Net costs of hospital-acquired and pre-admission PUs among older people hospitalised in Ontario
Bibliographic record
Abstract
OBJECTIVE: To determine the net cost of hospital-acquired and pre-admission pressure ulcers (PUs) in an acute-care setting in Ontario, Canada. METHOD: Cases of PUs were identified among hospitalised patients using Ontario Case Costing Initiative (OCCI) data from 2002-2006. Inpatient costs included direct and overhead costs.To determine the net cost of PUs, cases were matched controlling for age, gender, most responsible diagnosis and comorbidity. Mean net costs were estimated using Bayesian linear mixed models methods. Results were also reported by PU severity. RESULTS: In our study, there were 1351 cases of hospital-acquired PUs and 2523 cases of preadmission PUs over 5 years. Net cost of hospital-acquired PU ranged between CA$44000 for a category II PU to CA$90000 for a category IV PU. For pre-admission PU net cost was between CA$11 000 to CA$18500 for category II and category IV PU, respectively.The net cost of treating hospital-acquired PU is higher than pre-admission PU. Costs increase with increasing PU severity. CONCLUSION: The total net adjusted hospitalisation cost of a hospital-acquired PU in Ontario was CA$44000-90000, compared with CA$11 000-18500 for a pre-admission PU. Future studies should determine the attributable cost of PU using patient-level data to verify the accuracy of the study results.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".