In vitro evaluation of a computer-assisted decision support system for the primary care of polytrauma patients

Eur J Trauma Emerg Surg. 2023 Oct;49(5):2187-2192. doi: 10.1007/s00068-023-02295-9. Epub 2023 Jun 8.

Abstract

Introduction: The management of polytraumatized patients is set in a stressful environment with numerous critical decisions in a brief amount of time. Working along a standardised procedure can improve the outcome for these patients and reduce mortality. To help clinical practitioners, we developed "TraumaFlow", a workflow management system for the primary care of polytrauma patients based on the current treatment guidelines. This study sought to validate the system and investigate its effect on user performance and perceived workload.

Methods: The computer-assisted decision support system was tested in two scenarios in a trauma room of a level 1 trauma centre by 11 final-year medical students and 3 residents. In simulated polytrauma scenarios, the participants functioned as a trauma leader. The first scenario was performed without decision support and the second with support by "TraumaFlow" via tablet. During each scenario, the performance was evaluated in a standardized assessment. After each scenario, the participants answered a questionnaire on workload [NASA Raw Task Load Index (NASA RTLX)].

Results: In total, 14 participants (mean 28 ± 4 years, 43% female) managed 28 scenarios. During the first scenario without computer-assisted support, the participants achieved a mean of 6.6 out of 12 points (SD 1.2, range 5 to 9). With the support of TraumaFlow, the mean performance score was significantly higher with 11.6 out of 12 points (SD 0.5, range 11 to 12, p < 0.001). In the 14 scenarios performed without support, there was no run in which no errors were made. In comparison, ten of the 14 scenarios performed with TraumaFlow ran free of relevant errors. The mean improvement in the performance score was 42%. There was a significant decrease in the mean self-reported mental stress level in scenarios with support of TraumaFlow (55, SD 24) as compared to scenarios without support (72, SD 13, p = 0.041).

Conclusion: In a simulated environment, computer-assisted decision-making improved the performance of the trauma leader, helped to adhere to clinical guidelines, and reduced stress in a fast-acting environment. In reality, this may improve the treatment outcome for the patient.

Keywords: ATLS; Decision making; Emergency room; Life support; Outcome; Polytrauma; Safety; Simulation; Trauma; TraumaFlow; Workflow management.

MeSH terms

  • Computers
  • Female
  • Humans
  • Male
  • Multiple Trauma* / therapy
  • Primary Health Care
  • Trauma Centers
  • Workload*