ReviewAntimicrobial stewardship & healthcare epidemiology : ASHE2023
Leveraging electronic data to expand infection detection beyond traditional settings and definitions (Part II/III).
Review in Antimicrobial stewardship & healthcare epidemiology : ASHE, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05020418 (Promoting De-Implementation of Inappropriate Antimicrobial Use in Cardiac Device Procedures By Expanding Audit and Feedback), which is not on this map. Cited by 3 papers.
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.
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.
Promoting De-Implementation of Inappropriate Antimicrobial Use in Cardiac Device Procedures By Expanding Audit and Feedback
Who cites it
3 citing papers in PubMed.
- Leveraging a large language model to support expansion of surveillance activities to include cardiovascular implantable device infections in a large, integrated national healthcare system.Infection control and hospital epidemiology · 2026Article
- Automating surveillance for healthcare-associated infections: Rationale and current realities (Part I/III).Antimicrobial stewardship & healthcare epidemiology : ASHE · 2023Review
- The future of automated infection detection: Innovation to transform practice (Part III/III).Antimicrobial stewardship & healthcare epidemiology : ASHE · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rich and complex electronic health record presents promise for expanding infection detection beyond currently covered settings of care. Here, we review the "how to" of leveraging electronic data sources to expand surveillance to settings of care and infections that have not been the traditional purview of the National Healthcare Safety Network (NHSN), including a discussion of creation of objective and reproducible infection surveillance definitions. In pursuit of a 'fully automated' system, we also examine the promises and pitfalls of leveraging unstructured, free-text data to support infection prevention activities and emerging technological advances that will likely affect the practice of automated infection surveillance. Finally, barriers to achieving a completely 'automated' infection detection system and challenges with intra- and interfacility reliability and missing data are discussed.
Identifiers
What OpenQuestion 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 OpenQuestion graph.