CE
Bibliographic record
Abstract
OBJECTIVE: This study sought to explore the perceptions of health care workers about engaging patients as partners on care redesign teams under a program called Transforming Care at the Bedside (TCAB), and to examine the facilitating factors, barriers, and effects of such engagement. DESIGN: This descriptive, qualitative study collected data through focus groups and individual interviews. Participants included health care providers and managers from five units at three hospitals in a university-affiliated health care center in Canada. METHODS: A total of nine focus groups and 13 individual interviews were conducted in April 2012, 18 months after the TCAB program began in September 2010. Content analysis was used to analyze the qualitative data. FINDINGS: Health care providers and managers benefited from engaging patients in the decision-making process because the patients brought a new point of view. Involving the patients exposed team members to valuable information that they hadn't previously thought about during decision making. CONCLUSION: Health care teams stand to benefit from engaging patients in the change process. Patients contribute a different point of view, and this helps to ensure that the changes proposed and implemented address their needs.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.561 | 0.304 |
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".