Assessing the implementation processes of a large-scale, multi-year quality improvement initiative: survey of health care providers
Bibliographic record
Abstract
BACKGROUND: Beginning in 2012, Lean was introduced to improve health care quality and promote patient-centredness throughout the province of Saskatchewan, Canada with the aim of producing coordinated, system-wide change. Significant investments have been made in training and implementation, although limited evaluation of the outcomes have been reported. In order to better understand the complex influences that make innovations such as Lean "workable" in practice, Normalization Process Theory guided this study. The objectives of the study were to: a) evaluate the implementation processes associated with Lean implementation in the Saskatchewan health care system from the perspectives of health care professionals; and b) identify demographic, training and role variables associated with normalization of Lean. METHODS: Licensed health care professionals were invited through their professional associations to complete a cross-sectional, modified, online version of the NoMAD questionnaire in March, 2016. Analysis was based on 1032 completed surveys. Descriptive and univariate analyses were conducted. Multivariate multinomial regressions were used to quantify the associations between five NoMAD items representing the four Normalization Process Theory constructs (coherence, cognitive participation, collective action and reflexive monitoring). RESULTS: More than 75% of respondents indicated that neither sufficient training nor resources (collective action) had been made available to them for the implementation of Lean. Compared to other providers, nurses were more likely to report that Lean increased their workload. Significant differences in responses were evident between: leaders vs. direct care providers; nurses vs. other health professionals; and providers who reported increased workload as a result of Lean vs. those who did not. There were no associations between responses to normalization construct proxy items and: completion of introductory Lean training; participation in Lean activities; age group; years of professional experience; or employment status (full-time or part-time). Lean leader training was positively associated with proxy items reflecting coherence, cognitive participation and reflexive monitoring. CONCLUSIONS: From the perspectives of the cross-section of health care professionals responding to this survey, major gaps remain in embedding Lean into healthcare. Strategies that address the challenges faced by nurses and direct care providers, in particular, are needed if intended goals are to be achieved.
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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 | 0.058 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".