Exploration of pressure ulcer and related skin problems across the spectrum of health care settings in Ontario using administrative data
Bibliographic record
Abstract
This is a prospective cohort study using population-level administrative data to describe the scope of pressure ulcers in terms of its prevalence, incidence risk, associating factors and the extent to which best practices were applied across a spectrum of health care settings. The data for this study includes the information of Ontario residents who were admitted to acute care, home care, long term care or continuing care and whose health care data is contained in the resident assessment instrument-minimum data set (RAI-MDS) and the health outcomes for better information and care (HOBIC) database from 2010 to 2013. The analysis included 203 035 unique patients. The overall prevalence of pressure ulcers was approximately 13% and highest in the complex continuing care setting. Over 25% of pressure ulcers in long-term care developed one week after discharge from acute care hospitalisation. Individuals with cardiovascular disease, dementia, bed mobility problems, bowel incontinence, end-stage diseases, daily pain, weight loss and shortness of breath were more likely to develop pressure ulcers. While there were a number of evidence-based interventions implemented to treat pressure ulcers, only half of the patients received nutritional interventions.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".