Evaluation of the quality of cardiopulmonary resuscitation according to vehicle driving pattern, using a virtual reality ambulance driving system: a prospective, cross-over, randomised study

Abstract

Objectives: To analyse changes in the quality of cardiopulmonary resuscitation (CPR) according to driving patterns encountered during ambulance transport, using a virtual reality simulator.

Design: Prospective, cross-over, randomised study.

Setting: This study was conducted at the National Fire Service Academy, Cheonan-si, Korea.

Participants: Emergency medical technicians (39 men and 9 women) attending the National Fire Service Academy for clinical training with ≥6 months field experience or having performed ≥10 CPR. Individuals who withdrew consent were excluded.

Outcome measures: CPR quality parameters (eg, chest compression depth and its variability).

Results: Chest compressions were performed for 8 min each in a stationary and driving state. The mean chest compression depths were 54.8 mm and 55.3 mm during these two states, respectively (p=0.41). The SD of the chest compression depth was significantly higher while in the driving (7.6 mm) than in the stationary state (6.5 mm; p=0.04). The compression depths in the speed bump and sudden stop sections were 51.5 mm and 50.6 mm, respectively, which was shallower than those in all other sections (p<0.001). The correct hand position rate was low in the speed bump, sudden stop and right-hand cornering sections (65.4%, 71.5% and 72.5%, respectively; p=0.001) CONCLUSIONS: Although we found no differences in chest compression quality parameters between the stationary and driving states, the variability in the chest compression depth increased in the driving state. When comparing CPR quality parameters according to driving patterns, we noted a shallower compression depth, increased variability and decreased correct hand position rate in the speed bump, sudden stop and right-hand cornering sections. The clinical significance of these changes in CPR quality during ambulance transport remains to be determined. Future studies on how to reduce changes in the quality of CPR (including research on equipment development) are needed.

Keywords: chest compression parameters; emergency medical services; virtual reality simulator.

Figure 1

Virtual reality ambulance simulator (A) a virtual reality driving route (B).

Figure 2

Box plot demonstrating the SD of the compression depth according to the driving pattern. The upper horizontal line of the box indicates the 75th percentile, the lower horizontal line the 25th percentile, the horizontal line within the box the median, the upper horizontal bar outside the box the maximum value excluding outliers and the lower horizontal bar outside the box the minimum value excluding outliers. Circles represent outliers (<25th percentile—1.5* IQR or >75th percentile+1.5* IQR).