Rationale and developmental methodology for the SIMPLE approach: A Systematised, Interdisciplinary Malnutrition Pathway for impLementation and Evaluation in hospitals
Bibliographic record
Abstract
AIM: Changing population demographics, service demands, and healthcare provider expectations suggest that a shift is required regarding how malnutrition care is managed in hospitals. The present study aims to build the reason for required change, and to describe the process used to develop a model for managing malnutrition for implementation across six Queensland hospitals. METHODS: A cross-sectional survey of approaches to managing malnutrition in Queensland public hospitals, and development of a new model of care (guided by Knowledge-to-Action Framework and qualitative interviews) for testing within a broader implementation program. RESULTS: Twenty-three surveys were distributed with 21 completed by metropolitan (n = 11), regional (n = 8), and rural/remote (n = 2) settings. Substantial within and across site variance was observed, with care processes focused towards highly individualised, dietitian delivered care. Some early adopter sites demonstrated systematic, interdisciplinary or delegated malnutrition care processes; however, the latter was rarely or never undertaken in eight sites. A model for the Systematised, Interdisciplinary Malnutrition Pathway for impLementation and Evaluation (SIMPLE) in hospitals was drafted based on identified contemporary models and supporting literature. A mixed-methods approach combined survey data with structured interviews conducted in six sites, purposively sampled for maximal variation to iteratively refine the model. Consensus for implementation of the final model was achieved across site clinicians, leaders, and governance structures. CONCLUSIONS: Systematised, delegated, and interdisciplinary nutrition care activities are realistic in at least some settings. A model is now available to provide interdisciplinary care. Next steps including testing implementation will determine if this interdisciplinary model improves malnutrition care delivered in hospitals.
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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 | 0.277 | 0.202 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.006 | 0.020 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.007 | 0.014 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".