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June 6, 2026Frontiers in Public Health0 citationsOpen Access

Advancements in smart healthcare in emergency trauma care: from intelligent triage to prognostic prediction

FCFanyi ChengTXTao XuJMJunwei Mao

Key Points

  • This mini-review aims to explore the integration of smart healthcare technologies in emergency trauma care and their implications for clinical decision-making.
  • Synthesis of recent evidence on AI and telemedicine applications in trauma care.
  • Analysis of current studies focusing on prehospital triage, injury identification, and risk prediction.
  • Discussion of telemedicine's role in remote consultation and transfer support.
  • AI shows promise in predicting mortality and transfusion needs, improving patient outcomes.
  • Telemedicine reduces unnecessary interfacility transfers, enhancing trauma system efficiency.
  • Challenges include algorithmic bias, lack of prospective studies, and integration into clinical workflows.

Abstract

Emergency trauma care demands rapid, accurate decisions across the continuum from prehospital triage to definitive treatment and follow-up. Smart healthcare technologies, particularly artificial intelligence (AI) and telemedicine, are increasingly being integrated into trauma systems to augment clinical judgment, improve resource allocation, and expand access to specialist expertise. This mini-review synthesizes recent evidence on the application of these technologies in emergency trauma care. Current studies suggest that AI can support prehospital triage, identify life-threatening injuries on imaging, predict mortality, transfusion needs, and other adverse outcomes, and facilitate early risk stratification for both physiological and psychological sequelae. Telemedicine has shown value in remote consultation, transfer decision support, and virtual follow-up, with potential to reduce unnecessary interfacility transfers and optimize trauma system efficiency. However, the field remains constrained by major challenges, including the predominance of retrospective validation studies, limited prospective evidence of clinical utility, concerns regarding algorithmic opacity and bias, and persistent barriers related to workflow integration, infrastructure, reimbursement, and human factors. Overall, smart healthcare is reshaping emergency trauma care from intelligent triage to prognostic prediction, but its translation into routine practice will require prospective implementation studies, explainable and equitable model development, and closer alignment with real-world clinical workflows.

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Cite This Study

Cheng et al. (2026) studied this question.

synapsesocial.com/papers/6a23b89f71a5da9775e74b60https://doi.org/10.3389/fpubh.2026.1834849
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Also Consider

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  1. 1Enhancing Performance of the National Field Triage Guidelines Using Machine Learning: Development of a Prehospital Triage Model to Predict Severe Trauma2024 · 15 citations
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