Scene configuration and operational context

As illustrated in Figure 1, the Sanxia incident involved spatially dispersed casualty clusters, including a primary impact zone and a secondary cluster in an adjacent alley. This fragmentation limited early centralized oversight and required parallel assessments across multiple zones, complicating situational awareness during the initial operational phase. Prior studies of urban MCIs have similarly shown that nonlinear casualty distribution may delay command consolidation and increase reliance on decentralized decision-making during early response.Reference Kamler, Taube and Koch ^{1 ,} Reference Vassallo, Moran and Cowburn ²

Figure 1.

Schematic layout of the Sanxia mass-casualty incident scene showing collision points, vehicle path, casualty distribution, and ambulance positions (A1-A11). Schematic layout of the Sanxia mass-casualty incident scene illustrating key roadways, collision points, vehicle trajectory, major casualty cluster, secondary injury site, ambulance staging positions (A1-A11), and the location of the Incident Command Post (ICP). Landmarks such as nearby preschools and the elementary school are shown to provide spatial context for responder access and patient distribution. The diagram is not to scale.

Initial triage patterns and execution context

Initial patient assessment using the START protocol demonstrated overall alignment with subsequent transport and management priorities (Table 1). During the early operational phase, reassessment identified one initially ambulatory patient requiring additional evaluation, reflecting the dynamic nature of triage rather than a fixed misclassification. This finding underscores that triage during MCIs is a continuous process shaped by evolving patient conditions and resource availability, and that timely reassessment represents an operational strength rather than a failure of initial triage.Reference Marcussen, Bräuner and Alstrøm ^{3 ,} Reference Marcussen, Bräuner and Alstrøm ⁴

Table 1.

Summary of casualty characteristics and initial START triage classification

Note: Responder reflections documented at least one instance in which an ambulatory patient was initially categorized as green based on rapid assessment, and subsequently identified during reassessment as requiring additional observation. This finding is consistent with the appropriate execution of the reassessment process under dynamic MCI conditions, allowing prioritization decisions to be adjusted as clinical information evolves. Precise clinical parameters were not available, but no delay in life-saving intervention or priority transport was identified.

Temporal compression, multitasking, and information flow

The operational timeline presented in Table 2 demonstrates that triage, treatment, communication, and transport coordination occurred within a highly compressed interval, with multiple EMS units initiating patient contact before formal triage leadership and transport prioritization were fully established. Such temporal compression mirrors patterns described in prior analyses, in which early responder actions precede formal command consolidation.Reference Kamler, Taube and Koch ^{1 ,} Reference Rush, Lauria and DeSoucy ⁶

Table 2.

Chronological timeline of key operational events during the Sanxia mass-casualty incident

Note. Times are reported in local time and reflect reconstructed operational timelines based on dispatch records, responder documentation, and departmental after-action materials. Minor discrepancies of several seconds may exist due to asynchronous logging across sources. Event descriptions represent operational milestones rather than continuous activities. AAR, After-Action Report.

Under these conditions, multitasking demands increased reliance on informal communication pathways. In the Sanxia incident, handwritten notes, verbal updates, and radio reports served as primary mechanisms for information exchange during the critical early minutes. A private ambulance briefly attempted patient contact outside the formal MCI command structure; this was promptly corrected through on-scene coordination, after which transport proceeded under established EMS command and protocols. Activation of the MCI digital system occurred after completion of patient transport, reflecting the rapid pace of patient movement and reliance on analog communication during early response. These adaptations reflect operational realities during early MCI response rather than deviations from triage principles, particularly when reassessment and transport decisions must be continuously updated as scene conditions evolve.Reference Kamler, Taube and Koch ^{1 ,} Reference Vassallo, Moran and Cowburn ²

Digital system usability and operational adoption

Although an electronic MCI tracking platform was available, Table 2 indicates that system activation occurred only after all patients had been transported, limiting its operational relevance during the initial response window. Consequently, patient tracking and hospital notification relied on analog methods, with transport outcomes summarized in Table 3. While coordination was ultimately successful within a short operational interval, the absence of a shared digital platform constrained real-time situational awareness during early scene operations.

Table 3.

Patient distribution across receiving hospitals during the Sanxia mass-casualty incident

* Note: Transport destinations reflect real-time decision-making based on patient prioritization, hospital capacity updates, transport availability, and on-scene coordination during the incident. This table is descriptive and does not evaluate the clinical appropriateness of individual transport destinations or imply optimal hospital selection under ideal conditions.

This observation does not imply that digital tools would necessarily have altered clinical outcomes in this brief time frame. Rather, it highlights how usability, activation burden, and responder familiarity influence whether digital systems are adopted under peak operational stress. Prior literature emphasizes that effective digital integration in MCIs depends not only on system availability but also on training, recurrent use, and maintenance of operational competencies.Reference Apiratwarakul, Cheung and Tiamkao ^{7 ,} Reference Tahernejad, Sahebi and Abadi ⁸

Integration of auxiliary personnel

Non-EMS personnel, including school staff and community volunteers, were present during the response and primarily provided emotional support, reassurance, and basic scene containment for uninjured or distressed individuals. While not substituting for clinical roles, these contributions likely reduced peripheral demands on EMS personnel during early operations. Although the absence of formal integration into the incident command structure did not result in observable operational failure in this incident, disaster medicine literature suggests that predefined auxiliary roles may enhance system flexibility in larger or more prolonged MCIs.Reference Jetten, Seesink and Klimek ^{9 ,} Reference Markou-Pappas, Lamine and Ragazzoni ¹⁰

Triage uncertainty and system-level interpretation

Aggregated examples of context-dependent triage uncertainty are summarized in Table 4, illustrating where decision ambiguity emerged across initial sorting, reassessment, and transport prioritization. These patterns reflect the influence of cognitive load, fragmented scene layout, bystander input, and documentation constraints, rather than failures to recognize life-threatening conditions or perform appropriate interventions.Reference Marcussen, Bräuner and Alstrøm ^{3 ,} Reference Marcussen, Bräuner and Alstrøm ⁴ No evidence indicated delayed or inappropriate life-saving interventions, missed deterioration, or incorrect priority transport decisions. Instead, observed variability reflects inherent uncertainty in prioritization under time pressure and evolving operational conditions.Reference Marcussen, Bräuner and Alstrøm ³

Table 4.

Aggregated examples of triage decision uncertainty and contributing operational factors

System-level implications and limitations

While this analysis relied on reconstructed timelines and focused on operational processes rather than patient-level outcomes within a single jurisdiction, it provides actionable insights into urban mass-casualty incident response. The Sanxia incident illustrates that, even with established protocols, triage decision-making is strongly shaped by execution context, including cognitive load, scene fragmentation, and concurrent task demands. In addition, limited early use of digital tools and the absence of predefined auxiliary roles underscore the importance of aligning response systems with the realities of compressed operational timelines. Future incorporation of structured clinical outcome analysis into post-incident reviews may help inform targeted improvements in system design, operational protocols, and responder training competencies.