In Service of All: Co-Designing an Inclusive Person-Partnered Model of Care in the Canadian Forces Health Services
Bibliographic record
Abstract
Since being formalized in the 1980s, the model of patient-partnered care has become somewhat of a gold-standard in healthcare. Many health organizations have been working to implement this model, including the health services branch of Canada’s military. The military’s implementation of this model has been challenged by several factors, including ongoing sexual misconduct allegations, systemic racism, and the COVID-19 pandemic, among others. \n \nThe goal of this research project was to explore how a patient-partnered care model can be transformed into a person-partnered care (PPC) model that is meaningfully inclusive, diverse, equitable, and accessible (IDEA). This project further aimed to figure out how such a model can be implemented within the health services branch of the Canadian military. \n \nTo this end, the authors used primary and secondary research methods to assess the current state and model of Canada’s military healthcare. Three Horizons, a participatory foresight technique, was then used to design an IDEA PPC care model, and to identify possible opportunities and challenges with the model’s implementation in the military’s health services branch. \n \nThe findings provide an initial model of IDEA PPC for the military’s health services branch. Further research – particularly in terms of engagement or participatory knowledge-building – is required to enhance the initial model concept so it can work in all the varying contexts of military healthcare. Resources will also need to be dedicated to both design the model and to its implementation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.006 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".