Interprofessional collaboration in surgical setting during the implementation of a multimodal analgesia protocol: A qualitative study
Bibliographic record
Abstract
INTRODUCTION: The Enhanced Recovery after Surgery (ERAS) program has been a turning point for healthcare professionals and patient's surgical units. To optimize patient relief, a new multimodal analgesia (MMA) protocol was deployed. Implementing this protocol required several professionals, with their roles and interactions emerging as key factors to explore. OBJECTIVE: The aim of this qualitative study is to describe the interprofessional collaboration (IC) process during the MMA protocol implementation with surgical healthcare professionals. METHOD: A secondary analysis of data from a descriptive qualitative study was conducted. A total of 71 participants, including registered nurses, assistant nurses, managers/educators, residents, surgeons, and pharmacists, took part in semi-structured interviews. Emerging ideas were synthesized using thematic analysis (Braun and Clark, 2006) and then categorized based on constructs defined by the Sunnybrook framework (McLaney et al., 2022). RESULTS: Several subthemes emerged from secondary analysis: professional roles, interprofessional communication, beliefs, interprofessional trust, interprofessional influence, and nurse autonomy. The protocol implementation fostered role clarification, more efficient and relevant communication, highlighted interprofessional values and ethics, and shared decision-making. BENEFITS: Three emerging findings from this analysis: the importance for professionals of having a shared vision, the need for effective and relevant communication, and the importance of fully occupying professional roles. CONCLUSION: Successful MMA protocol implementation relying on IC could optimize pain management for surgical patients in ERAS trajectories. The ERAS program optimized post-surgical pain management, with successful MMA implementation relying on IC. This analysis highlights the importance of involving all relevant professionals in complex interventions like post-op pain relief to maximize outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".