Cost-effectiveness of hydrophilic-coated intermittent catheters compared with uncoated catheters in Canada: a public payer perspective
Bibliographic record
Abstract
Study design: A Markov model was used to analyze cost-effectiveness over a lifetime horizon. Objective: To investigate the cost-effectiveness of hydrophilic-coated intermittent catheters (HCICs) compared with uncoated catheters (UCs) among individuals with neurogenic bladder dysfunction (NB) due to spinal cord injury (SCI). Setting: A Canadian public payer perspective based on data from Ontario; including a scenario analysis from the societal perspective. Methods: A previously published Markov decision model was modified to compare the lifetime costs and quality-adjusted life years (QALYs) for the two interventions. Three renal function and three urinary tract infection (UTI) health states as well as other catheter-related events were included. Scenario analyses, including utility gain from compact catheter and phthalate free catheter use, were performed. Deterministic and probabilistic sensitivity analyses were conducted to evaluate the robustness of the model. Results: The model predicted that a 50-year-old patient with SCI would gain an additional 0.72 QALYs if HCICs were used instead of UCs at an incremental cost of $48,016, leading to an incremental cost-effectiveness ratio (ICER) of $66,634/QALY. Moreover, using HCICs could reduce the lifetime number of UTI events by 11%. From the societal perspective, HCICs cost less than UCs, while providing superior outcomes in terms of QALYs, life years gained (LYG), and UTIs. The cost per QALY further decreased when health-related quality-of-life (HRQoL) gains associated with compact HCICs or catheters not containing phthalates were included. Conclusion: In general, ICERs in the range of CAD$50–100,000 could be considered cost-effective. The ICERs for the base case and sensitivity analyses suggest that HCICs could be cost-effective. From the societal perspective, HCICs were associated with potential cost savings in our model. The results suggest that reimbursement of HCICs should be considered in these settings.
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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".