A Cost-Effectiveness Model to Determine Ostomy-Related Costs of Care and Health Outcomes Among People With an Ostomy in Canada Using a Ceramide-Infused Skin Barrier
Bibliographic record
Abstract
PURPOSE: The aim of this study was to determine whether a difference exists in the financial impact of the use of a 2-piece ceramide-infused skin barrier (CIB) versus standard of care barrier (SOC) in Ontario and Alberta using a cost-effectiveness model over a 1-year period for people with a fecal or urinary ostomy. DESIGN: A cost-effectiveness model adapted from a previously published work. SUBJECTS AND SETTING: The model was populated with data inputs from a hypothetical cohort of 1000 individuals in Ontario and 4000 in Alberta. Model results were assessed for robustness via the use of deterministic and probabilistic sensitivity analyses. The provinces of Ontario and Alberta were chosen because cost data were readily accessible. The combined population of these provinces accounts for 50% of Canada's population. RESULTS: An expected cost savings of Can$443.13 (US $322.60) and Can$243.84 (US $177.52) per user for the hypothetical cohort of 1000 individuals in Ontario and 4000 in Alberta per year was obtained for those using a CIB versus a non-infused skin barrier in Ontario and Alberta, respectively. The incremental cost effectiveness ratio (ICER) of CIB to SOC per peristomal skin complication (PSC) avoided and per quality-adjusted life day (QALD) gained was approximately Can$2702 (US $1967)/PSC and Can$1266 (US $922)/QALD for Ontario and approximately Can$1487 (US $1083)/PSC and Can$697 (US $507)/QALD for Alberta. Analysis indicated CIBs remained cost-effective across all sensitivity analyses performed. CONCLUSIONS: Finding suggest that a CIB is cost-effective when compared to a barrier not infused with ceramide when applied to persons with an ostomy and residing in the provinces of Alberta and Ontario.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".