Developing a Partnership Model to Address Gaps in Rural Healthcare Provider Training Using Simulation-Based Health Professions Education
Bibliographic record
Abstract
Rural and remote (R&R) healthcare providers experience difficulties accessing continuing medical education, including simulation, to improve their clinical competencies to address the diverse health needs of the rural Canadian population. At the same time, the College of Family Physicians of Canada (CFPC) has identified a need to shift toward a competency-based curriculum to increase access to clinical training using innovative, flexible methods, such as simulation. Simulation is a strategy that can be applied to facilitate this learning by allowing learners to practice clinical skills on a simulator. However, the high cost of simulators is not a practical solution to address the training needs of R&R healthcare providers. In accordance with one of the CFPC's policy considerations, establishing partnerships between relevant sectors such as university research and innovation centers, for-profit organizations (FPO), and not-for-profit organizations (NPOs) to develop and distribute simulators to R&R healthcare providers can help reduce costs and address gaps in health professions education. Modern, Industry 4.0-related technologies such as three-dimensional (3D) printing allow for sustainable and affordable manufacturing of simulators, however, the tools and "know-how" to develop these simulators are currently limited mainly to university research and innovation centers in urban areas. To date, no simulation-focused partnership model exists that addresses how Industry 4.0 augmented simulation technology can make its way from university research and innovation centers into R&R healthcare settings. The proposed solution is to create a simulation-focused partnership model between university research and innovation centers, FPOs, and NPOs to improve the diffusion of Industry 4.0 augmented simulation technology to the R&R Canadian healthcare sector. Diffusing simulators from a research lab to R&R healthcare providers is a sustainable approach aligned with CFPC's policy considerations to strengthen rural medical education, subsequently strengthening rural medical practice.
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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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".