Evidence map›Paper›PMID 39560875›Full record

ArticlePharmacoEconomics - open2025

Health Economic Evaluation of Antimicrobial Stewardship, Procalcitonin Testing, and Rapid Blood Culture Identification in Sepsis Care: A 90-Day Model-Based, Cost-Utility Analysis.

Wendy I Sligl, Charles Yan, Jeff Round, Xiaoming Wang, Justin Z Chen, Cheyanne Boehm, Karen Fong, Katelynn Crick, Míriam Garrido Clua, Cassidy Codan and 11 more

Abstract read
In one paragraph

Article in PharmacoEconomics - open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Hospital Cost Components and Predictors inTropical medicine and infectious disease · 2026
    Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Wendy I SliglDepartment of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta and Alberta Health Services, 2-124 Clinical Sciences Building, 8440 112 Street NW, Edmonton, Alberta, T6G 2B7, Canada. wsligl@ualberta.ca.ORCID http://orcid.org/0000-0003-4963-0401
Charles YanInstitute of Health Economics, Edmonton, Alberta, Canada.
Jeff RoundInstitute of Health Economics, Edmonton, Alberta, Canada.
Xiaoming WangProvincial Research and Data Services, Alberta Health Services, Edmonton, Alberta, Canada.
Justin Z ChenDivision of Infectious Diseases, Department of Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada.
Cheyanne BoehmPharmacy Services, Foothills Medical Centre, Alberta Health Services, Calgary, Alberta, Canada.
Karen FongPharmacy Services, University of Alberta Hospital, Alberta Health Services, Edmonton, Alberta, Canada.
Katelynn CrickDepartment of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta and Alberta Health Services, 2-124 Clinical Sciences Building, 8440 112 Street NW, Edmonton, Alberta, T6G 2B7, Canada.
Míriam Garrido CluaDepartment of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta and Alberta Health Services, 2-124 Clinical Sciences Building, 8440 112 Street NW, Edmonton, Alberta, T6G 2B7, Canada.
Cassidy CodanDepartment of Critical Care Medicine, Cumming School of Medicine, University of Calgary and Alberta Health Services, Calgary, Alberta, Canada.
Tanis C DingleDivision of Diagnostic and Applied Microbiology, Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada.
Connie ProsserDepartment of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada.
Guanmin ChenDepartment of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada.
Alena Tse-ChangDivision of Pediatric Infectious Diseases, Department of Pediatrics, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada.
Daniel GarrosDivision of Pediatric Critical Care, Department of Pediatrics, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada.
David ZygunDepartment of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta and Alberta Health Services, 2-124 Clinical Sciences Building, 8440 112 Street NW, Edmonton, Alberta, T6G 2B7, Canada.
Dawn OpgenorthDepartment of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta and Alberta Health Services, 2-124 Clinical Sciences Building, 8440 112 Street NW, Edmonton, Alberta, T6G 2B7, Canada.
John M ConlyDepartment of Medicine, Cumming School of Medicine, University of Calgary and Alberta Health Services, Calgary, Alberta, Canada.
Christopher J DoigPharmacy Services, University of Alberta Hospital, Alberta Health Services, Edmonton, Alberta, Canada.
Vincent I LauDepartment of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta and Alberta Health Services, 2-124 Clinical Sciences Building, 8440 112 Street NW, Edmonton, Alberta, T6G 2B7, Canada.
Sean M BagshawDepartment of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta and Alberta Health Services, 2-124 Clinical Sciences Building, 8440 112 Street NW, Edmonton, Alberta, T6G 2B7, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveWe evaluated the cost-effectiveness of a bundled intervention including an antimicrobial stewardship program (ASP), procalcitonin (PCT) testing, and rapid blood culture identification (BCID), compared with pre-implementation standard care in critically ill adult patients with sepsis.

methodsWe conducted a decision tree model-based cost-effectiveness analysis alongside a previously published pre- and post-implementation quality improvement study. We adopted a public Canadian healthcare payer's perspective. Two intensive care units in Alberta with 727 adult critically ill patients were included. Our bundled intervention was compared with pre-implementation standard care. We collected healthcare resource use and estimated unit costs in 2022 Canadian dollars (CAD) over a time horizon from study entry to hospital discharge or death. We calculated the incremental net monetary benefit (iNMB) of the intervention group compared with the pre-intervention group. The primary outcome was cost per sepsis case. Secondary outcomes included readmission rates, Clostridioides difficile infections, mortality, and lengths of stay. Uncertainty was investigated using cost-effectiveness acceptability curves, cost-effectiveness plane scatterplots, and sensitivity analyses.

resultsMean (standard deviation [SD]) cost per index hospital admission was CAD $83,251 ($107,926) for patients in the intervention group and CAD $87,044 ($104,406) for the pre-intervention group, though the difference ($3,793 [$7,897]) was not statistically significant. Costs were higher in the pre-intervention group for antibiotics, readmissions, and C. difficile infections. The intervention group had a lower mean expected cost; $110,580 ($108,917) compared with pre-intervention ($125,745 [$113,210]), with a difference of $15,165 ($8278). There were no statistically significant differences in quality adjusted life years (QALYs) between groups. The iNMB of the intervention group compared with pre-intervention was greater than $15,000 for willingness-to-pay (WTP) per QALY values of between $0 and $100,000. In our sensitivity analysis, the intervention was most likely to be cost-effective in roughly 56% of simulations at all WTP thresholds.

conclusionsOur bundled intervention of ASP, PCT, and BCID among adult critically ill patients with sepsis was potentially cost-effective, but with substantial decision uncertainty.

Identifiers

PMID39560875
PMCPMC11718022

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.