Organizational capacity for patient and family engagement in hospital planning and improvement: interviews with patient/family advisors, managers and clinicians
Bibliographic record
Abstract
BACKGROUND: Patient and family engagement (PE) in healthcare planning and improvement achieves beneficial outcomes and is widely advocated, but a lack of resources is a critical barrier. Little prior research studied how organizations support engagement specifically in hospitals. OBJECTIVE: We explored what constitutes hospital capacity for engagement. METHODS: We conducted descriptive qualitative interviews and complied with criteria for rigour and reporting in qualitative research. We interviewed patient/family advisors, engagement managers, clinicians and executives at hospitals with high engagement activity, asking them to describe essential resources or processes. We used content analysis and constant comparison to identify themes and corresponding quotes and interpreted findings by mapping themes to two existing frameworks of PE capacity not specific to hospitals. RESULTS: We interviewed 40 patient/family advisors, patient engagement managers, clinicians and corporate executives from nine hospitals (two < 100 beds, four 100 + beds, three teaching). Four over-arching themes about capacity considered essential included resources, training, organizational commitment and staff support. Views were similar across participant and hospital groups. Resources included funding and people dedicated to PE and technology to enable communication and collaboration. Training encompassed initial orientation and project-specific training for patient/family advisors and orientation for new staff and training for existing staff on how to engage with patient/family advisors. Organizational commitment included endorsement from the CEO and Board, commitment from staff and continuous evaluation and improvement. Staff support included words and actions that conveyed value for the role and input of patient/family advisors. The blended, non-hospital-specific framework captured all themes. Hospitals of all types varied in the availability of funding dedicated to PE. In particular, reimbursement of expenses and compensation for time and contributions were not provided to patient/family advisors. In addition to skilled engagement managers, the role of clinician or staff champions was viewed as essential. CONCLUSION: The findings build on prior research that largely focused on PE in individual clinical care or research or in primary care planning and improvement. The findings closely aligned with existing frameworks of organizational capacity for PE not specific to hospital settings, which suggests that hospitals could use the blended framework to plan, evaluate and improve their PE programs. Further research is needed to yield greater insight into how to promote and enable compensation for patient/family advisors and the role of clinician or staff champions in supporting PE.
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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 | 0.032 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| 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".