Sustaining organizational culture change in health systems
Bibliographic record
Abstract
PURPOSE: The questions addressed by this review are: first, what are the guiding principles underlying efforts to stimulate sustained cultural change; second, what are the mechanisms by which these principles operate; and, finally, what are the contextual factors that influence the likelihood of these principles being effective? The paper aims to discuss these issues. DESIGN/METHODOLOGY/APPROACH: The authors conducted a literature review informed by rapid realist review methodology that examined how interventions interact with contexts and mechanisms to influence the sustainability of cultural change. Reference and expert panelists assisted in refining the research questions, systematically searching published and grey literature, and helping to identify interactions between interventions, mechanisms and contexts. FINDINGS: Six guiding principles were identified: align vision and action; make incremental changes within a comprehensive transformation strategy; foster distributed leadership; promote staff engagement; create collaborative relationships; and continuously assess and learn from change. These principles interact with contextual elements such as local power distributions, pre-existing values and beliefs and readiness to engage. Mechanisms influencing how these principles sustain cultural change include activation of a shared sense of urgency and fostering flexible levels of engagement. PRACTICAL IMPLICATIONS: The principles identified in this review, along with the contexts and mechanisms that influence their effectiveness, are useful domains for policy and practice leaders to explore when grappling with cultural change. These principles are sufficiently broad to allow local flexibilities in adoption and application. ORIGINALITY/VALUE: This is the first study to adopt a realist approach for understanding how changes in organizational culture may be sustained. Through doing so, this review highlights the broad principles by which organizational action may be organized within enabling contextual settings.
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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 | 0.035 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".