@article{623,
  keywords = {clinical decision-making, cognitive bias, heuristics, misdiagnosis, simulation},
  author = {Ghazwan Altabbaa and Amanda D. Raven and Jason Laberge},
  title = {A simulation-based approach to training in heuristic clinical decision-making.},
  abstract = {<p>Background Cognitive biases may negatively impact clinical decision-making. The dynamic nature of a simulation environment can facilitate heuristic decision-making which can serve as a teaching opportunity. Methods Momentum bias, confirmation bias, playing-the-odds bias, and order-effect bias were integrated into four simulation scenarios. Clinical simulation educators and human factors specialists designed a script of events during scenarios to trigger heuristic decision-making. Debriefing included the exploration of frames (mental models) resulting in the observed actions, as well as a discussion of specific bias-prone frames and bias-resistant frames. Simulation sessions and debriefings were coded to measure the occurrence of bias, recovery from biased decision-making, and effectiveness of debriefings. Results Twenty medical residents and 18 medical students participated in the study. Twenty pairs (of one medical student and one resident) and two individuals (medical residents alone) completed a simulation session. Evidence of bias was observed in 11 of 20 (55%) sessions. While most participant pairs were able to avoid or recover from the anticipated bias, there were three sessions with no recovery. Evaluation of debriefings showed exploration of frames in all the participant pairs. Establishing new bias-resistant frames occurred more often when the learners experienced the bias. Conclusions Instructional design using experiential learning can focus learner attention on the specific elements of diagnostic decision-making. Using scenario design and debriefing enabled trainees to experience and analyze their own cognitive biases.</p>},
  year = {2019},
  journal = {Diagnosis (Berl)},
  volume = {6},
  pages = {91-99},
  month = {12/2019},
  issn = {2194-802X},
  doi = {10.1515/dx-2018-0084},
  language = {eng},
}