Welcome to Psychiatryai.com: Latest Evidence - RAISR4D

Digital coordination in mass casualty incidents: a retrospective analysis of prehospital distribution times before and after IVENA-MANV implementation

AI Summary
  • IVENA-MANV implementation did not significantly change triage-to-evacuation or total prehospital times (no statistically significant difference, p > 0.05).
  • System enabled structured hospital allocation and real-time capacity confirmation, mean 1.8 minutes to first confirmation, without extending on-scene times.
  • MCI severity level independently predicted prolonged intervals; digital tools likely strengthen coordination and documentation rather than accelerating evacuation, warranting prospective multicentre evaluation.
Summarise with AI (MRCPsych/FRANZCP)

Eur J Trauma Emerg Surg. 2026 May 20;52(1):168. doi: 10.1007/s00068-026-03216-2.

ABSTRACT

BACKGROUND: Digital coordination tools have been proposed to improve management during mass casualty incidents (MCIs). In 2021, the IVENA-MANV system was introduced in the Hannover region as an extension of the established IVENA eHealth platform to enable digital patient tracking and hospital capacity management. However, no real-world evaluations have yet quantified their operational impact.

OBJECTIVES: This study aimed to provide the first real-world evaluation of the IVENA-MANV digital coordination system and to determine how its implementation affected prehospital distribution processes and time intervals during mass casualty incidents.

METHODS: A retrospective observational study to assess the impact of the IVENA-MANV digital coordination platform on prehospital times during MCIs in Germany was conducted using dispatch records and IVENA-MANV logs from all MCIs between January 2018 and July 2025 in the Hanover-Region in Germany. Primary outcomes were the triage-to-evacuation (TtE) and total prehospital time (TPHT) per patient. Mann-Whitney U tests compared pre- and post-implementation groups, and multiple linear regression models examined associations between IVENA-MANV use, MCI-level, and time intervals.

RESULTS: Seventy-three MCIs met inclusion criteria, including 188 documented individual casualty characteristics. 41.1% of incidents used IVENA-MANV. Most MCIs were trauma-related (65.8%) and traffic-associated (64.4%). Mean TtE was 40.2 ± 19.3 min, and mean TPHT 83.9 ± 29.5 min. No statistically significant differences were found between pre- and post-implementation cohorts (p > 0.05). Regression analysis confirmed MCI-level as the only significant predictor of prolonged intervals (p < 0.001). IVENA-MANV enabled structured hospital allocation and real-time capacity confirmation (mean 1.8 min to first confirmation) without extending on-scene times.

CONCLUSIONS: Implementation of IVENA-MANV did not significantly affect prehospital time intervals but demonstrated qualitative benefits for coordination, documentation, and hospital communication. The value of digital systems in disaster medicine may therefore lie in strengthening coordination and information resilience rather than accelerating evacuation. Prospective multicentre and mixed-methods studies are warranted to assess their broader system-level impact.

PMID:42159736 | DOI:10.1007/s00068-026-03216-2

Document this CPD

AI Search

Share Evidence Blueprint

QR Code

Search Google Scholar

Save as PDF

close chatgpt icon
ChatGPT

Enter your request.

Psychiatry AI: Real-Time AI Scoping Review