• John W Mah, Katherine Bingham, Eric D Dobkin, Liza Malchiodi, Ann Russell, Steven Donahue, Ilene Staff, Michael E Ivy, and Orlando C Kirton.
• Department of Surgery/Critical Care, University of Connecticut School of Medicine, Farmington, Connecticut, USA. jmah@harthosp.org
• Simul Healthc. 2009 Jan 1;4(4):193-9.

IntroductionGroups of evidence-based guidelines were developed into a comprehensive treatment bundle as part of an international-based Surviving Sepsis Campaign to improve treatment of severe sepsis and septic shock. Conventional educational strategies of this sepsis treatment "bundle" may not ensure acceptable knowledge or completion of these specific tasks and may overlook other dynamic factors present during critical moments of a crisis. Simulation using multidisciplinary teams of clinicians through mannequin-based simulations (MDMS) may improve "bundle" compliance by identifying sepsis guideline errors, reinforcing knowledge, and exposing other potential causes of poor performance.MethodsSeventy-four clinicians participated in the MDMS 14 months after hospital-wide introduction of the sepsis bundle. Additionally, each team was given a sepsis treatment-learning packet before the training session. Twelve teams underwent a MDMS of a patient in septic shock. Two evaluators recorded completed sepsis guideline tasks in real time. Sessions were videotaped and reviewed with the team in a postscenario debriefing session. Pre/posttests were also administered.ResultsIndividual participants' pretest scores averaged 64.6% correct. Despite all but one team having at least one knowledgeable member with a pretest score of at least 80%, team task completion averaged only 60.4%. Team mean pretest scores and proportion of tasks completed were significantly correlated (P = 0.007), but correlations between specific tasks and related questions showed no relationship to knowledge.ConclusionInadequate completion of the sepsis guideline tasks during the MDMS could not be explained by inadequate pretest knowledge alone. MDMS may be a useful tool in identifying and exploring these unknown factors.

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