Implementation through translation: a qualitative case study of translation processes in the implementation of quality improvement collaboratives
Bibliographic record
Abstract
BACKGROUND: Quality improvement collaboratives (QICs) are used extensively to implement quality improvement in healthcare, and current research is demonstrating positive yet varying evidence. To interpret the effectiveness results, it is necessary to illuminate the dynamics of QIC implementation in specific contexts. Using Scandinavian institutionalist translation theory as a theoretical framework, this study aims to make two contributions. First, we provide insights into the dynamics of the translation processes inherent in QIC implementation. Second, we discuss the implications of the translation processes as experienced by participating actors. METHODS: We used empirical data from a qualitative case study investigating the implementation of QICs as an approach to quality improvement within a national Danish healthcare quality program. We included two diverse QICs to allow for exploration of the significance of organizational complexity for the translation processes. Data comprised qualitative interviews, participant observation and documentary material. RESULTS: Translation was an inherent part of QIC implementation. Key actors at different organizational levels engaged in translation of their implementation roles, and the QIC content and methodology. They drew on different translation strategies and practices that mainly materialized as kinds of modification. The translations were motivated by deliberate, strategic, and pragmatic rationales, contingent on combinations of features of the actors' organizational contexts, and the transformability and organizational complexity of the QICs. The findings point to a transformative power of translation, as different translations led to various regional and local QIC versions. Furthermore, the findings indicate that translation affects the outcomes of the implementation process and the QIC intervention. Translation may positively affect the institutionalization of the QICs and the creation of professional engagement and negatively influence the QIC effects. CONCLUSION: The findings extends the current research concerning the understanding of the dynamics of the translation processes embedded in the local implementation of QICs, and thus constitute a valuable contribution to a more sustainable and effective implementation of QICs in healthcare improvement. For researchers and practitioners, this highlights translation as an embedded part of the QIC implementation process, and encourages detailed attention to the implications of translation for both organizational institutionalization and realisation of the expected intervention outcomes.
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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 | 0.055 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.019 | 0.018 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".