Hospital capacity for patient engagement in planning and improving health services: a cross-sectional survey
Bibliographic record
Abstract
BACKGROUND: Patient engagement (PE) in planning or improving hospital facilities or services is one approach for improving healthcare delivery and outcomes. To provide evidence on hospital capacity needed to support PE, we described the attributes of hospital PE capacity associated with clinical quality measures. METHODS: We conducted a cross-sectional survey of general and specialty hospitals based on the Measuring Organizational Readiness for Patient Engagement framework. We derived a PE capacity index measure, and with Multiple Correspondence Analysis, assessed the association of PE capacity with hospital type, and rates of hand-washing, C. difficile infection rates and 30-day readmission. RESULTS: Respondents (91, 66.4%) included general: < 100 beds (48.4%), 100+ beds (27.5%), teaching hospitals (11.0%) and specialty (13.2%) hospitals. Most featured PE in multiple clinical and corporate departments. Most employed PE in a range of Planning (design/improve facilities 94.5%, develop strategic plans 87.9%), Evaluation/Quality Improvement (accreditation 91.2%, develop QI plans 90.1%) and Service Delivery activities (develop information/communication aids 92.3%). Hospitals enabled PE with multiple supports (median 12, range 0 to 25), most often: 76.9% strategic plan recognizes PE, 74.7% patient/family advisory council, and 69.2% pool of patient volunteers; and least often: 30.0% PE staff, 26.4% PE funding and 16.5% patient reimbursement or 3.3% compensation. Hospitals employed a range of less (inform, consult) and more (involve, partner) active modes of engagement. Two variables accounted for 29.6% of variance in hospital PE capacity index measure data: number of departments featuring PE and greater use of active engagement modes. PE capacity was not associated with general hospital type or clinical quality measures. CONCLUSIONS: Hospitals with fewer resources can establish favourable PE conditions by deploying PE widely and actively engaging patients. Healthcare policy-makers, hospital executives and PE managers can use these findings to allocate PE resources. Future research should explore how PE modes and methods impact clinical outcomes.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".