Understanding the effect of resident duty hour reform: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Concern surrounding the effect of resident fatigue on patient care recently led the National Steering Committee on Resident Duty Hours to publish Canadian recommendations suggesting that duty periods of 24 or more consecutive hours without restorative sleep should be avoided. We sought to characterize how different training programs are preparing for the effect of such changes on education, patient care and provider well-being. METHODS: Using constructivist grounded theory methodology, we conducted 18 one-on-one semistructured interviews with program directors, division directors and department chiefs from 11 residency programs affiliated with one Canadian medical school. We gathered and analyzed data iteratively until we reached theoretical saturation. RESULTS: The key theme articulated by our participants was that changes in resident duty hours would potentially lead to gaps in the provision of clinical care. These changes affect acute care specialties based primarily in the inpatient setting (e.g., medicine, surgery) more than primarily ambulatory (e.g., family medicine) or shift-model based (e.g., emergency) specialties. Potential strategies to address gaps in clinical care include resident-based solutions, faculty-based solutions and solutions based on other providers (e.g., nonacademic physicians, physician extenders). Each solution has unique advantages and disadvantages in terms of education, continuity of care, preparedness for practice and provider well-being. INTERPRETATION: Our data-driven framework serves as a guide for programs to anticipate challenges of satisfying clinical care needs in the face of changes to resident duty hours, while balancing education, care continuity, preparedness for practice and provider well-being. Our findings challenge the "one-size-fits-all" approach to changes to resident duty hours and endorse flexibility in enacting duty hour regulations based on specialty-specific factors.
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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 | 0.002 | 0.000 |
| 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 | 0.000 |
| 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".