Current Home Care Expenditures for Persons With Leg Ulcers
Bibliographic record
Abstract
Objective The purpose of this study was to gain a better understanding of the home care expenditures incurred in providing care to the population with leg ulcers. Design The study was designed as a descriptive survey and was conducted over a 4-week period during March 1999. Setting and Subjects Persons in a large Ontario urban center with an ulcer below the knee, including the foot, who were receiving nursing services in the home, were eligible for inclusion in the study. Instruments A leg assessment tool, a supply usage form, and a visiting nurses log (all developed by the researchers for the study) were used to collect data. Methods Home care nurses visited all clients and completed an in-depth assessment of their social, medical, and leg ulcer history. Legs were inspected, an ankle brachial pressure index score was determined, and ulcers were examined and measured. For each nursing visit, supply usage, travel and treatment times, and mileage were tracked. Results During the study period, 2270 visits were made (mean treatment time = 26 minutes, mean travel time = 17 minutes) costing $80.62 (Canadian dollars). Supply costs were $21.06. The regional annual home care expenditures were conservatively estimated to be $1.3 million. Conclusion Costs could potentially be reduced by cutting the 40% visit time attributed to travel, decreasing the visit frequency to clients with minimal drainage, and attention to “best practice.”
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".