Analyzing models of patient-centered care in Canada through a scoping review and environmental scan
Bibliographic record
Abstract
Aim: The objective of this study was to identify and synthesize models of patient-centered care in Canada and compare them with the normative models described in the literature. Subject and methods: Patient-centered care has gained momentum in the twenty-first century as a component of quality care. During the Covid-19 pandemic, the crisis often shifts the focus to the disease rather than the patient. The multiplicity of Canadian systems, including the federal, provincial, and territorial contexts, made a good case to search for a variety of models. This study was conducted using a scoping review method supported by an environmental scan to identify patient-centered care models in Canada. Results: The study identified 19 patient-centered interventions across Canada. The interventions included bedside interventions, patient-engagement projects at the organizational level, and citizen advisory panels at the system level. The organizational model was the most common. The goals of interventions ranged from enhancing the patient's experience of care to identifying ways to cut costs. In most organizational-level projects, there was a marked tendency to engage patients as members of quality improvement committees. Respecting patient dignity and autonomy in one-on-one clinical interactions was minimally addressed in the models. Conclusion: Health systems are not only technical, biomedical organizations but also socio-political institutions with goals of financial protection, the fair distribution of services and resources, and the meaningful inclusion of the citizens in the system, and thus patients need to be respected as individuals and as collectives within the healthcare system.
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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 | 0.048 | 0.124 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.038 | 0.071 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".