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Record W2769666326 · doi:10.18433/j3nw7g

Economic Evaluations on Antimicrobial Stewardship Programme: A Systematic Review

2017· review· en· W2769666326 on OpenAlexvenueno aff
Nor Haizan Ibrahim, Khalidah Maruan, Hasryn Azzuar Mohd Khairy, Yet Hoi Hong, Ahmad Fauzi Dali, Chin Fen Neoh

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2017
Typereview
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsnot available
Fundersnot available
KeywordsAntimicrobial stewardshipStewardship (theology)Political scienceBiologyAntibioticsMicrobiologyAntibiotic resistance

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.659
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.235
GPT teacher head0.507
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations47
Published2017
Admission routes1
Has abstractyes

Explore more

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