Wound-Specific Oral Nutritional Supplementation Can Reduce the Economic Burden of Pressure Injuries for Nursing Homes: Results from an Economic Model
Bibliographic record
Abstract
Objectives: To measure the cost savings and staff time savings of wound-specific oral nutritional supplements (WS-ONS) for patients with pressure injuries (PIs) in an average US nursing home in one year. Methods: Using evidence on how WS-ONS can impact PI healing time, we created a decision tree model to estimate changes in annual nursing home cost and staff time needed to treat PIs, between WS-ONS and standard of care. Cost savings were modeled as the reduced costs (in 2021 USD) of treating PIs due to improved healing time for a typical nursing home. Staff time was modeled using a time per task approach with tasks based on current PI treatment guidelines. The study period was one year, and the cost savings were measured from a US nursing home perspective. Results: A typical US nursing home with 85 residents would have 16 PI cases per year. Depending on the PI stage, WS-ONS reduced time to healing among patients with PI by 5.7 to 7.9 weeks compared to standard of care. WS-ONS use during PI reduced nursing home costs by $6,319 per patient for a Stage 2 PI, $7,651 per patient for a Stage 3 PI, and $16,579 per patient for a Stage 4 PI. The total cost savings from WS-ONS use at the nursing home level were $44,230 for Stage 2 PIs, $15,301 for Stage 3 PIs, and $49,737 for Stage 4 PIs. Across all stages, total annual cost savings for the typical US nursing home was $109,269. Nursing home staff time saving from WS-ONS administration was 65 hours per PI patient or 1,040 hours per nursing home per year. Implications: Nursing homes can realize reduced costs and staff time required to treat PIs from the use of WS-ONS among patients with PIs. Future research should uncover the suitable implementation strategies for nursing homes to use WS-ONS for appropriate patients with PI.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".