Turning High‐Risk Individuals: An Economic Evaluation of Repositioning Frequency in Long‐Term Care
Bibliographic record
Abstract
Recent evidence suggests that less frequent repositioning of long-term care residents at moderate to high risk of developing pressure ulcers (PrUs) is noninferior to current repositioning standards in preventing PrUs, but the long-term health and economic consequences of less frequent repositioning have not been adequately estimated. Our objective was to estimate the cost-effectiveness of different repositioning strategies (2-, 3-, 4-hour intervals). We conducted a cost-utility analysis using a lifetime horizon based on data from a randomized clinical trial and the literature. We updated a published PrU decision model with resource usage, unit costs, and epidemiological estimates from the literature and from a small observational study. The Ontario Ministry of Health and Long-Term Care perspective was taken. We estimated lifetime costs to be CAN$5,425 (95% credible interval (CrI)=$922-12,166) less per resident with 3-hour repositioning than with 2-hour repositioning and CAN$3,296 (95% CrI=$483-9,738) less than with 4-hour repositioning. The gain in expected quality-adjusted life years from a 3- to a 2-hour repositioning strategy was 0.008, (95% CrI=0.005-0.016) and from a 3- to a 4-hour repositioning strategy was 0.009 (95% CrI=0.007-0.018). Repositioning at 3-hour intervals was the dominant strategy with respect to the incremental cost-effectiveness ratio against the 2- and 4-hour strategies. Sensitivity analysis showed a 99% probability that 3-hour repositioning was a dominant strategy. We concluded that repositioning at 3-hour intervals for residents at moderate or high risk of PrUs and who were cared for on high-density foam mattresses appeared to be the most cost-effective strategy.
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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 | 0.015 | 0.057 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".