Implementation of the Canadian Clinical Practice Guidelines for Nutrition Support: A Multiple Case Study of Barriers and Enablers
Bibliographic record
Abstract
BACKGROUND: The Canadian Nutrition Support Clinical Practice Guidelines (CPGs), published in 2003, were designed to improve nutrition support practices in intensive care units (ICUs). However, their impact to date has been modest. This study aimed to identify important barriers and enablers to implementation of these guidelines. METHODS: Case studies were completed at 4 Canadian ICUs. Semistructured interviews were conducted with 7 key informants at each site. During the interviews, the key informants were asked about their perceptions of the barriers and enablers to implementation of the Canadian Nutrition Support CPGs. Interview transcripts were analyzed qualitatively, using a framework approach. RESULTS: Resistance to change, lack of awareness, lack of critical care experience, clinical condition of the patient, resource constraints, a slow administrative process, workload, numerous guidelines, complex recommendations, paucity of evidence, and outdated guidelines were cited as the main barriers to guideline implementation. Agreement of the ICU team, easy access to the guidelines, ease of application, incorporation into daily routine, education and training, the dietitian as an opinion leader, and open discussion were identified as the primary enabling factors. Although consistent across all sites, the influence of these factors seemed to differ by site and profession. CONCLUSIONS: Our findings suggest that implementation of the Canadian Nutrition Support CPGs is profoundly complex and is determined by practitioner, patient, institutional, and guideline factors. Further research is required to quantify the impact of each barrier and enabler and the mechanism by which they influence guideline adherence.
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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 | 0.014 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| 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".