Cost-of-illness studies in chronic ulcers: a systematic review
Bibliographic record
Abstract
OBJECTIVE: To systematically review the published academic literature on the cost of chronic ulcers. METHODS: A literature search was conducted in MEDLINE, EMBASE, HealthSTAR, Econlit and CINAHL up to 12 May 2016 to identify potential studies for review. Cost search terms were based on validated algorithms. Clinical search terms were based on recent Cochrane reviews of interventions for chronic ulcers. Titles and abstracts were screened by two reviewers to determine eligibility for full text review. Study characteristics were summarised. The quality of reporting was evaluated using a modified cost-of-illness checklist. Mean costs were adjusted and inflated to 2015 $US and presented for different durations and perspectives. RESULTS: Of 2267 studies identified, 36 were eligible and included in the systematic review. Most studies presented results from the health-care public payer or hospital perspective. Many studies included hospital costs in the analysis and only reported total costs without presenting condition-specific attributable costs. The mean cost of chronic ulcers ranged from $1000 per year for patient out of pocket costs to $30,000 per episode from the health-care public payer perspective. Mean one year cost from a health-care public payer perspective was $44,200 for diabetic foot ulcer (DFU), $15,400 for pressure ulcer (PU) and $11,000 for leg ulcer (LU). CONCLUSIONS: There was large variability in study methods, perspectives, cost components and jurisdictions, making interpretation of costs difficult. Nevertheless, it appears that the cost for the treatment of chronic ulcers is substantial and greater attention needs to be made for preventive measures.
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 | 0.014 | 0.088 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.009 |
| Bibliometrics | 0.023 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".