Turning for Ulcer Reduction (TURN) Study: An Economic Analysis.
Bibliographic record
Abstract
BACKGROUND: The Turning for Ulcer Reduction (TURN) study was a multisite, randomized controlled trial that aimed to determine the optimal frequency of turning nursing facility residents with mobility limitations who are at moderate and high risk for pressure ulcer (PrU) development. Here we present data from the economic analysis. OBJECTIVES: This economic analysis aims to estimate the economic consequences for Ontario of switching from a repositioning schedule of 2-hour intervals to a schedule of 3-hour or 4-hour intervals. DATA SOURCES: Costs considered in the analysis included those associated with nursing staff time spent repositioning residents and with incontinent care supplies, which included briefs, barrier cream, and washcloths. RESULTS: The total economic benefit of switching to 3-hour or 4-hour repositioning is estimated to be $11.05 or $16.74 per day, respectively, for every resident at moderate or high risk of developing PrUs. For a typical facility with 123 residents, 41 (33%) of whom are at moderate or high risk of developing PrUs, the total economic benefit is estimated to be $453 daily for 3-hour or $686 daily for 4-hour repositioning. For Ontario as a whole, assuming that there are 77,933 residents at 634 LTC facilities, 25,927 (33%) of whom are at moderate or high risk of developing PrUs, the total economic benefits of switching to 3-hour or 4-hour repositioning are estimated to be $286,420 or $433,913 daily, respectively, equivalent to $104.5 million or $158.4 million per year. LIMITATIONS: We did not consider the savings the Ontario Ministry of Health and Long-Term Care might incur should less frequent repositioning reduce the incidence of work-related injury among nursing staff, so our findings are potentially conservative. CONCLUSIONS: A switch to 3-hour or 4-hour repositioning appears likely to yield substantial economic benefits to Ontario without placing residents at greater risk of developing PrUs.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".