Elevating Healthcare: Revolutionizing Tradition through Patient-Centric Collaboration in Calgary Foothills. Exploring the Integrated Community Care Model and its Transformative Impact.
Bibliographic record
Abstract
Integrated care is most effective when the system is built around the patient, rather than requiring the patient to navigate the system. This was the guiding principle behind the Calgary Foothills Primary Care Network's case collaborative program, initiated over five years ago. Roughly 20% of Canadians experience mental illness or addiction issues annually, with 57% of those seeking professional mental health care consulting a family doctor first. Modern healthcare complexity demands provider collaboration yet lacks a structured framework for support. Feedback from patients and families highlighted challenges in navigating numerous resources and coordinating care across multiple agencies. In response, the case collaborative initiative was established, bringing together doctors, healthcare professionals, schools, communities, and government services. This collaborative approach addresses the complex health, psychological, and social needs of patients. The model, co-designed by the Primary Care Network and community partners with input from patient advisors, aligns with best practices such as patient-centered care, team-based care, population-focused care, evidence-based and quality improvement. The successful implementation of four case collaboratives has addressed 223 cases, focusing on concerns such as a lack of family resources, coordination of care, housing, financial issues, and social isolation. Evaluation results indicate that 85% of providers believe the model facilitated timely connection to resources, 91% believe it enhanced patients' quality of care, and 100% felt empowered to provide care. Patients reported feeling better supported, emphasizing the collaborative team's significant impact. The strengthened relationships among providers have not only benefited patients directly involved but have created a ripple effect, improving overall service delivery in the community. Our presentation will emphasize the integration of primary health care with patients and families as active partners. We'll outline the transition from traditional primary health practices to an integrated community care model, focusing on the co-design of the case collaborative model, key principles, challenges, learnings, and enablers supporting its success. Our goal is to contribute to a primary care collaborative that leads to better health, care, and value. Our future steps include enhancing patient engagement, transitioning to an inclusive model where families serve as primary referrers, and scaling the model provincially, nationally, and internationally.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".