Improving care in surgery – a qualitative study of managers’ experiences of implementing evidence-based practice in the operating room
Bibliographic record
Abstract
Background: More knowledge is needed on the preconditions and circumstances for leading implementation of evidence based practice in the operating room (OR). Effective leadership support is critical to enhance the provision of safer care. The aim of this study was to explore managers’ and clinical leaders’ experiences of implementing evidence-based practice to increase patient safety in the operating room.Methods: The study had a qualitative descriptive design. In all, 25 managers were interviewed, with different surgical specialities (orthopedics, general and pediatric surgery) and operating room suites, from eight hospitals and 15 departments.Results: The organizational structures were defined as key obstacles to implementation. Specifically, lack of a common platform for cooperation between managers from different departments, organizational levels and professional groups impeded the alignment of shared goals and directions. In cases where implementation was successful, well-functioning and supportive relationships between the managers from different professions and levels were crucial along with a strong sense of ownership and control over the implementation process. Whilst managers expressed the conviction that safety was an important issue that was supported by top management, the goal was usually to “get through” as many operations as possible. This created conflicts between either prioritizing implementation of safety measures or production goals, which sometimes led to decisions that were counter to evidence-based practice (EBP). While evidence was considered crucial in all implementation efforts, it might be neglected and mistrusted if hierarchical boundaries between professional subgroups were challenged, or if it concerned preventive innovations as opposed to technical innovations.Conclusions: The preconditions for implementing EBP in the OR are suboptimal; thus addressing leadership, organizational and interprofessional barriers are of vital importance.
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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 | 0.021 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 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".