Knowledge Creation at Multidisciplinary Patient Care Meetings: Implications for the Use of Collaborative Information Technology
Bibliographic record
Abstract
This paper describes a study of Bullet Rounds in General Internal Medicine at an urban teaching hospital in Toronto, Canada.Bullet Rounds are multidisciplinary meetings of healthcare professionals involved in patient care.The goal of the study was to examine the processes of the meetings to understand the level of collaboration and knowledge exchange that takes place, the issues faced by such groups, and the potential role of information technology in supporting them.The methodology included data collection through observation, and quantitative analysis of verbal exchanges in Bullet Rounds.Using the Knowledge Management framework, options for support using information technology are discussed.The author concludes that Knowledge portals that can be used for repositories, prompts and sharing may be helpful in the context of Bullet Rounds.The study extends previous work on analysis of verbal exchanges and contributes to knowledge of collaborative practices in multidisciplinary groups meetings of healthcare practitioners.
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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 | 0.052 | 0.157 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.020 | 0.022 |
| Scholarly communication | 0.022 | 0.016 |
| Open science | 0.005 | 0.017 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".