Exploration of clinical reasoning patterns in high-stakes clinical case simulations

Janet Mee

doi:10.17918/00011051

Clinical reasoning is a core competency for physicians, and deficiencies in this area can seriously affect patient care. Step 3 of the United States Licensing Exam, which all allopathic physicians must pass for licensure, assesses clinical reasoning through its Computer-based Case Simulations (CCS). CCS allows test-takers to demonstrate aspects of clinical reasoning by managing a patient in a simulated environment. Each test-taker's actions are recorded in a transaction log, providing a rich source of data for investigating various aspects of clinical reasoning, particularly data-gathering skills. The current study examines transaction lists for evidence of data-gathering skills to provide feedback to test-takers, helping them improve their clinical reasoning skills. This study employed data mining and process data methods to identify common data-gathering patterns in two CCS cases. Analytic methods included creating N-grams, applying weights, and examining how test takers employed them with k-means clustering. Because of the importance of time in patient care, sequence similarity calculations included common actions, the time elapsed between those actions, and the overall time spent on the case. The sequences were also analyzed to uncover relationships with demographic variables. Results showed that, despite content differences, both cases shared the most common eight N-grams, and the order of actions in the sequences matched the order of physical exam components that are displayed with checkboxes. Combining action and time information showed that test takers have common sequences, but those sequences are relatively unimportant in the context of their total actions. As anticipated, group differences were evident only in comparisons between U.S. and international medical graduates. These results support the proposition that, since the most frequent data-gathering patterns related to how test-takers selected physical examination components from a menu using checkboxes, test-takers may be demonstrating test-taking strategies, rather than data-gathering skills. Recommendations for future research include modifying real and simulated timestamp recording to more accurately reflect real-world constraints and resources, and encouraging thoughtful data-gathering actions. This study also informs future CCS design efforts to collect and record test-taker actions more accurately, enhancing feedback aimed at improving clinical reasoning skills.

Exploration of clinical reasoning patterns in high-stakes clinical case simulations

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Exploration of clinical reasoning patterns in high-stakes clinical case simulations

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