Economic evaluation of healthcare-associated infection prevention and control in long-term care: a systematic review protocol
Bibliographic record
Abstract
Abstract Background Given the high risk of contracting a healthcare-associated infection in long-term care facilities, infection prevention and control are essential for the quality of care and safety of residents and staff. To develop more effective infection prevention and control interventions in long-term care facilities, it is important to assess the cost-effectiveness and cost-benefit of existing interventions. There are only a few reviews on this subject, but these are not recent and most do not perform an economic evaluation. Moreover, none uses a discounting approach which limits inter-study comparison. To address these gaps, we will conduct a systematic review of economic evaluations related to healthcare-associated infection prevention and control in long-term care facilities using a discounting approach. Methods We will query MEDLINE, Embase, Web of Science, Cochrane, CINAHL, EconLit, JSTOR, and Scopus, as well as the gray literature databases CORDIS and ProQuest. We will include quantitative studies that evaluate four clinical best practices associated with infection prevention and control (hand hygiene, hygiene and sanitation, screening, basic, and additional precautions) and use at least one of five economic analyses (cost-effectiveness, cost-benefit, cost-minimization, cost-utility, cost-consequences). Primary outcomes will include net cost savings, incremental cost-effectiveness ratio, incremental cost per quality-adjusted life year, and incremental cost per disability-adjusted life year. Two co-authors will independently screen and select articles, extract data, and assess the quality of selected articles using the Scottish Intercollegiate Guidelines Network criteria, the Economic Evaluation criteria, and the Cochrane criteria for economic evaluation. Extracted data will be synthesized, and values will be adjusted to 2022 Canadian dollars using the discount rates of 3%, 5%, and 8%. Discussion Information obtained through this systematic review may help researchers and policy makers make more efficient use of limited healthcare resources to ensure the safety and quality of long-term care. Systematic review registration Research registry ID: reviewregistry1210.
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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 | 0.086 | 0.120 |
| Meta-epidemiology (narrow) | 0.007 | 0.007 |
| Meta-epidemiology (broad) | 0.024 | 0.022 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.077 | 0.009 |
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".