CMS Transportable Simulation-Based Training Curriculum in Patient Safety
Bibliographic record
Abstract
Abstract Introduction Patient safety has received significant press and funding for advancement since the landmark Institute of Medicine report in 1999. However, the difficult process of fostering cultural change in medicine requires that new educational methods, curricula, and assessment tools be instituted at the earliest possible opportunity in medical education. Simulation offers a method to assess performance in low-frequency but high-risk situations in an environment closely replicating daily clinical work. Methods This modular package is a transportable simulation-based curriculum designed to provide patient safety and human factors training for health care providers and learners. The curriculum identifies certain ACGME-designated competency domains as being amenable to assessment by simulation. Separately, probe instruments meant to evaluate learner retention of module teaching points and to serve in larger-scale validation studies are specified. The curriculum presents these competency domains and investigative probes within each module's simulation case. The specific areas of focus are (1) clinician recognition of cognitive biases that lead to diagnostic error, (2) teamwork in emergent resuscitations, (3) authority gradients and cultural change (e.g., medical error disclosure), and (4) transitions in care. These elements have repeatedly been determined to contribute significantly to preventable medical error. Using PowerPoint slide shows and simulation cases, the component modules are designed to educate and evaluate health care providers of all levels in these critical patient safety issues. Clinical content of the included simulation cases covers (1) difficult airway management, (2) multipatient multitrauma management, (3) toxic acetaminophen ingestion and antidote complications, and (4) contrast anaphylactoid reaction. Through these participatory learning exercises, the curriculum attempts to promote and ingrain a culture of safety in the participants. Results Participant surveys and performance data of residents and teams were collected and uniformly showed high levels of acceptance and satisfaction with simulation-based medical education. Although measurement of actual improvement in patient outcomes was not possible, surrogate measures of performance were collected. Discussion In a program jointly supported by this project and the study site's risk management department, pediatric residents demonstrated improvement in crucial skills such as airway and resuscitation management, team performance, and overall competency. The modules have been compiled into a stand-alone package for dissemination as a ready reference and for future collaborative research efforts.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.042 | 0.007 |
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".