Dealing with uncertainty in clinical reasoning: A threshold model and the roles of experience and task framing.
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| Title: | Dealing with uncertainty in clinical reasoning: A threshold model and the roles of experience and task framing. |
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| Authors: | Stojan, Jennifer N., Daniel, Michelle, Hartley, Sarah, Gruppen, Larry |
| Source: | Medical Education. Feb2022, Vol. 56 Issue 2, p195-201. 7p. 1 Diagram, 4 Charts. |
| Subjects: | Hospital medical staff, Judgment (Psychology), Work, Medical students, Uncertainty, Experience, Students, Experiential learning, Descriptive statistics, Medical logic |
| Abstract: | Introduction: Uncertainty is integral to clinical practice and clinical reasoning but has proven difficult to study and model. Little is known about how clinicians manage uncertainty. According to evidence‐based medicine theory, clinicians should utilise new information to reduce uncertainty until reaching action thresholds for further information gathering or treatment. We examined the impact of experience and task framing on uncertainty thresholds and the extent to which these thresholds guided clinical decisions. Finally, we sought to determine the impact of framing by having participants provide threshold responses as a range or as specific numbers. Methods: One hundred sixty‐eight fourth‐year medical students, 93 residents and 72 faculty were presented a case of viral pneumonia with a suspected superimposed bacterial infection. Participants identified their testing and treatment thresholds with either a specific number or an inter‐threshold range of probabilities that would compel them to test further. Afterwards, they were told the patient had a 20% pre‐test probability of a superimposed infection and asked whether they would treat the patient with antibiotics, order additional testing or neither. Responses were compared with their previously stated threshold values to assess decision‐making consistency. Results: Testing thresholds were 15.8%, 20.6% and 25.8%, treatment thresholds were 78.5%, 71.6% and 73.4% and threshold spans (difference between testing and treatment thresholds) were 62.7, 51 and 47.6 for students, residents and faculty, respectively. Sixty‐four percent of respondents made judgements consistent with their thresholds, 28% escalated their decision (doing more than their thresholds predicted) and 7.6% de‐escalated their decision (doing less than their thresholds predicted). Framing had an impact on both faculty and resident decisions and a larger impact on students. Discussion: These findings help us understand how clinical reasoning and threshold determinations vary with clinical experience. As uncertainty can lead to unnecessary testing and cognitive discomfort, examining decision thresholds helps us ascertain how diagnostic and treatment decisions are made. Stojan et al. explore the role of uncertainty in clinical reasoning and demonstrate how testing and treatment threshold determinations vary with clinical experience. [ABSTRACT FROM AUTHOR] |
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| Database: | Psychology and Behavioral Sciences Collection |
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| Abstract: | Introduction: Uncertainty is integral to clinical practice and clinical reasoning but has proven difficult to study and model. Little is known about how clinicians manage uncertainty. According to evidence‐based medicine theory, clinicians should utilise new information to reduce uncertainty until reaching action thresholds for further information gathering or treatment. We examined the impact of experience and task framing on uncertainty thresholds and the extent to which these thresholds guided clinical decisions. Finally, we sought to determine the impact of framing by having participants provide threshold responses as a range or as specific numbers. Methods: One hundred sixty‐eight fourth‐year medical students, 93 residents and 72 faculty were presented a case of viral pneumonia with a suspected superimposed bacterial infection. Participants identified their testing and treatment thresholds with either a specific number or an inter‐threshold range of probabilities that would compel them to test further. Afterwards, they were told the patient had a 20% pre‐test probability of a superimposed infection and asked whether they would treat the patient with antibiotics, order additional testing or neither. Responses were compared with their previously stated threshold values to assess decision‐making consistency. Results: Testing thresholds were 15.8%, 20.6% and 25.8%, treatment thresholds were 78.5%, 71.6% and 73.4% and threshold spans (difference between testing and treatment thresholds) were 62.7, 51 and 47.6 for students, residents and faculty, respectively. Sixty‐four percent of respondents made judgements consistent with their thresholds, 28% escalated their decision (doing more than their thresholds predicted) and 7.6% de‐escalated their decision (doing less than their thresholds predicted). Framing had an impact on both faculty and resident decisions and a larger impact on students. Discussion: These findings help us understand how clinical reasoning and threshold determinations vary with clinical experience. As uncertainty can lead to unnecessary testing and cognitive discomfort, examining decision thresholds helps us ascertain how diagnostic and treatment decisions are made. Stojan et al. explore the role of uncertainty in clinical reasoning and demonstrate how testing and treatment threshold determinations vary with clinical experience. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 03080110 |
| DOI: | 10.1111/medu.14673 |