Effectiveness of an Adapted SBAR Communication Tool for a Rehabilitation Setting
Bibliographic record
Abstract
Effective communication and teamwork have been identified in the literature as key enablers of patient safety. The SBAR (Situation-Background-Assessment-Recommendation) process has proven to be an effective communication tool in acute care settings to structure high-urgency communications, particularly between physicians and nurses; however, little is known of its effectiveness in other settings. This study evaluated the effectiveness of an adapted SBAR tool for both urgent and non-urgent situations within a rehabilitation setting. In phase 1 of this study, clinical staff, patient and family input was gathered in a focus-group format to help guide, validate and refine adaptations to the SBAR tool. In phase 2, the adapted SBAR was implemented in one interprofessional team; clinical and support staff participated in educational workshops with experiential learning to enhance their proficiency in using the SBAR process. Key champions reinforced its use within the team. In phase 3, evaluation of the effectiveness of the adapted SBAR tool focused on three main areas: staff perceptions of team communication and patient safety culture (as measured by the Agency for Healthcare Research and Quality Hospital Survey on Patient Safety Culture), patient satisfaction (as determined using the Client Perspectives on Rehabilitation Services questionnaire) and safety reporting (including incident and near-miss reporting). Findings from this study suggest that staff found the use of the adapted SBAR tool helpful in both individual and team communications, which ultimately affected perceived changes in the safety culture of the study team. There was a positive but not significant impact on patient satisfaction, likely due to a ceiling effect. Improvements were also seen in safety reporting of incidents and near misses across the organization and within the study team.
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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 | 0.017 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".