Using a Common Vision of Partners in Care to Enhance Hospital Collaborative Relationships
Bibliographic record
Abstract
Background: Collaborative care is a philosophy that guides the work of interdisciplinary teams, patients, and their families internationally. Hospital organizations must create and cultivate environments to meet customer, health policy, and legislative mandates for improved collaborative care. This study aimed to inform and aid cultural change related to collaborative care relationships with the goal of improving the quality of care.Methods and Findings: A critical ethnography using mixed methodologies was conducted at a mid-sized non-acute hospital in Ontario, Canada. This article presents Phase 3 of a three-phase study that engaged senior leaders (SLs) in interviews about customer service and collaborative relationships. Phase 3 findings were triangulated with prior Phase 1 study results from healthcare providers (HCPs) and Phase 2 results from mid-level leaders (MLLs). The combined findings from all three phases formed a description of the organization’s culture (self-awareness, congruency, and health), explicated five organizational tensions, and generated questions and innovative change ideas to advance growth toward a shared vision of “partners in care.”Conclusions: A shared conceptual model of partners in care emerged from the shared conversations held in the research focus groups and interviews over the three phases in the study. Organizational questions, tensions, and possibilities were revealed to advance the culture of collaboration with patients, families, and staff. Innovations were identified and implemented to enhance collaborative practice.
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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 | 0.039 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.013 | 0.025 |
| Scholarly communication | 0.020 | 0.019 |
| Open science | 0.003 | 0.034 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".