Leaning on leadership? Understanding how a lean implementation impacts hospital workers’ performance
Bibliographic record
Abstract
This study examines the extent to which a Lean implementation impacts hospital work unit performance. It also explores the extent to which willingness to change and role clarity explain these relationships. The longitudinal data for this study were collected from a Lean implementation study conducted in a Dutch hospital and then analyzed using structural equation modelling. The results reveal that the practice of Lean Leadership behaviour positively affects performance, both directly and indirectly through role clarity. However, other Lean practices, involvement in continuous improvement and Lean techniques, did not enhance hospital performance. The inconsistent findings concerning Lean’s soft practices suggest that major events (the COVID-19 pandemic in this case) can influence the implementation of Lean and the subsequent outcomes, potentially obstructing sustainable results. The novelty of this study is in its multi-wave design to evaluate the long-term effects of Lean and line managers’ leadership behaviour in a hospital context. Furthermore, it enhances our understanding of the mechanisms explaining the relationship between Lean and its outcomes in healthcare.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".