Diagnostic Reasoning by Expert Clinicians: What Distinguishes Them From Their Peers?

Validating the Korean shorter Diagnostic Thinking Inventory in medical education: a pilot study

PURPOSE

Developing clinical reasoning across the medical curriculum requires valid, reliable, and feasible assessment tools. However, few validated tools are available for the convenient and efficient quantification of clinical reasoning. Thus, this study aimed to create a shorter version of the Diagnostic Thinking Inventory (DTI) and validate it in the Korean medical education context (DTI-SK).

METHODS

The DTI-SK was constructed using content validity and a translation and back-translation process. It comprises two subcategories and 14 items. Its validity and reliability were explored using exploratory and confirmatory factor analyses, mean comparisons of four medical student groups (med 1 to med 4), and internal consistency using Cronbach's α. Two hundred medical students were invited to participate through email, and the survey was administered for 2 weeks.

RESULTS

Data from 136 students were analyzed. Exploratory factor analysis revealed two factors with eigenvalues greater than 1.0 and they together explained 54.65% of the variance. Confirmatory factor analysis demonstrated that the model had acceptable level of fit and convergent validity. Discriminant validity was confirmed using heterotrait-monotrait criterion. Group comparisons demonstrated that the med 4 students showed significantly higher scores than the med 1 and 2 students. The inventory exhibited strong internal consistency for all items (Cronbach's α=0.906).

CONCLUSION

The findings indicated that the DTI-SK is a reliable and valid tool for measuring medical students' clinical reasoning in the context of Korean medical education.

Clinical Reasoning: Perspectives of Expert Clinicians on Reasoning Through Complex Clinical Cases

Introduction Clinical reasoning is a core skill for physicians; most doctors do not attain the level of expertise associated with that of an expert clinician (EC). The purpose of this study is to identify the clinical reasoning strategies ECs prioritize when reasoning through complex cases. Methods We interviewed 14 ECs and performed a thematic analysis to identify strategies ECs prioritize when reasoning through complex clinical cases. The authors chose ECs based on the recognition of clinical and teaching expertise by trainees and other faculty members (ECs within our institution) and institutional recognition of high achievement in medicine and medical education (ECs outside our institution). We used a semi-structured guide to interview each EC, then reviewed and coded the interview transcriptions. We developed themes based on agreements between all transcript reviewers.  Results We interviewed 11 male and three female ECs, one from outside the study institution. Two (14%) ECs were primary care physicians, and the remaining were sub-specialists. The authors organized strategies for clinical reasoning through complex cases around four themes, which were as follows: (1) connecting clinical reasoning to patient context; (2) embracing uncertainty, then reducing it; (3) returning to the patient's bedside; and (4) remaining humble to limit diagnostic errors. Conclusion Clinical reasoning is a core clinical skill of physicians, and this article describes clinical reasoning strategies prioritized by ECs for complex clinical cases. Recognition and integration of these strategies into medical training and clinical educator practice may facilitate the evolution of clinical reasoning skills and reduce diagnostic errors.

Diagnostic errors in musculoskeletal oncology and possible mitigation strategies

The objective of this paper is to explore sources of diagnostic error in musculoskeletal oncology and potential strategies for mitigating them using case examples. As musculoskeletal tumors are often obvious, the diagnostic errors in musculoskeletal oncology are frequently cognitive. In our experience, the most encountered cognitive biases in musculoskeletal oncologic imaging are as follows: (1) anchoring bias, (2) premature closure, (3) hindsight bias, (4) availability bias, and (5) alliterative bias. Anchoring bias results from failing to adjust an early impression despite receiving additional contrary information. Premature closure is the cognitive equivalent of "satisfaction of search." Hindsight bias occurs when we retrospectively overestimate the likelihood of correctly interpreting the examination prospectively. In availability bias, the radiologist judges the probability of a diagnosis based on which diagnosis is most easily recalled. Finally, alliterative bias occurs when a prior radiologist's impression overly influences the diagnostic thinking of another radiologist on a subsequent exam. In addition to cognitive biases, it is also important for radiologists to acknowledge their feelings when making a diagnosis to recognize positive and negative impact of affect on decision making. While errors decrease with radiologist experience, the lack of application of medical knowledge is often the primary source of error rather than a deficiency of knowledge, emphasizing the need to foster clinical reasoning skills and assist cognition. Possible solutions for reducing error exist at both the individual and the system level and include (1) improvement in knowledge and experience, (2) improvement in clinical reasoning and decision-making skills, and (3) improvement in assisting cognition.