Economic Evaluations on Antimicrobial Stewardship Programme: A Systematic Review
Bibliographic record
Abstract
PURPOSE: To systematically review studies on cost-effectiveness of implementing Antimicrobial stewardship programmes (ASP) in the hospital setting. METHODS: A systematic literature search was performed using electronic databases, such as EMBASE, PubMed/Medline, CINAHL, NHS and CEA Registry from 2000 until 2017. The quality of each included study was assessed using Joanna Briggs Institute Critical Appraisal Checklist for Economic Evaluations and Consolidated Health Economic Evaluation Reporting Standards Statement checklist. RESULTS: Of the 313 papers retrieved, five papers were included in this review after assessment for eligibility. The majority of the studies were cost-effectiveness studies, comparing ASP to standard care. Four included economic studies were conducted from the provider (hospital) perspective while the other study was from payer (National Health System) perspective. The cost included for economic analysis were as following: personnel costs, warded cost, medical costs, procedure costs and other costs. CONCLUSIONS: All studies were generally well-conducted with relatively good quality of reporting. Implementing ASP in the hospital setting may be cost-effective. However, comprehensive cost-effectiveness data for ASP remain relatively scant, underlining the need for more prospective clinical and epidemiological studies to incorporate robust economic analyses into clinical decisions. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.
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 | 0.020 | 0.089 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.010 |
| Bibliometrics | 0.016 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".