Understanding the Impact of Residents' Interpersonal Relationships During Emergency Department Referrals and Consultations
Bibliographic record
Abstract
BACKGROUND: Communicating with colleagues is a key physician competency. Yet few studies have sought to uncover the complex nature of relationships between referring and consulting physicians, which may be affected by the inherent relationships between the participants. OBJECTIVE: Our study examines themes identified from discussions about communications and the role of relationships during the referral-consultation process. METHODS: From March to September 2010, 30 residents (10 emergency medicine, 10 general surgery, 10 internal medicine) were interviewed using a semistructured focus group protocol. Two investigators independently reviewed the transcripts using inductive methods and grounded theory to generate themes (using codes for ease of analysis) until saturation was reached. Disagreements were resolved by consensus, yielding an inventory of themes and subthemes. Measures for ensuring trustworthiness of the analysis included generating an audit trail and external auditing of the material by investigators not involved with the initial analysis. RESULTS: Two main relationship-related themes affected the referral-consultation process: familiarity and trust. Various subthemes were further delineated and studied in the context of pertinent literature. CONCLUSIONS: Relationships between physicians have a powerful influence on the emergency department referral-consultation dynamic. The emergency department referral-consultation may be significantly altered by the familiarity and perceived trustworthiness of the referring and consulting physicians. Our proposed framework may further inform and improve instructional methods for teaching interpersonal communication. Most importantly, it may help junior learners understand inherent difficulties they may encounter during the referral process between emergency and consulting physicians.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".