Use of medical simulation to explore equipment failures and human-machine interactions in anesthesia machine pipeline supply crossover.

摘要

BACKGROUND: High-fidelity medical simulation can be used to explore failure modes of technology and equipment and human-machine interactions. We present the use of an equipment malfunction simulation scenario, oxygen (O(2))itrous oxide (N(2)O) pipeline crossover, to probe residents' knowledge and their use of anesthetic equipment in a rapidly escalating crisis. METHODS: In this descriptive study, 20 third-year anesthesia residents were paired into 10 two-member teams. The scenario involved an Ohmeda Modulus SE 7500 anesthetic machine with a Datex AS/3 monitor that provided vital signs and gas monitoring. Before the scenario started, we switched pipeline connections so that N(2)O entered through the O(2) pipeline and vice versa. Because of the switched pipeline, the auxiliary O(2) flowmeter delivered N(2)O instead of O(2). Two expert, independent raters reviewed videotaped scenarios and recorded the alarms explicitly noted by participants and methods of ventilation. RESULTS: Nine pairs became aware of the low fraction of inspired O(2) (Fio(2)) alarm. Only 3 pairs recognized the high fraction of inspired N(2)O (Fin(2)o) alarm. One group failed to recognize both the low Fio(2) and the high Fin(2)o alarms. Nine groups took 3 or more steps before instigating a definitive route of oxygenation. Seven groups used the auxiliary O(2) flowmeter at some point during the management steps. CONCLUSIONS: The fact that so many participants used the auxiliary O(2) flowmeter may expose machine factors and related human-machine interactions during an equipment crisis. Use of the auxiliary O(2) flowmeter as a presumed external source of O(2) contributed to delays in definitive treatment. Many participants also failed to notice the presence of high N(2)O. This may have been, in part, attributable to 2 facts that we uncovered during our video review: (a) the transitory nature of the high N(2)O chose to mute. We suggest that the use of high-fidelity simulations may be a promising avenue to further examine hypotheses related to failure modes of equipment and possible management response strategies of clinicians.