Exploring the evolving concept of ‘patient ownership’ in the era of resident duty hour regulations—experience of residents and faculty in an internal medicine night float system
Bibliographic record
Abstract
BACKGROUND: Despite the use of 'patient ownership' as an embodiment of professionalism and increasing concerns over its loss among trainees, how its development in residents has been affected by duty hour regulations has not been well described. In this qualitative study, we aim to outline the key features of patient ownership in internal medicine, factors enabling its development, and how these have been affected by the adoption of a night float system to comply with duty hour regulations. METHODS: In this qualitative descriptive study, we interviewed 18 residents and 12 faculty internists at one university centre and conducted a thematic analysis of the data focused on the concept of patient ownership. RESULTS: We identified three key features of patient ownership: personal concern for patients, professional capacity for autonomous decision-making, and knowledge of patients' issues. Within the context of a night float system, factors that facilitate development of patient ownership include improved fitness for duty and more consistent interactions with patients/families resulting from working the same shift over consecutive days (or nights). Conversely, the increase in patient handovers, if done poorly, is a potential threat to patient ownership development. Trainees often struggle to develop ownership when autonomy is not supported with supervision and when role-modelling by faculty is lacking. DISCUSSION: These features of patient ownership can be used to frame discussions when coaching trainees. Residency programs should be mindful of the downstream effects of shift-based scheduling. We propose strategies to optimize factors that enable trainee development of patient ownership.
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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 | 0.017 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.026 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".