Patient Perspectives of the Operationalization of Adult Patient–centred Care at the Primary Care Diabetes Support Program, London, Ontario: A Qualitative Descriptive Study
Bibliographic record
Abstract
OBJECTIVES: Patient-centred care is a hallmark of family medicine, and patient-centred care for diabetes has been associated with better outcomes. The Primary Care Diabetes Support Program (PCDSP) in London, Ontario, uses a patient-centred model of care and targets 3 groups of patients at high risk for diabetes complications: 1) medically complex, 2) socially complex, and 3) those without a primary care provider. We describe, from the patients' perspectives, how the PCDSP operationalizes patient-centred care. METHODS: Using maximum variation sampling, we recruited and interviewed 17 patients regarding their experiences with the PCDSP. We asked patients about the PCDSP's approach to care and its impact on their diabetes management and overall health. We coded interview transcripts using an inductive thematic analysis approach. RESULTS: We identified 8 attributes of PCDSP care that aligned with the principles of patient-centred care: 1) reassurance, 2) education, 3) whole-person care, 4) individualized care, 5) high accessibility, 6) coordinated care, 7) integration of new technologies, and 8) ownership of care. Participants emphasized that they felt the care they received from the PCDSP was tailored to their individual needs; offered accessible, coordinated care with other providers; and gave them access to new medications and technologies as well as the latest research on diabetes care. CONCLUSIONS: Our findings highlight that the PCDSP approach is more holistic than existing patient-centred care models for diabetes described in the literature, which have focussed on education and skills to improve self-management. The attributes identified are mutually reinforcing and our findings reflect a longitudinal, high-quality primary care approach through the PCDSP.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".