Advances in Simulation (Nov 2018)

Detecting latent safety threats in an interprofessional training that combines in situ simulation with task training in an emergency department

  • Thomaz Bittencourt Couto,
  • Joyce Kelly Silva Barreto,
  • Francielly Cesco Marcon,
  • Ana Carolina Cintra Nunes Mafra,
  • Tarso Augusto Duenhas Accorsi

DOI
https://doi.org/10.1186/s41077-018-0083-4
Journal volume & issue
Vol. 3, no. 1
pp. 1 – 7

Abstract

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Abstract Background During in situ simulation, interprofessional care teams practice in an area where clinical care occurs. This study aimed to detect latent safety threats (LST) in a training program, which combined in situ simulation scenarios with just-in-time and just-in-place self-directed task training in an emergency department. We hypothesized this simulation-based training in actual care areas allows the detection of at least one LST per simulation scenario. Methods This prospective observational study (April 2015–March 2016) involved 135 physicians, nurses, and nurse technicians. Training themes selected were arrhythmia, respiratory insufficiency, shock, and cardiopulmonary resuscitation. Simulation weeks occurred every 3 months, with three 10-min scheduled in situ simulation scenarios alternating for each theme daily. The scenarios were followed by co-debriefing by two facilitators (a physician and a nurse). LST were identified by facilitators using a debriefing checklist. Additionally, a room was set up with task-trainers related to each theme. Results The number participants in scenarios was 114 (84% of the population) and in task-training, 101. The number of scenario cancelations was nine, making the final total number to 49 of 58 proposed. Fifty-six LST were observed, with an average of 1.1 per scenario. LST were divided into four categories: equipment (n = 23, 41.1%), teamwork (n = 12, 21.4%), medication (n = 11, 19.6%), and others (n = 10, 17.9%). There was a higher proportion in equipment-related LST (p < 0.01). Conclusions The training allowed a high rate of detecting LST regardless of theme. Equipment-related LST were more frequently found.

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