Assessing patient partnership among emergency departments in France: a cross-sectional study
Bibliographic record
Abstract
Abstract Objectives This study aims to describe the use of patient partnership, as defined by the Montreal Model, in emergency departments (EDs) in France and report the perception of patient partnership from both the practitioner and patient perspectives. Methods This cross-sectional study was conducted between July 2020 and October 2020. First, a survey was sent to 146 heads of EDs in both teaching hospitals and non-teaching hospitals in France to assess the current practices in terms of patient partnership in service organization, research, and teaching. The perceived barriers and facilitators of the implementation of such an approach were also recorded. Then, semi-structured telephone interviews were carried out with patients involved in a service re-organization project. Results A total of 48 answers (response rate 32.9%) to the survey were received; 33.3% of respondents involved patients in projects relating to service re-organization, 20.8% involved patients in teaching projects, and 4.2% in research projects. Overall, 60.4% of the respondents were willing to involve patients in re-organization or teaching projects. The main barriers mentioned for establishing patient partnership were difficulties regarding patient recruitment and lack of time. The main advantages mentioned were the improvement in patient/caregiver relationship and new ideas to improve healthcare. When interviewed, patients mentioned the desire to improve healthcare and the necessity to involve people with different profiles and backgrounds. A too important personal commitment was the most frequently raised barrier to their engagement. All the patients recognized their positive role, and more generally, the positive role of patient engagement in service re-organization. Conclusion Although this preliminary study indicates a rather positive perception of patient partnership among heads of EDs in France and partner patients, this approach is still not widely applied in practice.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".