How do Hospitals “Walk the Talk”? Exploring the Connection between Hospital Goals and Patient and Family Engagement Practices
Bibliographic record
Abstract
Hospitals are expected by accreditation bodies and governments to communicate their commitment to patient and family engagement (PE). While PE may be a central goal of many hospitals, having PE goals alone may not be sufficient to integrate PE into activities. How PE goals are translated to practices requires investigation. This thesis examined how hospital PE goals are understood and actioned by staff and patient and family partners through a scoping review of the connection between hospital goals and PE activities (paper 1) and a qualitative case study of two clinical programs at one hospital system (papers 2 and 3). The realization factors framework was used to identify PE activities that support goals for PE, and four healthcare logics allowed the exploration of how the two programs behaved in relation to the hospital’s goals: public management (i.e., benefit to society), market (i.e., healthcare efficiency), medical professional (i.e., care quality), and care professional (i.e., patient well-being). Paper 1 contextualized the realization factors framework for healthcare and PE. Paper 2 explored how the hospital conveyed its goals in documents and how 25 staff and patient and family partners described them in relation to the four logics. This paper found a strong emphasis on the care professional logic in both documents and participants. Paper 3 explored the presence or absence of realization factors in the programs to understand how hospital goals are operationalized. Despite pandemic-related challenges, the first program continued its commitment to PE through the patient and family advisory committee (PFAC). However, the PFAC was disbanded in the second program, and the funds were reallocated to address capacity challenges. A greater precarity of realization factors led to waning commitment and support for PFAC activities, opening a window for the market logic to dominate over the care professional logic. Different logics dominated each clinical program at different times, influencing the realization factors used to pursue and enact PE practices. These insights underscore the complexity of translating hospital goals into practices and offer a valuable framework for hospitals to operationalize PE goals in a manner that is both strategic and context-specific.
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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 | 0.025 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".