Food and nutritional care quality indicators in hospital
Bibliographic record
Abstract
Hospital malnutrition and increased prevalence of hospitalized patients with chronic diseases require hospital improvements in nutritional care quality. This study describes the construction of indicators to assess the quality of hospital food and nutritional care. We obtained a data bank containing information about 37 hospitals as well as their Hospital Food and Nutrition Service (HFNS) applying a questionnaire to the HFNS coordinators of each institution. We collected data about the activities of the clinical dietitians and administrative dietitian, meal production and management, and characteristics of the hospital diet. We grouped the obtained data into two corpora of actions, designated Nutritional Care Quality (NCQ) and Food Service Quality (FSQ). Each corpora comprised four indicators. The NCQ indicators included inpatient dietary coverage actions, evaluation and monitoring of nutritional status actions, actions on integration of nutritional assistance activities within the team, and actions supporting diet therapy. The FSQ indicators comprised mediation actions with users and other hospital sectors, autonomy and management control actions, meal production and qualification actions, and staff qualification actions. Systematizing the NCQ and FSQ indicators is important to support the Food and Nutritional Care Quality in Hospitals (FNCQH).
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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 | 0.011 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".