<scp>Systematised, Interdisciplinary Malnutrition Program for impLementation and Evaluation</scp> delivers improved hospital nutrition care processes and patient reported experiences – An implementation study
Bibliographic record
Abstract
AIM: Models of hospital malnutrition care reliant on dietitians can be inefficient and of limited effectiveness. This study evaluated whether implementing the Systematised, Interdisciplinary Malnutrition Program for impLementation and Evaluation (SIMPLE) improved hospital nutrition care processes and patientreported experiences compared with traditional practice. METHODS: A multi-site (five hospitals) prospective, pre-post study evaluated the facilitated implementation of SIMPLE, a malnutrition care pathway promoting proactive nutrition support delivered from time of malnutrition screening by the interdisciplinary team, without need for prior dietetic assessment. Implementation was tailored to local site needs and resources. Nutrition care processes delivered to inpatients who were malnourished or at-risk of malnutrition were identified across diagnosis, intervention, and monitoring domains using standardised audits from medical records, foodservice systems and patient-reported nutrition experience measures. RESULTS: Pre-implementation (n = 365) and post-implementation (n = 397) cohorts were similar for age (74 vs 73 years), gender (47.1% vs 48.6% female), and nutrition risk status (46.6% vs 45.3% at-risk). Post-implementation, at-risk participants were more likely to receive enhanced food and fluids (68.5% vs 83.9%; P < .01), nutrition information (30.9% vs 47.2%; P < .01), mealtime assistance where required (61.4% vs 77.9% P = .04), nutrition monitoring (25.2% vs 46.3%; P < .01) and care planning (17.8% vs 27.7%; P = .01). Patient-reported nutrition experience measures confirmed improved nutrition care. There was no difference in dietetic occasions of service per patient (1.51 vs 1.25; P = .83). CONCLUSIONS: Tailored SIMPLE implementation improves nutrition care processes and patient reported nutrition experience measures for at-risk inpatients within existing dietetic resources.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".