Interprofessional collaboration in home-based community care programs: A leadership imperative
Bibliographic record
Abstract
Community Paramedic (CP) services are relatively new in home-based community care, and as these programs expand, there are additional opportunities for leadership in interprofessional and cross-sectoral collaboration. Understanding the unique contributions of each health care provider can ensure that a patient-centered approach remains forefront. This qualitative study included 33 participants representing nurses, physicians and CPs involved in home-based community care. Interviews explored attitudes, barriers and enablers to collaboration, role optimization and integration of paramedics into home-based community care and were analyzed with interpretive descriptive methods. Participants recognized the benefits of CP services and positive attitudes motivated them to engage in collaboration to support patient-centered care. Participants stated they require support and leadership to strengthen interprofessional collaboration and care coordination. Strategies such as the removal of silos, forging new networks of collaboration, interprofessional education, and changes in professional regulation for paramedics can support new roles and opportunities for nurses, paramedics and physicians in home-based community care.
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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 | 0.021 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.006 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".