ArticleProceedings of the International Symposium of Human Factors and Ergonomics in Healthcare. International Symposium of Human Factors and Ergonomics in Healthcare2018
A MIXED METHODS APPROACH TO TAILORING EVIDENCE-BASED GUIDANCE FOR ANTIBIOTIC STEWARDSHIP TO ONE MEDICAL SYSTEM.
Article in Proceedings of the International Symposium of Human Factors and Ergonomics in Healthcare. International Symposium of Human Factors and Ergonomics in Healthcare, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
Who cites it
1 citing paper in PubMed, 2 citations in OpenAlex.
- Prediction of Antibiotic Susceptibility for Urinary Tract Infection in a Hospital Setting.Antimicrobial agents and chemotherapy · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
Our objective is to operationalize a novel antibiotic advisor, called the personalized weighted incidence syndromic combination antibiogram (pWISCA), intended to help physicians with initial antibiotic choice in hospitals. Clinical decision support tools are a promising technology for providing evidence-based guidance that incorporates data about patients from electronic health records. Nevertheless, congruence with policies and procedures and local experts' opinions, as well as taking into account local resistance data for the medical center's patient population, is needed when selecting and ordering the antibiotic medication options provided by pWISCA. This paper presents findings from applying a mixed methods approach to identify and prioritize antibiotic medications and associated contextual data to display in a CDS tailored to the local hospital. We discuss implications of these findings.
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.