The Integrated Nutrition Pathway for Acute Care (INPAC): Building consensus with a modified Delphi
Bibliographic record
Abstract
BACKGROUND: Malnutrition is commonly underdiagnosed and undertreated in acute care patients. Implementation of current pathways of care is limited, potentially as a result of the perception that they are not feasible with current resources. There is a need for a pathway based on expert consensus, best practice and evidence that addresses this crisis in acute care, while still being feasible for implementation. METHODS: A modified Delphi was used to develop consensus on a new pathway. Extant literature and other resources were reviewed to develop an evidence-informed background document and draft pathway, which were considered at a stakeholder meeting of 24 experts. Two rounds of an on-line Delphi survey were completed (n = 28 and 26 participants respectively). Diverse clinicians from four hospitals participated in focus groups to face validate the draft pathway and a final stakeholder meeting confirmed format changes to make the pathway conceptually clear and easy to follow for end-users. Experts involved in this process were researchers and clinicians from dietetics, medicine and nursing, including management and frontline personnel. RESULTS: 80% of stakeholders who were invited, participated in the first Delphi survey. The two rounds of the Delphi resulted in consensus for all but two minor components of the Integrated Nutrition Pathway for Acute Care (INPAC). The format of the INPAC was revised based on the input of focus group participants, stakeholders and investigators. CONCLUSIONS: This evidence-informed, consensus based pathway for nutrition care has greater depth and breadth than prior guidelines that were commonly based on systematic reviews. As extant evidence for many best practices is absent, the modified Delphi process has allowed for consensus to be developed based on better practices. Attention to feasibility during development has created a pathway that has greater implementation potential. External validation specifically with practitioner groups promoted a conceptually easy to use format. Test site implementation and evaluation is needed to identify resource requirements and demonstrate process and patient reported outcomes resulting from embedding INPAC into clinical practice.
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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 | 0.263 | 0.238 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.005 | 0.026 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".