C, Baierl L, Soy M and Bauer C (2026) Digital cross-sectoral training with dynamic patient and situation simulation in the context of mass casualty incidents—insights from the research projects D2PuLs and D2PuLs PRO. Front Disaster Emerg Med. 4:1756349. doi: 10.3389/femer.2026.1756349.

Konrad et al. describe a modular digital simulation environment that combines dynamic patient physiology, configurable clinical and prehospital scenarios, hybrid use with manikins, and data-supported debriefing for mass-casualty incident training (1). This is a valuable advance because it makes deterioration, competing demands, and resource allocation more visible than static patient cards. The evidence is nevertheless preliminary: the reported field tests primarily addressed feasibility, usability, technical implementation, organizational process, and self-assessed learning rather than observed clinical performance or patient-safety outcomes (1). A nursing-focused extension should therefore build on the platform's demonstrated feasibility while avoiding claims of established effectiveness.

Make nursing contributions measurable

The clinical field trial included 13 participants, of whom seven had nursing qualifications: six with specialist training in emergency, anesthesia, or intensive care and one with general nursing preparation (1). However, evaluation results were presented for the clinical group as a whole. This aggregation limits interpretation because nursing and medical participants may have different responsibilities, learning needs, interface risks, and performance expectations. Future D2PuLs evaluations should define profession-specific learning objectives before each scenario and report outcomes by role, while preserving interprofessional team measures.

The platform already permits configurable roles, dynamic patient progression, hospital triage, treatment-area allocation, communication workflows, and structured debriefing (1). What remains insufficiently explicit is the nursing contribution within these functions. Nursing-specific roles could include receiving or triage nurse, resuscitation nurse, medication and oxygen coordinator, surge-flow nurse, infection-prevention liaison, transfer and handover coordinator, and family-communication lead. These roles align with disaster-nursing competencies in preparedness, communication, ethical practice, clinical care, leadership, public health, and recovery (2). Scenarios should test nursing actions such as repeated triage after deterioration, safe identification during crowding, prioritization of oxygen and medication under scarcity, recognition and escalation of deterioration, isolation decisions, documentation continuity, and structured handover.

Outcome measures should also distinguish platform-generated activity from demonstrated competence. Candidate nursing-sensitive measures could include time to first reassessment, completeness of structured handover, recognition of deterioration, escalation accuracy, critical-documentation completeness, and omitted essential nursing care. These measures should initially be described as proposed indicators, then tested for feasibility, reliability, validity, and association with team performance before being used as measures of disaster readiness. Interprofessional simulation literature similarly supports aligning scenarios with explicit learning objectives and using valid measures of behavioral change rather than relying only on learner perceptions (3, 4).

Match technical design to resource constraints

Konrad et al. already discuss modularity, mobile use, hybrid formats, local protocol adaptation, and data-informed debriefing (1). The resource-limited extension is therefore not simply to repeat these strengths, but to address the platform's stated infrastructure requirements. Multiplayer training requires a device and stable internet connection for every participant, while the operator may need a high-performance laptop; hardware and licensing requirements rise further when individual third-party scene simulation is added (1). These requirements may exclude facilities with intermittent connectivity, limited equipment, or few trained instructors.

Concrete developments should include low-bandwidth operation, temporary offline scenario caching with later synchronization, simplified graphics, a lightweight instructor dashboard, shared-device small-group modes, and printable backup materials. Locally editable scenario templates should permit adaptation to available medicines, oxygen systems, staffing, referral pathways, and scope-of-practice rules. These design choices would complement, rather than replace, the mobile and hybrid architecture already described by Konrad et al. They would also support preparedness, cross-sector coordination, and timely emergency care within constrained health systems (5, 6).

Inclusive scenarios are also needed. Children, pregnant women, older people, persons with disabilities, displaced populations, and patients dependent on oxygen, dialysis, blood products, or continuous monitoring may face disproportionate harm during disrupted care (7). D2PuLs scenarios could model communication barriers, inaccessible evacuation or transfer, family separation, interruption of essential therapies, and ethical prioritization under scarcity. Nursing roles are central to recognizing and mitigating these risks.

From preliminary feasibility to safer practice

D2PuLs has not yet been tested through a live cross-sectoral handover of pretreated patients from prehospital teams to a hospital, and larger MCI scenarios remain untested (1). These should be priorities for future evaluation. A staged programme could assess usability first, then profession-specific performance, interprofessional handover, larger-scale system reliability, retention of learning, and transfer to observed practice. Debriefing should remain facilitated and non-punitive, using time-stamped actions to examine what happened, why it happened, and which system conditions shaped performance. Evidence-based debriefing standards emphasize planned reflection and a safe learning environment (8, 9).

In conclusion, D2PuLs offers a promising and adaptable foundation, but its nursing value will depend on making nursing roles, objectives, and outcomes explicit. The appropriate next claim is not that patient safety has already improved, but that the platform provides preliminary feasibility evidence and a testable opportunity to strengthen nursing and interprofessional performance across the mass-casualty care pathway.

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Footnotes

Edited by: Andreas Follmann, University Hospital RWTH Aachen, Germany

Reviewed by: Robert Wunderlich, University of Tübingen, Germany