Situating Primary Health Care within the International Classification of Functioning, Disability and Health: Enabling the Canadian Family Health Team Initiative
Bibliographic record
Abstract
Primary health care (PHC) mandates the provision of services delivered by a collaborative team of providers, ultimately to improve quality of care and health status. Considering the challenges related to interprofessional collaboration within novel PHC models, we explored how the World Health Organization's (WHO) International Classification of Functioning, Disability and Health (ICF) could facilitate the enactment of PHC teams. The Canadian Family Health Team (FHT) initiative is used as an example. This paper will explore how the ICF could inform the development of a practice model to enable PHC. Three potential barriers to the envisioned enactment of PHC within the espoused Canadian FHT initiative are identified through a critical gaps analysis; lack of (i) philosophical grounding, (ii) developmental and operational directives, and (iii) evaluation methods. An ICF-informed practice model is proposed to overcome these potential barriers. It is argued that the proposed ICF-informed practice model has international implications as a unifying conceptual framework ideally situated to facilitate the provision of comprehensive evidence-based person-centered care by interprofessional collaborative teams within diverse PHC models.
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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 | 0.040 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.025 | 0.021 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".