Characteristics differentiating problem representation synthesis between novices and experts

Formulating a thoughtful problem representation (PR) is fundamental to sound clinical reasoning and an essential component of medical education. Aside from basic structural recommendations, little consensus exists on what characterizes high-quality PRs.

To elucidate characteristics that distinguish PRs created by experts and novices.

Early internal medicine residents (novices) and inpatient teaching faculty (experts) from two academic medical centers were given two written clinical vignettes and were instructed to write a PR and three-item differential diagnosis for each. Deductive content analysis described the characteristics comprising PRs. An initial codebook of characteristics was refined iteratively. The primary outcome was differences in characteristic frequencies between groups. The secondary outcome was characteristics correlating with diagnostic accuracy. Mixed-effects regression with random effects modeling compared case-level outcomes by group.

Overall, 167 PRs were analyzed from 30 novices and 54 experts. Experts included 0.8 fewer comorbidities (p < .01) and 0.6 more examination findings (p = .01) than novices on average. Experts were less likely to include irrelevant comorbidities (odds ratio [OR] = 0.4, 95% confidence interval [CI] = 0.2-0.8) or a diagnosis (OR = 0.3, 95% CI = 0.1-0.8) compared with novices. Experts encapsulated clinical data into higher-order terms (e.g., sepsis) than novices (p < .01) while including similar numbers of semantic qualifiers (SQs). Regardless of expertise level, PRs following a three-part structure (e.g., demographics, temporal course, and clinical syndrome) and including temporal SQs were associated with diagnostic accuracy (p < .01).

Compared with novices, expert PRs include less irrelevant data and synthesize information into higher-order concepts. Future studies should determine whether targeted educational interventions for PRs improve diagnostic accuracy.