Changing the ward culture in a clinic during the implementation of person-centred care
Bibliographic record
Abstract
Objective: The purpose of this study was to explore the impact of an intervention on the organizational culture in five hospital wards in Sweden. The organizational culture was measured at the start of the project and compared with data collected five years later. The intervention was aimed at changing activities towards a new evidenced-based care model called the Gothenburg Person-centred Care model (PCC).Methods: In total, 230 registered nurses and assistant nurses participated in this cross-sectional health-care culture survey during 2009 and 2014. The Organizational Values Questionnaire was used.Results: The results indicated cultural change in all five wards at the clinic. A dominating culture of flexibility decreased and a culture of routines and structure increased. The wards moved towards a higher degree of cultural uniformity. The combination of cultural dimensions also seems to have become more equal during the study period.Conclusions: Few studies have focussed on the development of organizational culture in health-care contexts over time. The results suggest that the implementation of a new model of care has an impact on organizational culture. This implies that health-care managers should have confidence in the outcomes from change projects. It seems that systems of dual logic can develop over time to facilitate change and sustainability. However, if a new working model is to change the culture profoundly, it requires years of zealous implementation.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".