Sustaining improvements in relational coordination following team training and practice change: A longitudinal analysis
Bibliographic record
Abstract
BACKGROUND: Poor communication is a leading cause of errors in health care. Structured interprofessional bedside rounds are a promising model to improve communication. PURPOSE: The aim of the study was to test if an intervention to improve communication and coordination in an inpatient heart failure care unit would result in lasting change. METHODOLOGY/APPROACH: The relational coordination (RC) survey was administered to seven workgroups (i.e., nurses, physicians) at baseline (2015) and three subsequent years following the intervention (team training, leadership development workshops, and structured interprofessional bedside round implementation). Descriptive analysis and mixed-effects models were used to assess the impact of the intervention on improving RC. RESULTS: During the study period (2015-2018), 344 participants completed the survey for an overall response rate of 53.5% (n = 643). Postintervention, the RC index significantly increased from 3.79 to 4.08 (p < .001) and remained significantly higher over 2 years, with an RC index of 4.12 and 4.04, respectively (p < .001). The range of RC scores between and within workgroups narrowed over time, with nonrotating workgroups showing the most improvements. CONCLUSION: Findings indicate that positive changes as a result of the intervention have been sustained, despite high rates of turnover among all workgroups. Notably, positive change in RC was found to be more pronounced for nonrotating workgroups compared to team members who rotate within the hospital (i.e., pharmacists who rotate to other units every month). PRACTICE IMPLICATIONS: This intervention holds promise for teams seeking best practice models of "high-reliability" care organization and delivery. Sustained changes from this intervention represent an important area of future practice-based research.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".