Process of implementing collaborative care and its impacts on the provision of care and rehabilitation services to patients with a moderate or severe traumatic brain injury
Bibliographic record
Abstract
OBJECTIVE: The introduction of new services in a rehabilitation center is a unique opportunity to introduce a new model of care and services between two institutions. A hospital and a rehabilitation center experienced a clinical management model inspired by an American approach - collaborative care. The purpose of this study was to describe the implementation of this approach and to provide a perception of the quality of care and services provided to patients with moderate or severe traumatic brain injury and to their caregivers. MATERIALS AND METHODS: In this qualitative study, individual semistructured interviews were conducted with patients and their caregivers in the hospital and rehabilitation center where the patients were treated. Individual semistructured interviews were conducted with administrators, and two focus groups were held with clinicians before and after the implementation. RESULTS AND CONCLUSION: Ten days' waiting time were saved with the collaborative approach. Implementing the collaborative care approach has been found to have several benefits, including improved communication, coordination of services between institutions, and better preparation, awareness, and involvement of patients and their families. Administrators, clinicians, patients, and caregivers expressed their opinions on the organization of care and services, the needs and expectations of patients and their caregivers, their participation in terms of roles and responsibilities, their perception of continuity of care, their satisfaction with the care process, and their suggestions for improvements.
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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 | 0.030 | 0.072 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".