Improving Placement Capacity, Staff Recruitment and Patient Care with Collaborative Placement Models
Bibliographic record
Abstract
In April 2023, the UBC MPT program collaborated with VCH to plan a 4:1 collaborative student placement model. Units were chosen based on student need, patient stability and staffing, with two general surgery and two medical units selected. Preceptors were recruited via an expression of interest.Students self-selected for placements, and both preceptors and students received training informed by a literature review, one month prior to the pilot, running from August 21 to September 22, 2023. Evaluation included student and preceptor experience via online surveys and objective measures, including total placements offered, physiotherapy occasions of service, and new graduate hires into VCH’s New Graduate program. Student surveys had a 56% response rate, with overall positive feedback on opportunities to apply theoretical knowledge and develop clinical reasoning. Students felt they received sufficient feedback and interprofessional opportunities, but noted limited 1:1 time with preceptors.Preceptor surveys had a 100% response rate, with preceptors feeling well-prepared and supported by UBC. They enjoyed the educator role and were open to supervising again. Challenges included managing student expectations for 1:1 time and balancing both documentation reviews and supervision with varying student abilities.Objective data showed a 58% increase in placement capacity at VCH compared to the previous year and a 50% increase in physiotherapy occasions of services for patients during the pilot. New graduate hires from UBC to VCH rose by 67%, with two thirds of those being pilot participants. This pilot demonstrated that collaborative placement models can effectively be implemented to increase placement capacity and may increase recruitment in public health.Future efforts will prioritize enhancing placement experience for all participants, including implementing a comprehensive orientation to ensure students understand the balance between 1:1 time in a collaborative placement and other advantages, including peer learning. Additionally, preceptor support will be strengthened, particularly for managing varying competency levels. The primary aim of this project was to explore whether a 4:1 collaborative placement model could be implemented in acute care to increase placement capacity while secondarily determining the impact on patients and recruitment of new graduates to public health. Following the pilot's success, VCH permanently adopted the 4:1 collaborative model and created a Student Educator position to support preceptors and students. Other BC health authorities and Canadian universities have shown strong interest in replicating the model. To support knowledge translation of the pilot, a comprehensive toolkit is being developed to guide other sites in its implementation.
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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 | 0.054 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.007 | 0.016 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".