Faul Philipp, Neubecker Daniela, Schweigkofler Uwe, Koch Daniel, Hagebusch Paul
Department of Trauma and Orthopedics, BG Trauma Center Frankfurt, Friedberger Landstr. 430, 60389, Frankfurt Am Main, Germany.
Department of Anesthesiology, Intensive Care Medicine and Pain Therapy, BG Trauma Center Frankfurt, Friedberger Landstr. 430, 60389, Frankfurt Am Main, Germany.
Eur J Trauma Emerg Surg. 2025 Aug 22;51(1):278. doi: 10.1007/s00068-025-02949-w.
Providing effective emergency trauma care is a growing challenge for healthcare systems, particularly amid rising case numbers and limited hospital resources in Germany. Accurate prehospital assessment and appropriate hospital allocation significantly influence patient outcomes. IVENA eHealth® (Interdisziplinärer Versorgungsnachweis) is a nationwide digital platform that supports Emergency Medical Services (EMS) in coordinating emergency care and assigning patients based on real-time hospital capacity. However, its clinical accuracy has not been thoroughly evaluated and its triage categories are based on EMS estimation rather than a validated classification system. This study analyzes the concordance between prehospital trauma-patient allocation via IVENA and actual clinical treatment pathways.
In this retrospective single-center study, trauma referrals to a level-1-trauma-center in 2018 were analyzed. Included were patients triaged as severity category 1 (SC1, immediate) or severity category 2 (SC2, urgent) with suspected polytrauma, traumatic brain injury (TBI), thoracic or pelvic trauma. Prehospital SC was compared to hospital admission types: SC1 was assumed to require ICU care, SC2 a general ward. Patients triaged as severity category 3 (SC3, non-urgent) were not included in the analysis. Overtriage and undertriage rates were assessed, and prehospital suspected diagnoses were compared with discharge diagnoses. Sensitivity, specificity, and positive predictive value (PPV) were calculated. Logistic regression was used to identify influencing factors.
Among 4,331 patients, 742 (17.1%) were SC1, 2,840 (65.6%) SC2, and 749 (17.3%) SC3. SC1 (245 included patients) triage accuracy was 64.08%, with 35.92% overtriaged. SC2 (446 included patients) had 55.61% overtriage and 2.24% undertriage, exceeding the ≤ 50% recommended threshold. SC1 classification showed 94.01% sensitivity and 64.08% PPV. Discrepancies between prehospital and discharge diagnoses were frequent, particularly for polytrauma, TBI, and thoracic trauma. Polytrauma with TBI had 82.35% triage accuracy, while polytrauma without TBI showed 45.45% overtriage. Closed TBI cases classified as SC1 were overtriaged in 41.67%, while SC2 patients had 51.33% overtriage and 2.66% undertriage.
The digital referral system IVENA eHealth® supports the structured transmission of EMS-assigned patient allocations, but the accuracy of SC1 and SC2 assignments varies considerably. The observed discrepancies between prehospital classifications and actual clinical care highlight the limitations of current prehospital assessment practices. SC1 classification resulted in ICU admission in only 64.08% of cases, indicating the need to reassess assumptions linking severity codes with clinical requirements. Despite these mismatches, the overall undertriage rate remained below 3%, suggesting a high level of patient safety within the current system. Optimizing prehospital assessment protocols, integrating real-time hospital capacity data, and strengthening EMS training may improve allocation accuracy. To better align digital referral systems with clinical realities, future research should focus on developing dynamic decision-support tools, implementing adaptive allocation algorithms, and evaluating the effects of updated clinical guidelines.
对于医疗系统而言，提供有效的紧急创伤护理面临着日益严峻的挑战，尤其是在德国病例数量不断上升且医院资源有限的情况下。准确的院前评估和适当的医院分配对患者的治疗结果有重大影响。IVENA eHealth®（跨学科服务证明）是一个全国性的数字平台，可支持紧急医疗服务（EMS）协调急救护理并根据医院实时容量分配患者。然而，其临床准确性尚未得到全面评估，并且其分诊类别基于EMS的估计，而非经过验证的分类系统。本研究分析了通过IVENA进行的院前创伤患者分配与实际临床治疗路径之间的一致性。
在这项回顾性单中心研究中，对2018年转诊至一级创伤中心的创伤患者进行了分析。纳入的患者为疑似多发伤、创伤性脑损伤（TBI）、胸部或骨盆创伤且分诊为严重程度1类（SC1，紧急）或严重程度2类（SC2， urgent）的患者。将院前SC与医院入院类型进行比较：假设SC1需要重症监护病房（ICU）护理，SC2需要普通病房。分诊为严重程度3类（SC3，非紧急）的患者未纳入分析。评估过度分诊和分诊不足率，并将院前疑似诊断与出院诊断进行比较。计算敏感性、特异性和阳性预测值（PPV）。使用逻辑回归确定影响因素。
在4331例患者中，742例（17.1%）为SC1，2840例（65.6%）为SC2，749例（17.3%）为SC3。SC1（纳入245例患者）的分诊准确率为64.08%，过度分诊率为35.92%。SC2（纳入446例患者）的过度分诊率为55.61%，分诊不足率为2.24%，超过了建议的≤50%的阈值。SC1分类显示敏感性为94.01%，PPV为64.08%。院前诊断与出院诊断之间的差异很常见，尤其是在多发伤、TBI和胸部创伤方面。伴有TBI的多发伤的分诊准确率为82.35%，而不伴有TBI的多发伤的过度分诊率为45.45%。分类为SC1的闭合性TBI病例中，41.67%被过度分诊，而SC2患者的过度分诊率为51.33%，分诊不足率为2.66%。
数字转诊系统IVENA eHealth®支持EMS分配患者的结构化传输，但SC1和SC2分配的准确性差异很大。院前分类与实际临床护理之间观察到的差异凸显了当前院前评估实践的局限性。SC1分类仅导致了64.08%的病例入住ICU，这表明需要重新评估将严重程度代码与临床需求联系起来的假设。尽管存在这些不匹配情况，但总体分诊不足率仍低于3%，表明当前系统内患者安全水平较高。优化院前评估方案、整合医院实时容量数据以及加强EMS培训可能会提高分配准确性。为了使数字转诊系统更好地与临床实际情况保持一致，未来的研究应专注于开发动态决策支持工具、实施自适应分配算法以及评估更新后的临床指南的效果。
