Improving clinical reasoning and communication during handover: An intervention study of the BRIEF-C tool
Bibliographic record
Abstract
BACKGROUND: Existing handover communication tools often lack a clear theoretical foundation, have limited psychometric evidence, and overlook effective communication strategies for enhancing diagnostic reasoning. This oversight becomes critical as communication breakdowns during handovers have been implicated in poor patient care. To address these issues, we developed a structured communication tool: Background, Responsible diagnosis, Included differential diagnosis, Excluded differential diagnosis, Follow-up, and Communication (BRIEF-C). It is informed by cognitive bias theory, shows evidence of reliability and validity of its scores, and includes strategies for actively sending and receiving information in medical handovers. DESIGN: A pre-test post-test intervention study. SETTING: Inpatient internal medicine and orthopaedic surgery units at one tertiary care hospital. INTERVENTION: The BRIEF-C tool was presented to internal medicine and orthopaedic surgery faculty and residents who participated in an in-person educational session, followed by a 2-week period where they practised using it with feedback. MEASUREMENTS: Clinical handovers were audiorecorded over 1 week for the pre- and again for the post-periods, then transcribed for analysis. Two faculty raters from internal medicine and orthopaedic surgery scored the transcripts of handovers using the BRIEF-C framework. The two raters were blinded to the time periods. RESULTS: A principal component analysis identified two subscales on the BRIEF-C: diagnostic clinical reasoning and communication, with high interitem consistency (Cronbach's alpha of 0.82 and 0.99, respectively). One sample t-test indicated significant improvement in diagnostic clinical reasoning (pre-test: M=0.97, SD=0.50; post-test: M=1.31, SD=0.64; t(64)=4.26, p<0.05, medium to large Cohen's d=0.63) and communication (pre-test: M=0.02, SD=0.16; post-test: M=0.48, SD=0.83); t(64)=4.52, p<0.05, large Cohen's d=0.83). CONCLUSION: This study demonstrates evidence supporting the reliability and validity of scores on the BRIEF-C as good indicators of diagnostic clinical reasoning and communication shared during handovers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".