Health care costs matter: a review of nutrition economics – is there a role for nutritional support to reduce the cost of medical health care?
Bibliographic record
Abstract
Background and aims: As policy-makers assess the value of money spent on health care, research in the field of health economics is expanding rapidly. This review covers a period of 10 years and seeks to characterize the publication of papers at the intersection of health economics and nutrition. Methods: Relevant publications on nutrition care were identified in the medical literature databases using predetermined search criteria. These included nutritional interventions linked to health economic terms with inclusion criteria requiring original research that included clinical outcomes and cost analyses, subjects’ ages ≥18 years, and publications in English between January 2004 and October 2014. Results: Of the 5,646 publications identified in first-round searches, 274 met the specified inclusion criteria. The number of publications linking nutrition to economic outcomes has increased markedly over the 10-year period, with a growing number of studies in both developed and developing countries. Most studies were undertaken in Europe (39%) and the USA and Canada (28%). The most common study setting was hospital (62%) followed by community/noninstitutional care (30%). Of all the studies, 12% involved the use of oral nutritional supplements, and 13% involved parenteral nutrition. The economic outcomes consistently measured were medical care costs (53% of the studies), hospital length of stay (48%), hospital readmission rates (9%), and mortality (25%). Conclusion: The number of publications focused on the economics of nutrition interventions has increased dramatically in recent years. Studies have demonstrated that malnutrition can increase the costs of care and length of hospital stay while corresponding studies show that nutrition interventions can help lower the cost of health care by decreasing the incidence of complications and speeding recovery. As populations age, policies that lead to wider adoption of screening, assessment, and treatment of malnutrition will be important to improve health economic outcomes. Keywords: economics of nutrition interventions, reducing health care costs through nutrition
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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 | 0.007 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".