The Value of Audit and Feedback Reports in Improving Nutrition Therapy in the Intensive Care Unit
Bibliographic record
Abstract
BACKGROUND: The objective of this study was to determine whether auditing practice and providing feedback in the form of benchmarked site reports is an effective strategy to improve adherence to nutrition guidelines. METHODS: The authors conducted a multicenter observational study in Canadian intensive care units (ICUs). In January 2007, an audit of daily nutrition information was collected (type and amount of nutrition received and strategies to improve nutrition delivery). Each ICU was e-mailed individualized benchmarked performance reports documenting their performance compared with the Canadian Critical Care Nutrition guidelines and in relation to the other ICUs. Nutrition practice was reaudited in May 2008 to evaluate changes in practice. RESULTS: Twenty-six ICUs in Canada participated, with 473 and 486 patients accrued in 2007 and 2008, respectively. The authors observed a significant increase in enteral nutrition (EN) adequacy (from 45.1% to 51.9% for calories, and from 44.8% to 51.5% for protein) and an increase in the percentage of patients receiving EN without parenteral nutrition (from 71.9% to 81.3%). They also observed trends toward improvements in the percentage of patients who had EN started within 48 hours (from 60.3% to 66.8%). There were no significant differences in the use of motility agents or small bowel feeding in patients who had high gastric residual volumes. CONCLUSION: Audit and feedback reports are associated with improvement in some nutrition practices in many ICUs; however, the magnitude of these effects is quite modest. More research is needed to determine the optimal methods of using audit and feedback to improve quality of nutrition care.
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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 | 0.062 | 0.299 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".