A cost-effectiveness analysis of mupirocin and chlorhexidine gluconate for Staphylococcus aureus decolonization prior to hip and knee arthroplasty in Alberta, Canada compared to standard of care
Bibliographic record
Abstract
While decolonization of Staphylococcus aureus reduces surgical site infection (SSI) rates following hip and knee arthroplasty, its cost-effectiveness is uncertain. We sought to examine the cost-effectiveness of a decolonization protocol for Staphylococcus aureus prior to hip and knee replacement in Alberta compared to standard care – no decolonization. Decision analytic models and a probabilistic sensitivity analysis were used for a cost-effectiveness analysis, with the effectiveness of decolonization based on a large published pre- and post- intervention trial. The primary outcomes of the models were infections prevented and health care costs. We modelled the cost-effectiveness of decolonization in a hypothetical cohort of adult patients undergoing hip and knee replacement in Alberta, Canada. Information on the incidence of complex surgical site infections (SSIs), as well as the cost of care for patients with and without SSIs was taken from a provincial infection control database, and health administrative data. Use of the decolonization bundle was cost saving compared to usual care ($153/person), and resulted in 16 complex Staphylococcus aureus SSIs annually as opposed to 32 (with approximately 8000 hip or knee arthroplasties performed). The probabilistic sensitivity analysis demonstrated that the majority (84%) of the time the decolonization bundle was cost saving. The model was robust to one-way sensitivity analyses conducted within plausible ranges. There were small upfront costs associated with using a decolonization protocol, however, this model demonstrated cost savings over one year. In a Markov model that considered the impact of a decolonization bundle over a lifetime as it pertained to the need for subsequent joint replacements and patient quality of life, the bundle still resulted in cost savings ($161/person). Decolonization for Staphylococcus aureus prior to hip and knee replacements resulted in cost savings and fewer SSIs, and should be considered prior to these procedures.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".