Need for the Integrated Nutrition Pathway for Acute Care (INPAC): gaps in current nutrition care in five Canadian hospitals
Bibliographic record
Abstract
BACKGROUND: Malnutrition is common in hospitalized patients and is associated with increased mortality, length of stay, and risk of re-admission. The consensus based Integrated Nutrition Pathway for Acute Care (INPAC) was developed and validated to enhance patients' nutrition care and improve clinical outcomes. As part of the More-2-Eat project (M2E), five hospitals implemented INPAC activities (e.g. screening) in a single medical unit. The purpose of this paper is to demonstrate the care gaps with respect to INPAC activities on these five units prior to implementation. Results were used as part of a needs assessment on each unit, demonstrating where nutrition care could be improved and tailoring of implementation was required. METHODS: Cross-sectional data was collected by site research associates (RAs) using a standardized audit form once per week for 4 weeks. The audit contents were based on the INPAC algorithm. All medical charts of patients on the study unit on the day of the audit were reviewed to track routine nutrition care activities (e.g. screening). Data was descriptively displayed with REDCap™ and analyzed using R Studio software. RESULTS: Less than half of patients (249/700, 36%) were screened for malnutrition at admission. Of those screened, 36% (89/246) were at risk for malnutrition yet 36% (32/89) of these patients did not receive a dietitian assessment. Also, 21% (33/157) of patients who were not screened at risk were assessed. At least one barrier to food intake was noted in 85% of patient medical charts, with pain, constipation, nausea or vomiting being the most common. Many of these barriers were addressed through INPAC standard nutrition care strategies that removed the barrier (e.g. 41% were provided medication for nausea). Advanced nutrition care strategies to improve intake were less frequently recorded (39% of patients). CONCLUSION: These results highlight the current state of nutrition care and areas for improvement regarding INPAC activities, including nutrition screening, assessment, and standard and advanced nutrition care strategies to promote food intake. The results also provided baseline data to support buy-in for INPAC implementation in each M2E study unit. TRIAL REGISTRATION: Retrospectively registered ClinTrials.gov Identifier: NCT02800304, June 7, 2016.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".