Sustaining Quality Improvement and Patient Safety Training in Graduate Medical Education
Bibliographic record
Abstract
PURPOSE: Despite an official mandate to incorporate formal quality improvement (QI) and patient safety (PS) training into graduate medical education, many QI/PS curricular efforts face implementation challenges and are not sustained. Educators are increasingly turning to sociocultural theories to address issues such as curricular uptake in medical education. The authors conducted a case study using Bourdieu's concepts of "field" and "habitus" to identify theoretically derived strategies that can promote sustained implementation of QI/PS curricula. METHOD: From October 2010 through May 2011, the authors conducted semistructured interviews with principal authors of studies included in a systematic review of QI/PS curricula and with key informants (identified by study participants) who did not publish on their QI/PS curricular efforts. The authors purposively sampled to theoretical saturation and analyzed data concurrently with iterative data gathering within Bourdieu's theoretical framework. RESULTS: The study included 16 participants representing six specialties in the United States and Canada. Data analysis revealed that academic physicians belong to, and compete for legitimate forms of capital within, two separate but related fields associated with QI/PScurricular implementation: the "academic field" and the "health care delivery field." Respondents used specific strategies toexploit and/or redefine the prevailingforms of legitimate capital in each field to encourage changes inacademic physicians' habitus that would legitimizeQI/PS. CONCLUSIONS: Situating study findings in a sociocultural theory enables articulation of concrete strategies that can legitimize QI/PS in the academic and health care delivery fields. These strategies can promote sustained QI/PS curricula in graduate medical education.
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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 | 0.043 | 0.095 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| 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".