Barriers and facilitators to implementing continuous quality improvement programs in colonoscopy services: a mixed methods systematic review
Bibliographic record
Abstract
BACKGROUND AND AIM: Continuous quality improvement (CQI) programs may result in quality of care and outcome improvement. However, the implementation of such programs has proven to be very challenging. This mixed methods systematic review identifies barriers and facilitators pertaining to the implementation of CQI programs in colonoscopy services and how they relate to endoscopists, nurses, managers, and patients. METHODS: We developed a search strategy adapted to 15 databases. Studies had to report on the implementation of a CQI intervention and identified barriers or facilitators relating to any of the four groups of actors directly concerned by the provision of colonoscopies. The quality of the selected studies was assessed and findings were extracted, categorized, and synthesized using a generic extraction grid customized through an iterative process. RESULTS: We extracted 99 findings from the 15 selected publications. Although involving all actors is the most cited factor, the literature mainly focuses on the facilitators and barriers associated with the endoscopists' perspective. The most reported facilitators to CQI implementation are perception of feasibility, adoption of a formative approach, training and education, confidentiality, and assessing a limited number of quality indicators. Receptive attitudes, a sense of ownership and perceptions of positive impacts also facilitate the implementation. Finally, an organizational environment conducive to quality improvement has to be inclusive of all user groups, explicitly supportive, and provide appropriate resources. CONCLUSION: Our findings corroborate the current models of adoption of innovations. However, a significant knowledge gap remains with respect to barriers and facilitators pertaining to nurses, patients, and managers.
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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 | 0.058 | 0.175 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".