Effects of Clinical Supervision on Resident Learning and Patient Care During Simulated ICU Scenarios*
Bibliographic record
Abstract
OBJECTIVES: Closer supervision of residents' clinical activities has been promoted to improve patient safety, but may additionally affect resident participation in patient care and learning. The objective of this study was to determine the effects of closer supervision on patient care, resident participation, and the development of resident ability to care independently for critically ill patients during simulated scenarios. DESIGN: This quantitative study represents a component of a larger mixed-methods study. Residents were randomized to one of three levels of supervision, defined by the physical proximity of the supervisor (distant, immediately available, and direct). Each resident completed a simulation scenario under the supervision of a critical care fellow, immediately followed by a modified scenario of similar content without supervision. SETTING: The simulation center of a tertiary, university-affiliated academic center in a large urban city. SUBJECTS: Fifty-three residents completing a critical care rotation and 24 critical care fellows were recruited between April 2009 and June 2010. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: During the supervised scenarios, lower team performance checklist scores were obtained for distant supervision compared with immediately available and direct supervision (mean [SD], direct: 72% [12%] vs immediately available: 77% [10%] vs distant: 61% [11%]; p = 0.0013). The percentage of checklist items completed by the residents themselves was significantly lower during direct supervision (median [interquartile range], direct: 40% [21%] vs immediately available: 58% [16%] vs distant: 55% [11%]; p = 0.005). During unsupervised scenarios, no significant differences were found on the outcome measures. CONCLUSIONS: Care delivered in the presence of senior supervising physicians was more comprehensive than care delivered without access to a bedside supervisor, but was associated with lower resident participation. However, subsequent resident performance during unsupervised scenarios was not adversely affected. Direct supervision of residents leads to improved care process and does not diminish the subsequent ability of residents to function independently.
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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 | 0.003 | 0.028 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".