Clinical Governance to Enhance User Involvement in Care: A Canadian Multiple Case Study in Mental Health
Bibliographic record
Abstract
BACKGROUND: Individuals with serious mental illness face challenges in managing their health, leading to the need for integrating their needs and preferences in care decisions. One way to enhance collaboration between users and providers is to improve clinical governance; a shared responsibility between managers and providers, supported by healthcare organizations (HCOs), policies, and standards. We applied the concept of clinical governance to understand (1) how managers and providers can enhance the involvement of users in mental health, (2) the contextual and organizational factors that facilitate user involvement in care, and (3) the users' perceptions of their involvement in care. METHODS: We conducted two, in-depth case studies from two clinical teams in Canada offering outpatient care for users with acute mental illness. A total of 25 interviews were carried out with managers, and four focus groups were held with providers. A measure of patient-reported experience was used to evaluate the users' perceptions of their involvement in care. RESULTS: The providers used two methods to involve users in the care planning process: encouraging users to identify their life goals and supporting them to define recovery-oriented objectives. To encourage the adoption of collaborative practices, the managers used various practices such as revising care protocols, strengthening providers' knowledge of best practices and integrating peer-support workers (PSWs) in the team. Compliance with organizational and external commitments/requirements for user involvement, access to specific training and the institutionalization of a culture promoting user involvement facilitated the adoption of collaborative practices. We found that mental health teams that adopt recovery and collaborative practices with users show a high degree of user-perceived involvement in care. CONCLUSION: This is the first study to apply the concept of clinical governance to understand how managerial and clinical practices, and other organizational and contextual factors, can enhance the involvement of mental healthcare users.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.026 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".