Wound management: Investigating the interprofessional decision‐making process
Bibliographic record
Abstract
Our aim is to develop a robust socio-geographical transferable theory outlining the basic social process used by members of an interprofessional health care team when making decisions around wound care management. Using a qualitative multigrounded theory approach, three focus groups were held at the Royal Victoria Regional Health Centre in Barrie, Ontario, Canada, comprised of 13 clinicians who participate in wound care decision-making. Data were analysed using an approach developed for multigrounded theory. A Critical Realist theoretical lens was applied to data analysis in the development of conclusions. Ten categories were identified before thematic saturation. Category interactions developed a perceived basic social process outlining how interprofessional clinicians determine how they approach wound care decisions: patient factors, scope of practice, equipment and supplies, internal clinician factors, knowledge and education, interprofessional team, assessment, wound care specialist consultation, and care plan, as well as documentation and communication. Understanding how wound care decision-making is determined by interprofessional health care providers will assist clinical leaders and policy makers in creating a foundation for determining resource allocation, allowing clinicians to use evidence-based practice to improve patient and clinician satisfaction, wound healing time, decrease costs, and prevent wound recurrence.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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; both teacher heads agree on what is shown here.
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".