Towards Better Health, Social, and Community-Based Services Integration for Patients with Chronic Conditions and Complex Care Needs: Stakeholders’ Recommendations
Bibliographic record
Abstract
The objective was to report on issues related to patients with complex care needs and recommendations identified by 160 key participants at a summit in Quebec City about better integration of primary health care services for patients with chronic diseases and complex care needs. A descriptive qualitative approach was used. While focus groups were led by a facilitator, a rapporteur noted highlights and a research team member took independent notes. All notes were analyzed by using a thematic analysis according to an inductive method. Seven issues were identified, leading to the formulation of recommendations: (1) valuing the experience of the patient; (2) early detecting of a non-homogeneous patient population; (3) defining interprofessional collaboration based on patient needs; (4) conciliating services provided by clinical settings according to a registered clientele-based logic with the population-based logic; (5) working with the community sector; (6) aligning patient-oriented research values with existing challenges to primary care integration; and (7) promoting resource allocation consistent with targeted recommendations. The summit highlighted the importance of engaging all stakeholders in improvement of integrated care for patients with complex care needs. The resulting recommendations target shared priorities towards better health, social, and community-based services integration for these patients.
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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 | 0.036 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".