Recognising the importance of informal communication events in improving collaborative care
Bibliographic record
Abstract
BACKGROUND: While the concept of collaboration is highly touted in the literature, most descriptions of effective collaboration highlight formal collaborative events; largely ignored are the informal collaborative events and none focusing on the frequent, 'seemingly' by chance communication events that arise and their role in supporting patient safety and quality care. OBJECTIVE: To identify the types of informal communication events that exist in the inpatient setting and better understand the barriers contributing to their necessity. METHODS: We undertook a constructivist grounded theory study in an inpatient internal medicine teaching unit in Ontario, Canada. Interview and observational data were collected across two phases; in total, 56 participants were consented for the study. Data collection and analysis occurred iteratively; themes were identified using constant comparison methods. RESULTS: Several types of informal communication events were identified and appeared valuable in three ways: (1) providing a better sense of a patient's baseline function in comparison to their current function; (2) gaining a more holistic understanding of the patient's needs; and (3) generating better insight into a patient's wishes and goals of care. Participants identified a number of organisational and communication challenges leading to the need for informal communication events. These included: scheduling, competing demands and the spatial and temporal organisation of the ward. As a result, nursing staff, allied health professionals and caregivers had to develop strategies for interacting with the physician team. CONCLUSION: We highlight the importance of informal communication in supporting patient care and the gaps in the system contributing to their necessity. Changes at the system level are needed to ensure we are not leaving important collaborative opportunities to chance alone.
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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 | 0.058 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.018 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.004 | 0.008 |
| 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".